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🪙 How a Stablecoin is Minted: A Step-by-Step Guide

Yogi Nelson

Welcome to the BlockchainAIForum where your technology questions are answered. Today we take explore the step-by-step process used to “mint” stablecoins. Minting is more than just pressing a button on a website—it involves a structured process combining real-world financial steps and blockchain technology. Stablecoins are blockchain-based tokens designed to maintain a steady value, typically pegged to a fiat currency like the US dollar. But what actually happens when someone “mints” a stablecoin? This article explains, in clear terms, how a fiat-backed stablecoin (like USDC or USDT) is minted, step by step.

📌 1️⃣ User Onboarding and Compliance

Step summary: The user proves their identity and gets authorized to use the stablecoin system.

  • What happens?
    A customer (say, Alice) wants to buy stablecoins. She registers with the issuing company (like Circle for USDC).
    She completes KYC (Know Your Customer) checks: uploading identification, proof of address, and sometimes even undergoing a video verification.
    Compliance teams review her information to prevent fraud, money laundering, or sanctions violations.
  • Tools used: Web forms and apps, compliance software, human compliance officers
  • Physical work: Reviewing documents, customer support for failed KYC

💰 2️⃣ Fiat Deposit

Step summary: The user sends actual money to the issuer.

  • What happens?
    Alice wires $10,000 from her bank account to the stablecoin issuer’s designated bank account. The issuer’s bank confirms receipt.
  • Tools used: SWIFT, ACH, SEPA, payment processors
  • Physical work: Bank staff may review or clear large transactions; finance teams reconcile wires

🔎 3️⃣ Treasury Verification and Approval

Step summary: The issuer confirms the deposit and authorizes minting.

  • What happens?
    The stablecoin company’s treasury team verifies the wire against Alice’s account. They check that the money actually settled (not just pending) and approve the minting amount.
  • Tools used: Banking portals, internal ledgers, compliance software
  • Physical work: Treasury analysts approve transactions; auditors may review records

🛠️ 4️⃣ Blockchain Transaction: Minting

Step summary: The issuer creates new tokens on-chain.

  • What happens?
    An authorized operator accesses the issuer’s blockchain wallet and uses a smart contract function called mint to create 10,000 new tokens. This transaction is submitted to the blockchain network.
  • Technical detail:
    The mint function increases the token supply by the specified amount. Validators confirm and record the transaction.
  • Tools used: Blockchain wallets (e.g., MetaMask, Gnosis Safe), command-line tools, smart contract interfaces
  • Physical/computer work: An employee signs the transaction using secure keys; blockchain nodes confirm it

🔗 5️⃣ Recording and Auditing

Step summary: The issuer updates internal records and ensures accountability.

  • What happens?
    The treasury updates its ledger: Alice’s $10,000 in the bank is matched by 10,000 newly minted tokens. Issuers often maintain 1:1 backing by keeping fiat reserves in segregated accounts.
  • Tools used: Accounting software, audit dashboards, blockchain explorers
  • Physical work: Accountants reconcile records; auditors verify the match between tokens and reserves

📲 6️⃣ Delivery to Customer

Step summary: Alice receives the stablecoins in her wallet.

  • What happens?
    The issuer sends the newly minted 10,000 tokens to Alice’s blockchain address. She sees them in her wallet and can now trade, lend, or hold them.
  • Tools used: Blockchain wallets, blockchain explorers, issuer’s platform for delivery
  • Physical/computer work: Staff initiates the transfer; Alice confirms receipt in her wallet

✅ Conclusion

Minting a stablecoin is not just a “crypto” step but a process that bridges real-world banking and blockchain technology. It involves:

  • Customer onboarding and compliance
  • Receiving and verifying fiat deposits
  • Authorized blockchain minting
  • Careful treasury management and audits
  • Delivering tokens to users

This process ensures that each stablecoin is genuinely backed by real assets, maintaining trust in the system.

📜 Final Note

Stablecoin issuers often publish attestation reports by independent auditors, proving that the total tokens in circulation match the fiat reserves held in bank accounts. This transparency is critical for user confidence in the stablecoin’s peg.

Time to go but first a proverb from Fiji, where they say: “children are like empty pots–they need careful fillling.

Until Next Time,

Yogi Nelson

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WHAT IS THE CONNECTION BETWEEN MORGAN STATE UNIVERSITY AND XRP RIPPLE?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, was submitted by Hiram from Los Angeles, and he wants to know, what is the connection between Morgan State University and XRP Ripple (XRP)?

Hiram, you came to the right place.  Not long ago, I too was wondering about the connection between universities who cater to people of color and blockchain technology.  Your question prompted me to investigate the issue.  I’ll share my discovery and the fascinating connection between Morgan State University (MSU) and XRP.  Let’s commence with a short description of Morgan State University and XRP.

The MSU campus is in Baltimore, Maryland.  MSU was founded in 1867 as a public university dedicated to higher education of African Americans during a time in American history when Black people could not enter “main-stream” universities due to the rampant and institutional racism of the USA.  Today, MSU offers bachelors, masters, and doctorate degrees across dozens of fields, including computer science.  MSU of course fits into the category of Historically Black College and University (HBCU). The MSU campus was declared a national treasure by the National Trust for Historic Preservation!  Holy precious jewel, Batman!  What about XRP, you ask?

XRP is a San Francisco based blockchain and crypto currency company specializing in efficient and low-cost international money transfers.   Unlike Bitcoin, XRP uses a proof of stake consensus and a network of validators, making transactions faster and more energy efficient. XRP established the University Research Blockchain Initiative (URBI) in 2018 with the intent of fostering innovation for the next generation of blockchain engineers at Historically Black Colleges and Universities.  A blockchain with a heart, Batman!

Partnering with universities is not new to XRP.  In fact, XRP has 50+ university partners spread across 26 different countries, has developed the curriculum for 600+ fintech courses, and sponsored over 1,500 research projects.  Essentially, the foundation arm of XRP, known as URBI as noted above, deliberately focuses on developing international software engineering talent.  This makes perfect sense given XRP is in the international money transfer business. 

Let’s now discuss the nature of their partnership. Initiated in 2018, the original collaboration between MSU and XRP bolstered technological bandwidth, set new academic excellence standards, and cultivated a culture of innovation. The partnership gave rise to innovative programming such as the student-led “Morgan-Hack-A-Thon”, which drew about 150 students from 7 HBCUs and featured an XRP Ledger workshop and Finance Challenge Statement from XRP.  Under the terms of the renewed three-year partnership, XRP will donate another $1.05M to MSU.  The additional funding will lead to the creation of opportunities for new programming and research for students and faculty, says XRP.   Holy renewal of vows, Batman! 

From the perspective of MSU, they aim to boost on-going efforts, while also engaging other HBCUs, says, Ali Emdad, MSU Business School Dean. MSU also notes the importance of combining collaborative research with real-world applied learning opportunities, particularly in the fin-tech space.  Ultimately, the goal is to nurture a pipeline of diverse, skilled, and highly trained professionals ready to excel in enterprise blockchain jobs.  The partnership envisions activities that include cutting-edge research endeavors, faculty-led projects intersecting blockchain, artificial intelligence (AI) and machine learning (ML), XRPL development workshops, and an annual national blockchain and fintech conference.  Holy practical partnership, Batman!

I end with this proverb from Belize, where they say: Monkey knows from which limb to swing!

Until next time,

Yogi Nelson

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ARTIFICIAL INTELLIGENCE AND AUTOMOBILES, WHAT’S THE LATEST?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, was submitted by Stelios from California and he wants to know what is happening with artificial intelligence (AI) in automobiles?

Stelios, you came to the right place.  After you asked me this question, I decided to do a little research and found an informative article from PwC.  I’ll start with a word about PwC and thereafter dive into their findings. 

Who is PwC?  PwC is one of the Big 4 accounting firms in America.  PwC is also a major international firm, with offices across the globe.  In addition to accounting services, PwC offers business consulting, market intelligence, and strategic development.  Recently PwC produced a report titled, Is GenAI a game changer for the e-mobility ecosystem? 

https://www.pwc.com/m1/en/publications/is-gen-ai-a-game-changer-for-the-emobility-ecosystem.html

Okay, now it’s time to examine the fundamental premise from where PwC begins.

Anyone who has purchased a new car recently knows automobiles are increasingly more electronic and software driven than mechanical.  The trend started 10 – 15 years ago and has accelerated quickly.  PwC says, software and electric vehicles will be the largest value pool of cars by 2030!

With that as a baseline premise, PwC explored the following question “… how can Generative AI (GenAI) catalyze a transformative revolution in the electric mobility sector leveraging its novel capabilities to build predictive models, develop bespoke services, optimize processes across the value chain and much more”.  Holy forecasting insight Batman! Let’s check out the six predictions in greater detail below.   

Research and Development (R&D).  PwC asserts AI will accelerate research and development (R&D) of new materials and testing processes and thereby reduce production of prototype timelines drastically.  PwC envisions AI will analyze a wide range of potential battery chemistries, for instance.

Generative Design: PwC reports that by using GenAI to analyze the significant increase in data, more design possibilities are accessible.  GenAI enable the design process leading to innovations in and optimized vehicles. 

Demand Forecasting and Inventory Optimization:  Essentially, the argument PwC makes here is that with GenAI automobile manufacturers will be able to forecast with greater precision and thus reduce waste.  For example, the GenAI system will identify demand patterns, seasonality, and potential fluctuations.    

In-Car Personalization:  This one could be particularly cool if done right.  PwC says that with GenAI user preferences, historical user interactions, sensor data, etc., could be used to customize the driving experience to the vehicle owner. We need this for the Batmobile, Batman!

Intelligence Energy Management Systems:  Clearly an electric vehicle is energy efficient, that we know.  However, the point PwC makes goes beyond a particular car and includes the entire production chain.  Wow, I hadn’t considered that.  Good point.

Traffic Control and Optimization:  With GenAI says PwC, traffic patterns, route optimization, and of course congestion management. 

Although AI in cars has existed for 10+ years, PwC concludes with the assertion that GenAI technology will hit the mass market by 2030 and become the dominant technology.  I don’t think there is any reason to disagree. What say you, Stelios?

I conclude with a proverb from Chile, where they say: liar falls faster than a thief. 

Until next time,

Yogi Nelson

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SHOULD YOU BE WORRIED IF YOU LAWYER USES ARTIFICIAL INTELLIGENCE (AI)

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, was submitted by Esquire Nave and he wants to know if he should be worried if his lawyer uses artificial?

Attorney Nava, you came to the right place.  Great question I found an interesting article on this subject, titled AI on Trial, Legal Models Hallucinate in 1 out of 6 Queries. https://hai.stanford.edu/news/ai-trial-legal-models-hallucinate-1-out-6-queries. The report was produced by Stanford’s Human AI Center.  Let’s examine their findings and the implications for the legal profession, beginning with basic findings of fact.

Large language models such as ChatGPT, are not ready for prime time in the courthouse, is the headline.  Stanford’s HAI Center study reports error rates were as high as 69%.  Holy inadmissible evidence Batman! U.S. Supreme Court Chief Justice felt compelled to make a point regarding this problem in his 2023 Annual Report on the Judiciary https://www.supremecourt.gov/publicinfo/year-end/2023year-endreport.pdf

Is there a solution?  People working on retrieval augmented generation (RAG) say yes, and they have it.  According to RAG advocates, RAG reduces hallucinations in domain-specific contexts. RAG proponents claim they can avoid hallucinations and can guarantee legal citations.  Essentially, RAG systems promise to deliver more accurate and trustworthy legal information by integrating a language model with a database of legal documents. Can RAG advocates deliver on these bold claims?  Not yet says, Stanford’s HAI Center.

Stanford put two RAG providers to the test, Lexus-Nexus and Thomson-Reuters.  Stanford found RAG providers are less prone to hallucinations when compared to ChatGPT, etc.  However, given that non-RPG models produced an error rate of 69% that wasn’t much of an accomplishment.  According to Stanford, RAG models hallucinated 17% (1 of 6) when prompted.  Which brings us to the next question, what types of queries were asked of the RAG models.  Answer, there were four basic types.

The Stanford HAI Center says they prompted the models with the following four types of queries:

1) general research questions (questions about doctrine, case holdings, or the bar exam);

2) jurisdiction or time-specific questions (questions about circuit splits and recent changes in the law);

3) false premise questions (questions that mimic a user having a mistaken understanding of the law); and

4) factual recall questions (questions about simple, objective facts that require no legal interpretation). 

The RAG models fell into one of two types of hallucination errors.

The first was to describe the law incorrectly or make a straight factual error.  The second type of error was mis-grounded.  When mis-grounded errors were produced, the AI model describes the law correctly, but cited source which did not support its claims.  Either way, a problem; a big problem.  Mis-grounded hallucinations might be more troublesome because they undermine the point of AI in legal research; namely, AI reduces the time required to conduct research.

Stanford identified three challenges facing RAG model developers.  First, legal retrieval is difficult because the “law” is more than verifiable facts; it also consists of rulings and interpretations.  Second, the complexity of American jurisprudence means retrieval of inappropriate authoritative documents happens often. Last, sycophancy is a concern.  Sycophancy is the tendency of RAG models to agree with the user’s incorrect assumptions. 

Bottom line–RAG models are superior to ChatGPT but require greater transparency, refinement, and not yet ready for Broadway.

We end with a proverb from Estonia:  One fool can ask more questions than 10 men can answer.

Until next time,

Yogi Nelson

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WHAT TOOLS ARE BEING CREATED TO ENSURE ARTIFICIAL INTELLIGENCE SECURITY?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, was submitted by Ish and he wants to know what tools are being created to ensure artificial intelligence (AI) security?

Ish, you came to the right place.  I did a little research and discovered an excellent report from the RAND Corporation.  Let’s review what they say, but first a word about the Rand Corporation.

The RAND Corporation is a non-profit policy analysis organization.  RAND was established in 1948.  Their mission is to advise governments and large corporation on matters of national importance.  RAND was contracted by the United Kingdom to examine the range of tools designed for the development, deployment and use of trustworthy AI in the United Kingdom and the United States.  Wow!  No easy task, Batman!  What did RAND conclude?

Let’s begin with tools for trustworthy AI.  RAND acknowledges the rather obvious point—there is not a universally accept definition for the term “tools for trustworthy AI”.  However, governments and large institutions have consistently articulated certain principles that would enhance trustworthiness in AI.  Those principles include fairness, transparency, accountability, privacy, safety and explainability.  Notwithstanding the lack of consensus, RAND made the attempt and offered the following definition:

Tools for trustworthy AI are specific approaches or methods to help make AI more trustworthy and can help to bridge the gap between the high-level AI principles and characteristics, on the one hand, and the practical implementation of trustworthy AI, on the other.

Based on their definition, RAND identified far more tools for developing trustworthy AI than what I expected—233 to be precise.  RAND divides the tool set into three categories:  technical, procedural, and educational.  You may be surprised to learn the US depends more on technical professionals and academia to develop AI trust tools when compared to the UK.  Additionally, large US corporation develop more trustworthy AI tools compared to their counterparts in the UK.  The UK prefers procedural methosds and relies less on academia. 

As expected, the RAND study offers a series of recommendations.  RAND offers the following guiding principle:

AI tools need to be complemented by a collaborative and inclusive approach that involves multiple perspectives and actors, such as governments, businesses, civil society, academia and international organizations.  In other words, be willing to listen to voices from across the spectrum.  RAND also suggested governments use the following methodology:

  1.  Link up with relevant stakeholders to proactively track and analyze the landscape of tools for trustworthy AI in the UK, the US and beyond.
  2. Systematically capture experiences and lessons learnt on tools for trustworthy AI, share those insights with stakeholders and use them to anticipate potential future directions.
  3. Promote the consistent use of a common vocabulary for trustworthy AI among stakeholders in the UK and the US.
  4. Encourage the inclusion of assessment processes in the development and use of tools for trustworthy AI to gain a better understanding of their effectiveness.
  5. Continue to partner and build diverse coalitions with international organizations and initiatives, and to promote interoperable tools for trustworthy AI.
  6. Join forces to provide resources such as data and computing power to support and democratize the development of tools for trustworthy AI.

Time to end with a proverb from the UK where they say: Every cloud has its silver lining.

Until next time,

Yogi Nelson

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CAN YOU LEARN BLOCKCHAIN TECHNOLOGY IN MALAYSIA?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question was submitted by Ying in Thailand, and she wants to know if she can learn blockchain technology in Malaysia.

Ying, you came to the right place.  Your question shows you are aware that blockchain technology is spreading throughout the world.  The answer is yes, you can learn blockchain technology in Malaysia.  Let’s look at a Malaysian blockchain program and see what they offer.  We begin with the program name.

The name is not particularly creative, but it gets the point across—The Malaysia Blockchain Academy.  Simple and straight forward.  Their physical presence is in their capital, Kuala Lumpur.  A beautiful city, and worth a visit.  I hope to be there later this year.

The academy offers seven on-line courses and one in-person.  I’ll start by talking about the in-person course, named Certified Blockchain Technologist.  According to the Academy, this is an instructor led course designed for anyone who wants to understand blockchain technology.   The course offers to teach blockchain technology using real world examples, case studies and use cases.  By the end of the course you will create your own blockchain and wallet!  If you pass the final and complete a class project, you will earn a certificate that is recognized across the global.  Holy high tech, Batman.  Now an overview of their seven on-line courses.

The Academy does not explicitly indicate the order in which courses should be taken in, nevertheless I will suggest a sequence, beginning with Introduction to Hyperledger Blockchain.  What is Hyperledger Blockchain?  Hyperledger is an open source permissioned blockchain framework designed for global enterprises who want to have advanced privacy controls in place. It was started by The Linux Foundation and now backed by IBM, Intel and SAP Ariba.  What else is available?

Next, I suggest Blockchain Platforms and Framework as that course offers a deep understanding of the technology, with a particular emphasis on IBM technology. Who knows, maybe land a job with IBM?  After you finish those three classes, students are ready for courses four and five, both of which are practical and hands.

I suggest Create a Blockchain Network as the fourth course and Create an App Using Blockchain as the fifth.  These two courses are designed to teach students how to apply the lessons not just theoretical understanding.  That’s awesome, right?  Let’s cover the last three courses.

On to course six, Introduction to Polkadot technology.  I find this offering particularly useful.  Polkadot is a layer one blockchain with a world-wide reach.  Develop an expertise in Polkadot and you are immediately employable or even better create your own company!  Two more courses remain.

Checking in at number seven is a class focused on Fin-Tech.  Fin-Tech is an abbreviation for Financial Technology. Stop and consider all the technology associated with finance and banking and then visualize yourself at the center of that technology.  That is the point of the Fin-Tech class. 

We conclude with a crypto-currency course.  Unfortunately, the common narrative is that blockchain and crypto currency are one and the same.  They are not.  Crypto currency is just one of numerous blockchain applications.  Take this course and understand the technology behind crypto.

Time to go, but first a proverb from Malaysia, where they say:  A tiger dies leaving its stripes, a person dies leaving their name.

Until next time,

Yogi Nelson

Uncategorized

DID THE WHITE HOUSE CREATE AN ARTIFICIAL INTELLIGENCE SAFETY AND SECURITY BOARD?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, comes from Lynn in Florida and she wants to know if the White House created an artificial intelligence safety and security board?

Lynn, you came to the right place.  The answer is yes, the White House did establish an artificial intelligence safety and security board.  Let’s spend the next three minutes examining this situation, including the who, what, why.  We begin with a bit of background.

Last October, President Biden issued an executive order (14110) which directed Department of Homeland Security (DHS) to establish an advisory board that would support the development and management of AI technologies responsibly.  Note, establishing advising boards in Washington is common to the point where there are extensive federal regulations that must be followed, including public notices.  The executive order directed the DHS Secretary to establish the advisory board within 180 days.  DHS made it under the wire Batman! On to the purpose of the Board. 

The purpose includes, but is not limited to, information about emergent risks, threat mitigation guidance, and guardrails for critical infrastructure owners’ and operators’ use of AI, says the Federal Register notice posted on April 29th.  The notice also says, the Board will provide DHS information, advice, and recommendations to advance the security and resilience of our nation’s critical infrastructure in its use of artificial intelligence. Interestingly, the Board has been exempted from the Federal Advisory Committee Act, “…in recognition of the sensitive nature of the subject matter involved.”  Holy government secrets Batman! A word about the Board organization.

Although up to 35 members are permitted, DHS elected to appoint only 22 members.  The Board will meet quarterly. Senior Advisor to the President for Science and Technology, Arati Prabhakar, will function as principal staff.  Although no mention of where the Board will meet, mostly likely and logical, is DHS headquarters. 

Who are the 22 Board members?

  • Sam Altman, CEO, OpenAI;
  • Dario Amodei, CEO and co-founder, Anthropic;
  • Ed Bastian, CEO, Delta Air Lines;
  • Rumman Chowdhury, Ph.D., CEO, Humane Intelligence;
  • Alexandra Reeve Givens, President and CEO, Center for Democracy and Technology
  • Bruce Harrell, Mayor of Seattle, Washington; Chair, Technology and Innovation Committee, United States Conference of Mayors;
  • Damon Hewitt, President and Executive Director, Lawyers’ Committee for Civil Rights Under Law;
  • Vicki Hollub, President and CEO, Occidental Petroleum;
  • Jensen Huang, President and CEO, NVIDIA;
  • Arvind Krishna, Chair and CEO, IBM;
  • Fei-Fei Li, Ph.D., co-director, Stanford Human-centered Artificial Intelligence Institute;
  • Wes Moore, Governor of Maryland;
  • Satya Nadella, Chairman and CEO, Microsoft;
  • Shantanu Narayen, Chair and CEO, Adobe;
  • Sundar Pichai, CEO, Alphabet;
  • Arati Prabhakar, Ph.D., Assistant to the President for Science and Technology; and Director, the White House Office of Science and Technology Policy;
  • Chuck Robbins, Chair and CEO, Cisco; and Chair, Business Roundtable;
  • Adam Selipsky, CEO, Amazon Web Services;
  • Lisa Su, Chair and CEO, Advanced Micro Devices (AMD);
  • Nicol Turner Lee, Ph.D., Senior Fellow and Director of the Center for Technology Innovation, Brookings Institution;
  • Kathy Warden, Chair, CEO and President, Northrop Grumman; and
  • Maya Wiley, President and CEO, The Leadership Conference on Civil and Human Rights.

Do you see is the intermingling of government and corporate America?  For what purpose, you decide.  I guess we won’t know because the meetings are secret. 

Time to go, but first a proverb from Portugal: To a person who understands half a word is enough.

Until next time,

Yogi Nelson

Artificial Intelligence, blockchain association

IS THE BIS (BANK FOR INTERNATIONAL SETTLEMENTS) AN HONEST SOURCE REGARDING DECENTRALIZED FINANCE?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, was submitted by Rufus and he wants to know whether the Bank for International Settlement (BIS) provided an honest assessment of decentralized finance in their recent report, titled Project Atlas? https://www.bis.org/publ/othp76.pdf

Rufus, you came to the right place.  Correct, the BIS did produce Project Atlas, a report that purports to “map out” the world of decentralized and crypto finance.  Project Atlas was released October 2023 by the BIS’s “Innovation Hub”.  Let’s assess their creditability but first a short description of the BIS. 

BIS is headquartered in Switzerland.  BIS is the bank used by central banks to settle transactions.  Holy epidemy of centralized finance Batman!  BIS says it facilitates international monetary cooperation, financial stability and provides banking services to central banks across the globe. 

BIS has an office dedicated to financial innovations.  However, their Innovation Hub did not feel compelled to create decentralized finance.  Given BIS is the epidemy of concentrated finance and its corresponding power, I suppose decentralized finance was not a priority innovation.

BIS says the rise of decentralized finance poses threats and risk.  The BIS is correct. There are threats, there are risks.  The more important questions are, who is threaten and who is at risk by the rise of decentralized finance and crypto? 

According to BIS, central bank regulators are becoming increasingly apprehensive about the scale of crypto markets and their integration with traditional finance.  I can’t help but point out BIS believes research integrity starts by asking central bankers if decentralized finance is a problem! Why not ask central bankers if centralized banking is a problem or what are the problems with centralized banking?  Sorry, for the rude observation Batman!  And, although commercial banks have minimal exposure to crypto markets say the BIS, they are nevertheless nervous.  If that sounds contradictory you are not alone. Let’s move on. 

BIS cites failure of two crypto projects, FTX and Terra, as examples of the “pitfalls” of unregulated finance markets but fails to note neither required taxpayer bailouts.  In other words, decentralized finance poses a threat and risk because business failure is punished with financial loss not rescued by middle class taxpayers. Perhaps BIS has a right to fear the public asking, “why when decentralized finance fails there are no taxpayer bailouts but when traditional finance fails, we are stuck with the bill?”  That indeed is a threat and risk.

BIS says the gaps in their ability to collect decentralize finance data is a threat and risk.  BIS says:

Project Atlas seeks to answer the question: how can central banks harness technologies to gain insights into DeFi markets and gather more reliable and comprehensive statistics on crypto ecosystems?

In other words, BIS, and fellow compadres, want to maintain control.  Their innovation hub consists not to create new technology offering greater freedom; their innovation hub is dedicated to researching how to extend and maintain the incumbent system; a system they own and employ to control the world’s financial system.  Holy transparent agenda Batman!

I will cease but not before pointing out Project Atlas true innovation is it shows centralized finance is threaten by crypto and decentralized finance.  That’s a big deal.

Time to hit the road, but first a proverb from Paraguay: If it doesn’t rain it doesn’t leak, says the man with a damaged roof.

Until next time,

Yogi Nelson

Artificial Intelligence

WHAT IS THE STATE OF ARTIFICIAL INTELLIGENCE

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, was submitted by Jayesh and he wants to know what is the state of artificial intelligence?

Jayesh, you came to the right place; I have your answer.  Last week Stanford University Institute for Human Centered Artificial Intelligence (HAI) released a 500-page report titled, AI Index: The State of AI in 13 charts. The report contains fascinating findings.  Let’s cover the highlights beginning with foundation models by access types in 2023.

A foundation model serves as the fundamental architecture upon which more specialized models are built.  For instance, ChatGPT is a well-known foundation model.  In 2023, there were 149 foundation models released. Fortunately, 66% were open source, meaning they can be freely used and modified by anyone.  In 2021 and 2022, only 31% and 44% were open sourced.  That’s the good news.  The “bad news” –closed source models outperformed open-source models across 10 benchmarks.  Holy lagging behind, Batman!  What about quantity you ask?

When it comes to quantity of AI foundation models in 2023, Google is the leader.  Google released 18, second place Meta knocked out 11, winning the bronze medal was Microsoft with 9.  OpenAI earned honorable mention with 7 models.  One point to consider is the close relationship between Microsoft and Open AI; Microsoft owns 49% of Open AI.  Hence, perhaps a more precise analysis would be to blend the production of Microsoft and Open AI. 

We move onto foundation model by economic sectors and the result is no thunderbolt. If you guessed industry (private for-profit corporations) dominates foundation models, Bingo, move to the head of the class.  With 108 foundation models released in 2023, industry is the epicenter of activity.  Academia lags far behind at only 28, and government is microscopic with only 4 models. 

Building foundation models is expensive.  HAI reports Google spent about $191B, yes, $191B with a “B” to build the Gemini foundation model.  OpenAI, and its ChatGPT came in second with an estimated $78B price tag.  Given these are industry models, investors will expect a return on investments.  Will free models to fade into oblivion in the future?  Let’s see. Speaking of money, private investment in AI is down from the 2021 peak.  Perhaps this explains why ChaptGPT was a sensation in 2022 and 2023 (reaping the results of previous investments?).  Maybe.  HAI reports $96B was spent in 2023, of which 25% went to generative AI.  And of course, private investment dominated in the US. 

What countries are leading the AI race?  Answer:  US and China.  According to HAI, the US released 61 notable foundation models, whereas China had only 15 and the UK 8. 

Let’s wrap up with three more findings, starting with the top five AI corporate adoption use cases.  HAI reports the high flying five are:  contact center automation (26%); personalization (23%); customer acquisition (22%); AI based enhancements of products (22%) and creation of new AI-based products (19%).  When it comes to global opinion, 57% believe AI will change their job in the next five years, 35% say AI is unlikely to impact their job, and 8% are clueless.  Ha, ha! Nervous about AI?  Join the 69% of British nervous Nellies; or perhaps instead chill with South Koreans, where only 44% are nervous.

Time to say goodbye, but first a proverb from Cameroon: Rain does not fall on one roof alone.

Until next time,

Yogi Nelson

Uncategorized

WHAT IS THE AI DIVIDE AND WHAT CAN BE DONE TO BRIDGE IT?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, was submitted by Alfredo and he wants to know what is the AI divide and what can be done to bridge it?

Alfredo, you came to the right place.  Alfredo if you believe history repeats itself you won’t be surprised by an AI divide.  The adoption of new technology follows a well-established pattern, and it goes like this–people and societies with the most resources adopt new technologies first and the rest follow behind.  Initial buyers of automobiles, televisions, telephones, and internet at home were people with resources and access. Adoption and use of AI is following a similar trajectory.  Fortunately, at least one university president, Adela Dela Torre, of San Diego State University (SD State U) has noticed and demands action before the divide turns into a canyon.  Let’s examine what DelaTorre wrote on April 4, on Inside Higher Ed.

She begins with a simple declarative sentence—leaders in higher education must take decisive actions to prevent AI from further exacerbating inequality.  According to DeLaTorre, Amazon Web Services says that 73% of employers report prioritizing hiring talent with AI skills.  Given the direction and obvious impact AI will have on the future workforce, why 27% would not prioritize AI skills is unexplainable!  Holy head in the sand, Batman! Moreover, employers are willing to offer higher salaries (up to 50%) for graduates with AI skills.  What do students say?

Students agree AI will impact their future careers.  In a survey of 8,000 students, 71% expect using AI will be an essential part of their job.  However, the survey revealed noticeable differences that are explainable by access to technology and socio-economic background.   

For example, students with plenty of access to technology (measured by the quantities of smart devices owned) viewed AI positively, less intimidating, or complex.  The same is not true for students from economically disadvantaged neighborhoods, first -generation, low-income, and those coming from under-represented communities.  These students reported a lower use of AI tools, were significantly less comfortable using or understanding AI tools, and see AI less favorably.  The result–an AI divide. 

Will time solve the AI divide?  According to DelaTorre the trend is not a friend.  She says the trend is toward pricey commodification. DelaTorre correctly notes, many AI tools are free today–emphasis today.  However, according to the U.K. non-profit, Jisc, access to a full suite of the most popular AI tools costs nearly $1,300 per year and that is beyond the financial reach of many on the wrong side of the AI divide.

DelaTorre concludes with a call to action by recommending greater partnerships for AI affordability and access between universities and AI companies.  Her second recommendation calls for universities to embrace data-driven discussions and decision-making regarding AI.  Her third point is to enhance training and responsible use of AI.  She concludes with suggesting development of comprehensive AI strategies. 

Given the history of technology adoption and the survey results, the AI divide is legitimate and Dela Torre’s recommendations are on target.  As an AI community, we should acknowledge reality and support those working to bridge the AI, not dismiss their warnings.

Time to go, but first a proverb from the Dominican Republic, where they say:  Don’t be like the shadow: a constant companion, yet not a comrade. 

Until next time,

Yogi Nelson

Artificial Intelligence, Blockchains, France, Productivity

WHAT WILL BE THE IMPACT OF ARTIFICIAL INTELLIGENCE ON

Yogi Nelson

PRODUCTIVITY AND EMPLOYMENT?

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered.   Here no question is mundane.  As a bonus, a proverb is also included.  Today’s question, was submitted by Milagros and she wants to know what will be the impact of artificial intelligence on productivity and employment?

Milagros, you came to the right place.  Two days ago, I viewed an interview with Philippe Aghion.  Aghion is a leading French economist who recently published an important research paper on the subject that he presented to French President Emanuel Macron.  Holy influencer, Batman!  Although there are numerous AI experts, this article covers only the perspective of Aghion. 

Aghion limited his research to the impact of AI on productivity and employment.  According to Aghion, the full impact productivity and employment of AI will go beyond electricity and the internet!  Holy big assertion, Batman.  Let’s understand Aghion’s logic.

His first reason is perhaps obvious; AI facilitates automation, and automation means increased productivity.  Easy to agree; let’s move to his second reason.  Aghion says, AI facilitates learning, and again, intuitively he makes sense.  Just like electricity and the internet facilitated learning, in too many ways to itemize here, AI users can learn new skills and information, making them more productive and thus increasing overall productivity.  Aghion’s third point is where he inaugurates new thinking. 

Aghion says, AI is vastly superior to either electricity or the internet in its ability to produce new ideas and these forthcoming innovations will deliver greater productivity and employment. And, unlike electricity and the internet which both eventually plateaued in productively gains, Aghion says the boost in productivity coming from new ideas will continue for an undetermined duration because there is no limit to human ideas.  Last, Aghion says electricity and the internet both took about 10 years before impacting productivity meaningfully; AI is on the same trajectory.  Time to examine what Aghion says concerning employment—it’s not all rosy.

Let’s start with the good news.  Aghion claims that automation creates more net employment. He says automation adopters become more efficient and pass along the benefits to customers in lower prices and better quality.  He further claims, that although competitors may lose jobs, the overall market size grows because new customers enter and employment in the sector grows.  Analogous to what Henry Ford did in the automobile industry. 

As expected, Aghion believes certain industries might be in jeopardy and offered three examples: IT security firms, production process companies, and machine learning firms (e.g., call centers).  With regards to employment impacts, he divided his analysis into significant, moderate, and little to no effect.  Aghion identified clerks, secretaries, and accountants as the three most likely adversely impacted occupations.  Aghion says architects, lawyers, and perhaps health care fall in the moderate group.

Aghion concluded with a few recommendations starting with government policy to prevent oligopolies from dominating AI.  He notes large firms are not necessarily innovators, but small firms are.  Second, open-sourced AI is essential to transparency and long-term viability.  Third, protection of personal data must be a priority.  Last, is job training and re-education for displaced workers.  Aghion forecasts 20% of all jobs will be eliminated or nearly eliminated by AI over the next decade. Therefore, generous re-education, training, and unemployment benefits will be required.

Time to quit before AI grabs my money losing blog, (ha ha) and share a French proverb:

“You should turn your tongue around in your mouth seven times before you speak.”

Until next time,

Yogi Nelson

Artificial Intelligence, Blockchains, France, Yogi Nelson

A GLIMPSE AT MISTRAL—THE FRENCH LEADER IN THE AI REVOLUTION

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, was submitted by Luis from Malibu and he wants to know is Mistral leading the French AI revolution?

Luis, you came to the right place. Your question has perfect timing. I just returned from France and am feeling the French vibe! Rather than covering the entire waterfront of AI developments in France, I’ll limit myself to a French company named Mistral.  Let’s start with a bit of background on Mistral, including its name which is French to the core–c’est la vie!

The word mistral has multiple uses in French.  Not only does Mistral mean a cold northwesterly wind, but it’s also not uncommon for companies in industries related to wind energy, sailing, or the environment to use it in their name. The French say it evokes a sense of power, speed, and a connection to the natural world. It can also mean masterly.  While traveling in France, I noticed Mistral as a last name as we say in the USA or as they say in France, the family name.  Holy multi-tasking word, Batman!  Now a word about the Mistral team and company mission.

With fewer than two dozen members, the Mistral team is small.  According to Mistral, their mission is to make frontier AI ubiquitous, and to provide tailor-made AI to all developers.  Mistral says, their mission requires fierce independence, strong commitment to open, portable, and custom solutions, and an extreme focus on shipping the most advanced technology in limited time.  How I discovered Mistral comes next, followed by what Mistral does, and what it offers.

Approximately three months ago I discovered Mistral while researching AI projects for this blog.  I attempted access but was denied.  Instead, Mistral put me on a waiting list of interested users and recently granted me access with a full disclosure that their large language model (LLM) is in beta testing status. 

Today, I put Mistral’s LLM, Le Chat, to the test against, two American companies—Open AI’s ChatGPT and Microsoft’s Co-Pilot– by asking all three identical questions.  All three-offer free access to their LLM services.  I won’t detail the contest; it’s not necessary.  Essentially, Mistral is lacking behind the competition.  Why Mistral trails, is a matter of speculation.  Perhaps its funding related?  Or maybe Mistral team size means it’s too small to compete with the titans? Could be they started later?  I don’t know, but I do know the competition is ahead.  Okay, now we go beyond their LLM to a preview of Mistrals AI products. 

On their website, Mistral has a click option labeled La Plataforme (the Platform).  This is where you’ll find the heart of their offerings and services.  Basically, La Plataforme is a subscription service.  For a fee, Mistral offers access to their AI developer tools. Mistral claims the tools permits users to develop AI agents and other related products.  The subscription grants access to the latest Mistral models and to pay based on what you use.  That’s a good feature.  Moreover, users can set monthly spending limits and if there are multiple users with an enterprise, Mistral will centralize billing.  The subscription grants access to the corresponding documentation and of course users can create API keys to access Mistral AI.

Time to say “au revoir” (goodbye) but not before sharing this French proverb:  Only imbeciles don’t change their opinions.”   Well said, my French friends!

Sincerely,

Yogi Nelson

Artificial Intelligence, Blockchains, China, international aid

IS CHINA USING ITS INTERNATIONAL AID TO PROMOTE ITS ARTIFICIAL INTELLIGENCE TECH AND GAIN MARKET DOMINANCE IN DEVELOPING COUNTRIES?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your technology questions are answered!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, was submitted by Marcia in Palmdale, CA and she wants to know is China using its international aid to advance use of its artificial intelligence technology and gain market dominance in developing countries?

Marcia, you came to the right place.  You ask a tough question, fortunately there is an organization headquartered in Santa Monica, CA that researches the subject and their name is RAND.  RAND stands for Research and Development Corporation. Let’s understand RAND then answer your specific question.  

RAND is a non-profit public policy research organization.  RAND was established in 1948 with the intent of providing non-partisan policy research and analysis.  Almost 100% of RAND’s 1,800 research staff members have either a Ph.D. or master’s degree.   With seven offices spread across the globe in the USA, UK, and Australia, RAND has a worldwide audience.  Last year RAND launched 800+ new research projects funded by more than 350 clients.  RAND conducts policy research across 10 subjects, including national security.  Bottom line–RAND is an impressive research organization consisting of brainy people.  Holy nerds, Batman!  Now let’s turn to the question asked by Marcia.

According to RAND, at $85B per year, China is the world leader in development finance.  USA development finance falls a far second at only $45B per year.  RAND says, Chinese tech companies can use this large government funding support to deploy state-of-the-art artificial intelligence (AI) tools in development contracts in recipient countries. And therefore, the AI exports facilitated by these arrangements are likely to bolster China’s growing global AI technology-related supply chains, trade flows, technology standards, and regulatory systems.  In other words, when China provides development finance (aid) to Pakistan, for example, the contract with Pakistan, will include conditions that require Pakistan to use Chinese AI technology.  Holy foot in the door, Batman! 

Given the situation, RAND’s national security team was contracted (they don’t say by whom, but you can safety assume a branch of the U.S. government) to explore two questions:

1.  How can China’s AI exports be systematically tracked and analyzed using reliable data sources?

2.  What would promote a better understanding of the global landscape of China’s AI exports?

China does not participate in the International Aid Transparency Initiative.  Hence, researchers tracked Chinese development finance by receiving countries. Researchers used OCED (Organization for Economic Cooperation and Development) data in their research. The dataset captured all official financial and in-kind commitments from China from 2000–2021 to developing countries.

First, let’s look at the published findings of the 33-page report.   https://www.rand.org/pubs/research_reports/RRA2696-1.html  followed by a few words regarding unpublished findings, as perhaps those too are interesting. 

Reported Findings:

  • Researchers discovered 155 AI applications and AI infrastructure projects that were exported to 64 countries
  • The researchers used GIS to map their findings.  Although Pakistan was the largest beneficiary, the map clearly shows most Chinese aid was dedicated to African nations.   

Unreported Findings:

The report has six blank pages and no explanation for the blank pages is offered. The blank pages are not labeled, “Intentionally Left Blank”.  The pages are simply blank with no explanation whatsoever.  And no mention of what who paid for the report!  Holy mystery, Batman!

I end with a proverb from Pakistan:  The friend appears in hard times, not at big dinners.

Until next time,

Yogi Nelson

Artificial Intelligence, blockchain association, Blockchains, China

WHAT ARE BLOCKCHAIN ASSOCIATIONS?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your technology questions are answered.   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question was submitted by Kandy, and she wants to know what are blockchain associations?

Kandy, you came to the right place.  Although the definition may vary depending on the country, an association is generally defined as an organization comprised of businesses or individuals in a specific industry or trade collaborating to address common issues, set standards, and advocate for their shared interests and goals.  Members pay dues, and the association’s professional staff work on their behalf.  On to the blockchain association located in Washington, D.C.

Washington D.C. is not only the USA capital, it’s also the headquarters of associations.  Government capitals and associations are congenital twins.  Where one goes, so does the other.  As of 2022, over 3,400 associations were registered in Washington, including an association of associations.  Lol!  That is not a joke! 

The Blockchain Association in Washington has 100+ members.  Membership is restricted.  Individuals cannot join, only organizations.  Their mission is “… to advance the future of crypto in the United States, promoting potential of blockchain technology and shaping policy that ensures its success. We work with our members to educate policymakers about blockchain technology and its ability to pave the way for a more secure, competitive, and consumer-friendly digital marketplace.”  Holy shared interest, Batman! Let’s discuss blockchain associations around the world. 

As noted above blockchain associations basically function in a universal manner—they all advocate, educate, promote, hold events, etc.  Hence, I will only highlight one or two unique facts for a select few blockchain associations.

Canada—Blockchain Association of Canada.  Two fun facts about BAC.  First, BAC sponsors innovation challenges.  Second, BAC is headquartered in Vancouver not Ottawa (Canada’s capital).

Cayman Islands.  The Cayman Islands is an international banking center.  Therefore, we should not be shocked to discover the country is embracing blockchain technology.

China.  Several years ago, China declared blockchain a national priority technology and not surprisingly there are numerous national and international blockchain associations, including the UK-China Blockchain Association, the Hong Kong Blockchain Society, French-Chinese Blockchain Association.

Germany—Blockchain Bundersverband.  The German blockchain association has a working group focused on decentralized autonomous organizations. 

Mexico—Blockchain Association of Mexico.  We Latinos are known for coming late.  Lol. The Mexican Blockchain Association arrived early!  Lol!

Singapore–Blockchain Association Singapore (BAS).  The BAS has six working groups including one dedicated to stable coins and central bank digital currency.  If you know Singapore, you are not surprised.

Swiss Blockchain Federation.  Located in Bern (the capital) the SBF works across a range of topics, including bringing blockchain technology to the public sector.

United Arab Emirates—Government Blockchain Association of UAE. 

United Arab Emirates–Middle East, Africa & Asia Crypto & Blockchain Association (MEAACBA).  This is an international blockchain association.  Members hail from the Middle East, Africa, and Asia and the headquartered is in Dubai, UAE.  

United Kingdom–International Blockchain Association (IBA).  The IBA has offices in London, New York, and Dubai. 

Kandy, the research reveals an emerging picture.  First, blockchain adoption is growing fast.  Second adoption is increasingly international.  Third, beyond the USA, Dubai, China, and Singapore are blockchain hot spots. Fourth, crypto does not equal blockchain.  Blockchain is a technology with countless use cases that extends far beyond just crypto.  Five, policy makers are being educated around the world and that portends a brighter future.

I end with a proverb from Tunisia:  Like salt, he doesn’t miss any meal.

Until next time,

Yogi Nelson

Artificial Intelligence, Blockchains, Patents

How are DARPA, Explainable Artificial Intelligence and Nvidia Connected? 

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your technology questions are answered!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, comes from Susan in Irvine and she ask how are DARPA, Explainable Artificial Intelligence (XAI) and Nvidia all connected?

Susan, you came to the right place.  As a wealth manager I know you have a fiduciary duty to maintain current on investable technology on behalf of your clients.  Around 1990 a new technology was on the horizon–the internet–and it created trillions in new wealth!  Artificial intelligence (AI) is on a similar trajectory.  However, AI is not well understood–yet.  Let’s take a moment to acquaint ourselves with AI from the perspective of DARPA. In hindsight, DARPAs XAI program could have been used to foresee a tremendous investment opportunity—Nvidia the advanced computer chip maker essential to the AI business.

DARPA is an acronym that stands for Defense Advanced Research Projects Agency.  DARPA is part of the Department of Defense (DoD) and its mission is development of emerging technologies for military use.  DARPA created the internet in the late 1960s to facilitate control and command of military communications.  Under DARPA leadership, the US military maintains technological superiority over all other nations. 

In 2015 DARPA released an article titled, Explainable Artificial Intelligence (XAI).  https://www.researchgate.net/publication/356781652_DARPA_’s_explainable_AI_XAI_program_A_retrospective     Remember the XAI project was undertaken in 2015–years before the public had access to ChatGPT and other similar products.   Let’s examine the research findings.

According to DARPA in 2015, “…dramatic success in machine learning will lead to numerous AI applications.  It appears AI will eventually produce autonomous systems that will perceive, learn, decide, and act on their own”, DARPA predicted.  However, DARPA was concerned the effectiveness of AI systems would be stymied unless and until machines can creditably explain their decisions and actions to human users. Holy transparency, Batman! Therefore, the XAI program was intended to create a suite of machine learning techniques that would:

  • Produce more explainable models, while maintaining a high level of learning performance (prediction accuracy); and
  • Enable human users to understand, appropriately trust, and effectively manage the emerging generation of artificially intelligent partners.

XAI program was focused on the development of multiple systems by addressing challenges in two areas: 

  • machine learning problems to classify events based on multimedia data  
  • machine learning problems to construct decision policies for an autonomous system to perform a variety of simulated missions

DARPA selected these two areas because both represented major operational challenges.  The first relates to classification and reinforcement learning and the second is centered on intelligence analysis and autonomous systems.  In other words, DARPA was working on building AI machines that understand the context and environment in which they operate, and over time allow them to characterize real world phenomena precisely and in real time.  Basically, DAPRA was developing AI-Gen 2 before the public had access to AI-Gen 1! Holy Explainable AI, Batman! 

DARPA released XAI seven public findings of the XAI program and kept an unknown number of classified secret findings! LOL. Holy keep it on the down-low, Batman! LOL!

  1. Users prefer systems that include explanations rather than just answers (no surprise)
  2. To improve end results the task must be sufficiently difficult that the XAI explanation helps (makes sense)
  3. User cognitive load to interpret explanations can hinder user performance (in other words there are times when too much explanation is a negative)
  4. XAI is more helpful in edge cases
  5. Explanation effectiveness can change over time
  6. XAI combined with an advisor helps (no kidding, LOL)
  7. XAI is effective for aligning mental models

What’s are the two takeaways?  Obviously, DARPA did not leak military secrets on the internet and only disclosed the minimum. However, DARPA did leave an interesting information trail in 2015 that had we followed it, could have been a monster opportunity.  The XAI 2015 article was a glimpse into the future and we might have forecasted the rise of Nvidia.  Holy unicorn, Batman!  Nvidia stock has since soared, and we could have, should have…

I end with a Russian proverb: trust but verify!

Until next time,

Yogi Nelson

Artificial Intelligence, Blockchains

What is SimTheory?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your technology questions are answered!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question was submitted by Tracey, and she wants to know what is SimTheory?

Tracey, you came to the right place.  Tracey be prepared to go down under and learn about this fantastic project.  We start by introducing the SimTheory team. SimTheory is led by Chris and Michael Sharkey. They are based in Sydney, Australia, and it’s fair to say they are tech bros! LOL.  Now, let’s move on to their project.

As often happens in life we start with one idea and that leads to another.  In the case of SimTheory, it started as a podcast.  That’s how I discovered it.  The Skarkey bros say the idea was to create a cyber space to try AI models for the podcast show.  In other words, SimTheory is more than a podcast; SimTheory is a podcast and a cyber space testing ground.  That’s an awesome concept. Holy two for the price of one, Batman!

The Sharkey bros consider SimTheory as a place to create and share artificial intelligence (AI) agents.  The point is to empower anyone, and everyone, to deploy powerful open-source instruction-based AI agents to accomplish real goals, say the Sharkeys.  Take a moment to consider what the bros say: “we think of SimTheory as a website builder crossed with a social network for AI agents. SimTheory exist for a single purpose–to serve the This Day in AI (their podcast) community with a place to place to try different modals, modalities, fine tunes, instructions, and prompts.”

Let’s talk about the podcast.  The podcast is A+, five-stars, whatever rating scale you pick, it’s at the apex.  The show is weekly and new episodes are released every Monday.  It’s a long-form podcast, about 75 minutes per show.  Honestly the material can be technical especially in the beginning of your AI journey.  However, the tech bros are entertaining and with time, study, and effort anyone can understand the material.  Perhaps offering a few examples from their podcast would help.

On a recent episode they put Bland.ai to the test.  Bland.ai is an AI tech used to make voice calls that can react and respond in “near” time.  In the test they called local hardware and pet stores using Bland.ai and of course the results were a combination of hilarious, impressive, and a peak into the future.  The point was to test whether the human answering the phone call would notice the caller was an AI.  They also intend to prank their mom on an upcoming show.  LOL.

Obviously, the podcast has a serious side.  For instance, SimTheory puts products to the test and gives honest assessments.  They have offered non bias reviews of products from Google, Microsoft, OpenAi, sports betting with AI, and numerous others.  The Sharkeys also gave their assessment of President Biden’s executive order regarding AI.  All-in-all, terrific material from every angle.  Now a word about the AI agents you’ll discover on their website.

The categories are diverse, including but not limited to health, entertainment, art, comedy,  therapy, design, and education.  Under education, there is D.A.N. the mechanic.  In the entertainment category discover Tay, “Your Virtual Girlfriend” (who is a bit toxic LOL).  There is also an AI agent that does an amazing job of transforming images into video!

Time for a SimTheory podcast and leave with a proverb from Australia:  Traveler, there are no paths.  Paths are made by walking. 

Until next time,

Yogi Nelson

Artificial Intelligence, computer vision, Patents

IS SMOKEY BEAR USING ARTIFICIAL INTELLIGENCE TO FIGHT FOREST FIRES?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your technology questions are answered. As a bonus, a proverb is also included!  Today’s question, submitted by Mike, a former Fire Chief, and he asks if Smokey Bear is using artificial intelligence to fight forest fires?

Mike, you came to the right place.  Let’s converse about how AI protects the forest using California as an example, but first we start with a definition.  According to CAL FIRE, California Fire Fighting Agency, wildfires are uncontrolled fires that rapidly spread through vegetation, such as forest, grasslands, etc. https://www.fire.ca.gov/  CAL FIRE notes wildfires can be natural occurrences or resulting from human activity.  Holy burning bush, Batman!

Wildfires in California are an enormous problem.  Between 2019 – 2022, wildfires caused more than $25B in property damage, millions of acres of forest were burned, thousands of homes were destroyed and hundreds of deaths!  Moreover, wildfires are increasing in numbers and intensity.  Bottom line—it’s an enormous problem. 

Firefighting is a mammoth human coordination challenge.  AI is, in part, a human coordination technology.  California created the Alert California Initiative to coordinate the wildfire challenge.  The initiative has numerous partners.  The purpose is to use AI technology to make data driven decisions regarding wildfires. 

Alert California had a predecessor–Cameras on Mountain Tops (CMT) program.  Program administrators wanted to fix the shortcoming of CMT.  What was the shortcoming?  Essentially, too much data!  CMT system covered 90% of high fire risk areas, as defined by CAL FIRE. The deluge of data generated from the 1,000+ cameras spread throughout the state generated 8 – 16M images per day!  CAL FIRE could not manage the data in time to take effective action.  A human coordination problem.  The solution?   Add artificial intelligence service partner, DigitalPath!

DigitalPath started by implementing computer vision to help humans deal with massive data sets.  Just imagine, cameras were picking up 100,000 smoke images per day.  California operations centers were inundated with 7K – 10K fire alert emails/text/voicemail per day.  The goal was one alert per fire.  Holy efficiency, Batman!

Using a combination of AI computer vision and algorithms, Alert California has dramatically augmented its ability to determine whether an image is relevant, timely, duplicative, etc. and to classify the importance. With AI, firefighters work more effectively, by for example, positioning equipment in ideal locations and of course, under safer conditions!  Here is how it works:

When the AI spots a potential fire on the Alert California network of cameras, the AI system alerts firefighters and provides a percentage of certainty and estimates the incident location.  If the incident is confirmed by trained personnel, firefighters respond. AI is also used to estimate what resources are required, location, and quantity.  Moreover, the AI is also deployed to map out evacuations!  Smokey Bear is ecstatic, Batman!

Ironically extinguishing fires early today means more fuel for blazing infernos tomorrow.  Think of it as a dam that burst at maximum capacity!  However, on the horizon there are positive developments.  For example, with computer vision 40% of all wildfires are being detected by the AI system prior to 911 alerts, and the number is increasing.  With AI, controlled fires become more manageable.  AI is also improving firefighters’ ability to identify where fires are likely to occur and/or when they are occurring.  Simulations are working faster thus increasing the reliability of predictive models to give warnings.  In other words, there is reason for optimism.

I conclude with an Estonian proverb: The stomach never gets full by only licking.

Until next time,

Yogi Nelson

Artificial Intelligence, Blockchains, cryptography, Patents

WHAT IS THE NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your technology questions are answered!   As a bonus, a proverb is also included.  Today’s question, was submitted by Jose in Miami and he asks what is the National Institute of Standards and Technology (NIST)?

Jose, you came to the right place.  NIST is not a well-known federal agency, nevertheless it has an important function.  Let’s quickly review its history, mission, organization, followed by an overview of its six laboratories. 

NIST BACKGROUND

I was surprised to learn NIST was established in 1901.  Holy foresight, Batman!  NIST is an independent agency, meaning it has its own Administrator, but falls within the U.S. Department of Commerce.  NIST says its mission is to “… promote U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve our quality of life.”  

We should not be surprised to learn NIST is among the nation’s oldest physical science laboratories. Furthermore, it’s no surprise that Congress established NIST in 1901.  Why? At the time the USA was a rising industrial star with an eye on catching and surpassing the UK and Germany. For our factories and industries to effectively compete, the USA required standardized measurements and technology.  Understanding the moment, USA leaders used public policy to push industrialization, akin to what China does today and we continue to do with the CHIPS Act as the most recent example.  Nothing new, Batman!

Of course, the agency has evolved and today NIST functions with a core competency of measurement science, rigorous traceability, and development and use of standards. NIST received an enormous vote of confidence from President Biden when he issued Executive Order (EO) 14110:

https://www.federalregister.gov/documents/2023/11/01/2023-24283/safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence

The EO assigned NIST a prominent role in artificial intelligence policies and programs, specifically related to research, development, and implementation. 

NIST Six Laboratories:

Communications Technology Laboratory (CTL).  According to NIST, the Communications Technology Lab was established in 2014 to unite their many wireless communications efforts. CTL focuses on developing precision instrumentation and creating test protocols, models, and simulation tools to enable a range of emerging wireless technologies. Is that your Bat-Phone ringing?!

Engineering Laboratory.  The Engineering Laboratory has a broad mandate of promoting U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology.  Using its discretion, EL built the following portfolio:  1) advanced manufacturing; 2) disaster resistant buildings, infrastructure, and communities; and 3) sustainable and energy efficient manufacturing, materials, and infrastructure.  Holy resistant to hurricanes, Batman!

Information Technology Laboratory.  ITL claims its mission is to cultivate trust in information technology and metrology.  ITL uses, its non-regulatory influence, and world-class measurement and testing facilities, computer science, mathematics, statistics, and systems engineering to achieve the mission.

Material Measurement Laboratory (MML) conducts measurement science research.  MML is focused on research related to industries in the chemical, biological and material sciences fields. MML researchers perform fundamental and applied research, evaluate data, and create other programs and tools to assure the quality of measurement results.

Physical Measurement Laboratory (PML).  PML is dedicated to measuring.  PML’s activities range from fundamental measurement research through provision of measurement services, standards, and data across the following areas:

  • length, mass, force and shock, acceleration
  • time and frequency
  • electricity, temperature, humidity
  • pressure and vacuum
  • liquid and gas flow
  • electromagnetic, optical, microwave, acoustic, ultrasonic, and ionizing radiation

I wrap it up with a proverb from Finland:  There are always people to grab the branches when there are people to carry the spruce.

Until next time,

Yogi Nelson

Artificial Intelligence, Blockchains, Sports AI

IS THERE A ROLE FOR ARTIFICIAL INTELLIGENCE (AI) IN SPORTS?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your technology questions are answered, mostly correct!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, was submitted by Riezl in Las Vegas and she wants to know is there a role for AI in sports?

Riezl, you came to the right place.  You pose a fascinating question worthy of a thorough answer. The answer is yes!  I will discuss how AI may impact sports betting, sport analytics, and sports medicine.  Let’s start with sports betting, but first a disclosure. I do not endorse gambling, nor any company mentioned in this article.   

SPORTS BETTING

MySports.AI is an application that uses advanced machine learning algorithms, to predict outcomes. A unique feature of Mysports.AI, is its ability to customize different betting strategies for each player, catering to various funds and betting cycles. The platform provides back-tested records, allowing players to analyze the profitability of various events under each betting strategy. Mysports.AI backers say the model has undergone tens of thousands of machine learning training sessions.

SPORTS ANALYTICS

Sport analytics was popularized by the movie, Money Ball.  Sports analytics involves collecting and analyzing relevant statistics to facilitate decision making.  Acceptance of analytics in sports is commonplace and soon AI will join the club.  New York University offers a sports analytics certificate https://www.sps.nyu.edu/professional-pathways/certificates/sports-management/sports and a required course is artificial intelligence and machine learning!

Sports are competitions set within a multi-billion-dollar business milieu.  Not surprisingly there are on-field and off-field analytics. On-field refers to improving the performance of teams and players.  For example, in the NBA the analytics indicate superior three-point shooting is essential.  No team can expect to hoist a championship trophy if they are dearth of three-point shooters. Holy Stephon Curry, Batman!  AI algorithms are being used in Formula 1 to improve racing tactics and to automated tire replacement strategies. Piccinotti (2021).  Even tennis racquets are going high-tech with the advent of rackets based on Real HawkEye computer vision system data! There are several on-field analytics AI firms including  GeminiSports.com.

Last, certain sports require considerable human judgment to determine the winner, i.e., gymnastics and ice skating. Recently, Fujitsu created an AI to analyze the performance of a gymnast’s movements using 3D laser sensors (Atiković et al., 2020).

Off-field analytics is concerned with the business of sports. Teams have multiple revenue sources, including ticket sales, merchandise, parking, television broadcast, etc. and expense centers. AI powered sports business analytics can discover ways to maximize revenues, reduce costs, improve fan acquisition, marketing strategies, and perhaps the financial impact of a new sponsorship.  As shown by Chmait et al. (2020a), the relationship between the success of athletes and their salaries is an important value proposition to explore. GWI.Com and others are focused on AI in sports business.

Sports Medicine Analytics and AI

If we enter the time machine and travel to 1995, we discover researchers such as Bartlett discussing potential applications of artificial intelligence in sports performance! In 2006, Bartlett published Artificial Intelligence in Sports Biomechanics: New Dawn or False Hope, wherein he correctly predicted multi-layer artificial neural networks (aka Deep Learning) will take center stage in sports technique analysis.  Other researchers such as Brockett, are using AI to detect patterns that lead to injuries. Fister et al. (2015) has researched whether nature-inspired AI algorithms can investigate safe and effective training programs since 2015.

I end with a proverb from Rwanda:  All proverbs have a good reason for existing.

Until next time,

Yogi Nelson

Artificial Intelligence, Blockchains

AND NOW A WORD ABOUT AIRDROPS?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your technology questions are answered, mostly correct!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, submitted by Danny in Los Angeles, and he wants to know about airdrops.

Danny, you came to the right place.  If you take the term literally, you might think someone is dropping air on your head which would be absurd!  Let’s start with a definition.

Airdrops is a term native to and used exclusively in crypto.  You won’t find reference to airdrops in any other market or industry.  Best of all, airdrops are free!  No charge.  Nada.  Zero.  However, nothing is truly free, meaning we must dig a little deeper.

Let’s start with the obvious; airdrops are a marketing strategy.  The point is to raise awareness and adoption of the project doing the airdrop.  Holy obvious, Batman! Generally, start-up blockchain companies are most likely to engage in airdrops.  The first airdrop occurred in 2014 by AuroraCoin, in Iceland.  El Salvador gave every citizen $30 of Bitcoin to those who installed the government built crypto wallet.  A government-built wallet from a corrupt government to encourage a decentralized money system.  Holy, are you serious, Batman!

Airdrops vary.  I’ll explain a few staring with Standard.

Standard Airdrop.  Standard Airdrop is the simplest.  Participants need only provide their wallet address and basic information. The airdrop quantity may vary depending on several factors, including number of participants, and the amount available, to name just two.

Bounty Airdrop.  To earn bounty airdrops, users must perform certain tasks.  Tasks vary, but generally revolve around raising project awareness, e.g., posting on social media, tagging a company, retweeting a post.  Some projects award airdrops for recruiting other users, think multi-layer marketing, Batman!

Holder Airdrop.  Holder airdrops are often automatic and based on a formula of quantities of tokens a holder possesses, and duration held. It is a way to reward commitment and loyalty.  Only the financially faithful, Batman!

Exclusive Airdrop.  As the name suggest, exclusive airdrops are reserved for selected individuals.  Who are the exclusive?  Generally, they are people who spend the most time on the project, contribute to the project, post about the project, and/or stake their holdings with the project.  Staking is generally the most effective way to get airdrops.  Holy, hoity-toti, Batman! 

Raffle Airdrops.  Raffle airdrops occur when a project decides to give away X number of tokens, based on a lottery.  However, the lottery may not be completely random.  The lottery may be weighted to give advantage to holders.     

If nothing is free nor perfect, what are the downside of airdrops.  In a word–SCAMS!  I’ll give you two scam types, starting with dusting.

In a dusting scam, the thief will send micro amounts of a valuable coin, e.g., Bitcoin, to a recipient.  The idea is to entice the victim to attach their wallet to a crooked phishing website, via a legit service such as Metamask, to claim their airdrop.  After a user connects their wallet and enters their password the scammer drains the stash!  Holy, where is my money Batman!  The second is enticing market participants to invest in a fraudulent, or non-existent project.  Either way your money is vaporized!  Two more quick points.  Tokens from airdrop projects might be worthless because the project fails, and/or token illiquidity.  Hence, keep the champagne on ice but the cork in the bottle!  Lol!

I end with a proverb from Niger:  Ashes fly back into the faces of those who throws them.

Until next time,

Yogi Nelson

Blockchains

ARE BLOCKCHAINS AND CHARITIES A PERFECT MATCH?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your technology questions are answered, mostly correct!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, comes from Lisa in Naperville, and she wants to know if blockchain technology and charity are a perfect match?

Lisa, you came to the right place.  Prior to your question, I hadn’t considered a possible marriage between blockchain technology and charity work.  That’s my fault.  The answer is … read this article and decide for yourself!

In traditional charity, benefactors expect their donations will be accepted and deployed congruent with their intent by the charity administrator.  In other words, based on trusting intermediaries.  What if there was a technology that would remove the need for trusted intermediaries? Suppose that technology allowed a peer-to-peer exchange of value, without permission, and need for trust because all transactions are subject to verification on a digital distributed ledger for anyone to confirm, at any time, from anywhere?  That would be incredible! Breaking news, the technology exist–its blockchain combined with crypto currency!  Holy obvious, Batman! Hold on, the tsunami of reasons for pairing blockchain with charity are only beginning to flood in. 

Blockchain technology removes unnecessary intermediaries, making the donation process faster.  For example, donations can be sent and received directly on-chain, making transactions quick.  What perhaps previously took 8 steps, and several middlemen, can be reduced to maybe 4 using blockchain technology.  However, this pairing goes beyond the removal of intermediaries.

With blockchain technology benefactors can verify transactions independently.   In other words, matching blockchain and charity flows beyond eliminating middlemen.  The point is there is no need to trust because the proof is in the blockchain.  Sweet! 

A third reason is efficiency.  Charities that utilize smart contracts, via blockchains, have a tremendous advantage over their competitors.  With smart contracts, charities can automate transactions when predetermined criteria are satisfied.  Thus far we have faster, more efficient, and trustless reasons.  Let’s talk about international charities. 

Speaking from personal experience, sending money overseas is expen$$$ive and s-l-o-w—but not with blockchain technology.  With a couple of mouse clicks money is sent instantly and for just pennies.  Moreover, with blockchain and smart contracts the potential pool of donors is worldwide, making it reason number five!  You are on a roll now Batman, please mention NFTs.

Charities need to raise awareness to succeed and issuing NFTs could be a means to draw attention.  NFT stands for non-fungible token, therefore each NFT is unique.  A charity could raise funds by selling a series of NFTs or an NFT collection set in a raffle, for example.  Holy storytelling, Batman! 

Using blockchain technology for charitable purposes is not worry free.  For example, crypto currencies fluctuate in value; hence, a benefactor may exceed their intended donation, or under deliver.  Either way, it complicates budgeting for the charity.  Sending stable coins is a possible solution because they are pegged to specific assets, i.e., U.S. Dollar, Euro, Yen, etc. but that too could be a hurdle. 

What hurdle?  The challenge of the digital divide.  Not every charity organization has the technical skills to handle crypto currencies.  Cyber security may be a challenge.  For instance, transactions can be hacked or compromised.  Send out the Bat signal! 

Government regulations are always a consideration.  Some nations permit charities to accept crypto donations; others might incarcerate in the BIG house for doing so! 

I end with this Panamanian proverb: If you want no disappointments, don’t indulge in illusion

Until next time,

Yogi Nelson

Blockchains, China, cryptography, Patents, Yogi Nelson

WHY ALL THE FUSS ABOUT 3924 3924, 3924, 3924, 3924, 3924, 3924

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your technology questions are answered, mostly correct!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, submitted by Albert from Iowa and his question is, why the number 3924?

Albert, you came to the right place.  Let’s talk about this number, 3,924.  According to the Blockchain Global Patent Authorization, as of December 2020, there were 3,924 patents granted for blockchain technology worldwide.  For a new technology, 3,924 is a staggering number and as I said previously the number reflects 2020 statistics.  Holy worldwide adoption, Batman!

This naturally leads to the next question.  What countries lead in blockchain patents?  According to Lexology, U.S. companies accounted for 39% of all patents granted, South Korea comes in second with 21%, and China was a close third at 19%.  In other words, the US, South Korea, and China accounted for 79% of all blockchain patents globally up to year 2020.  But that is backward looking data.  If we want to understand the next wave, we must examine pending patent applications as that tells a forward-looking story. Okay, let’s do it.

In Digital Finance by Baxter Hines, he cites The Block as the source for pending patents.  According to that source, Chinese companies should dominate the next wave of blockchain patents.  In fact, the top five companies with blockchain patents pending are all Chinese.  Tencent, Alibaba, and Ant Financial alone have 1,263 patents pending whereas the top three American companies (Walmart, IBM, and Microsoft) have only 123.  Is there more to the story?  I think so.  Read on. 

Let’s go back to 2019.  In 2019, Chinese President Xi Jinping identified the advancement of blockchain technology as a national priority and declared China will “lead the next wave of digital transformation” and called for greater study, investment, and regulation.  What happened next?

Well, in typical top-down authoritarian fashion, more than 35,000 firms responded to Xi’s appeal by registering their companies as “blockchain related” and expanding the use of blockchain technology into their businesses’ operations.  Holy jumping right on the task, Batman! But hold on there is more to the story.

Of the 35,000 that responded only 730 qualified for the Chinese government’s blockchain certification (2%).  Nevertheless, more than 10,000 blockchain patent applications were filed!  But quantity and quality are not always synonymous, and the Chinese government approved only a small fraction of the applications.  Perhaps, Xi needed to be more explicit in his order.  I suggest he try this next time: “Listen up comrades.  We need lots of high-quality world class blockchain patents.”  Lol!

Research and development into blockchain technology is big business.  There is a battle for blockchain technology supremacy between the US and China, with South Korea in the hunt also.  The winner of this battle will have an advantage across many developing technologies, including artificial intelligence (AI).  Many technology analysts are forecasting a fuse of blockchain, AI, and the internet of things (IOT) converging into a tsunami of tech advancements in the next decade.  Hold on to your safety belts, Batman!

I close today with a proverb from Denmark, where people say:  Never advise anyone to go to war or to marry.  Wise words indeed!

Until next time.

Yogi Nelson

Artificial Intelligence, Blockchains, cryptography, Yogi Nelson

WHAT IS CRYPTOGRAPHY?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your technology questions are answered, mostly correct!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, was submitted by William from La Puente, CA and he wants to know what is cryptography?

William, you came to the right place.  William the only reasonable place to start is with a definition.  Let me answer by referring to an awesome movie called My Big Fat Greek Wedding.  In the movie the father of the bride would constantly say, “… the Greeks invented that, the Greeks did that first, etc.”  Well perhaps the old man had a point because in the case of cryptography the word comes from the Greeks.  Kryptos means hidden and graphein is to write; hence, cryptograph is to write in a hidden manner.  Holy hidden message, Batman!

Okay the word has its origin in Greece, but what does cryptography do?  Essentially, cryptography provides information protection/security.  Using cryptography, data can be transformed by substitution.  For example, an early and primitive form of substitution cryptography was to shift every letter three spots.   A sentence that would normally read like this: “Encrypted using Caesar cipher” becomes Hqfubswhg xvlqj Fdhvdu fiskhu.  The other method, known as transposition, involves moving the order of characters of words by a pre-determined agreement.  No, it’s not pig Latin!  Lol.

Cryptography concepts are likely foreign; hence, we should start slowly. I’ll cover just three topics today and save the rest for later.  Let’s start with the security services of cryptography, there are four. 

First is authentication.  By authentication I mean the assurance the communicating entity is legitimate.  Second, data confidentiality.  In other words, the protection from unauthorized disclosure.  The third is data integrity.  In this context I mean the data has not been altered; it was received exactly as sent.  Last, comes non-reputation.  Non-reputation refers to the notion that the receiver can prove the alleged sender sent the message.  Impressive!

We are off to a fast start.  Let’s try two more topics beginning with cryptographic keys. 

In cryptography there are two types of key systems–symmetric and asymmetric.  Symmetric is where one key is used to encrypt and decrypt messages.  The keys are essentially shared by the two parties and the data is transferred via a secure network.  However, authentication nor non-reputation is provided, and the origin of the message cannot be determined.  Let’s compare that to asymmetric cryptography. 

In asymmetric there are public and private keys.  The public key is derived from the private.  As you can guess, asymmetric was developed due to the problems with symmetric cryptography.  Asymmetric wins the crypto security battle handily.  However, if you lose your private key there is no way to access the data, value, or information that was sent!  You best hold on tight!

Hashing is an ideal spot to end the lesson.  Hashing, (I don’t mean potatoes, although I love hash browns) in cryptography is the process of transforming data or a string of characters into a short and fixed length value.  The value produced is unique; no other record has it.  Hashing algorithms are used to perform the hashing process in three steps:  1) data input; 2) hashing function #; and 3) hash output (of a fixed length). By the way, blockchains make extensive use of hashing.  More on that later.

There is more to say but for now I’ll stop with a proverb from our friends in Tajikistan, where they say:  In every drop of water, there is a grain of gold.

Until next time,

Yogi Nelson

Blockchains

WHAT IS THE FUTURE OF DIGITAL FINANCE ADOPTION ACCORDING TO MOODY’S?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your technology questions are answered, mostly correct!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, comes from Oswaldo, in New York, and he wants to know what does Moody’s Investor Service (Moody’s) forecast for digital finance adoption in 2024 and beyond?

Oswaldo, you came to the right place.  On December 14, the Decentralized Finance office of Moody’s released a report, titled: 2024 Outlook: Digital Finance Slowly, Steadily Moves Towards Interoperability and Standardization.  The research was led by Christiano Ventricelli; here is the link:  https://www.moodys.com/research/Decentralized-Finance-and-Digital-Assets-Global-2024-Outlook-Digital-finance-Outlook–PBC_1386273?cid=web-ntrnlbnnr-16640  Before jumping into their forecast, first let’s understand who is Moody’s?

Moody’s has been around since 1908 and it offers credit ratings, macro-economic forecasting, and several other services, including Investor Service.   Moody’s produces research papers across numerous financial topics, including digital finance.  With that short introduction, let’s examine Moody’s four findings.

Mass Adoption Will Need More Interoperability and Standardization.  According to Moody’s, blockchain technology has numerous potential benefits, including greater efficiency and potential cost savings.  Blockchain enthusiasts agree.  I concur with Moody’s that until and unless blockchains reach interoperability the benefits of blockchain may not materialize.  What Moody’s did not say, but I will, is blockchains need a “Wi-Fi moment”.  Imagine if Wi-Fi was not seamless and users had to switch constantly to maintain a connection?  What a mess!  This is the state of public blockchains today. There are bridges under construction to connect blockchains, but most are too tiny, weak, and not suitable at enterprise scale.

Asset tokenization will keep growing, but reliable digital cash options remain elusive. Yes, asset tokenization will result in convergence between traditional and digital finance.  Agreed. And, yes, it’s true there are tech and regulatory risk considerations.  However, I part ways with Moody’s regarding digital cash adoption options.  Moody’s believes Central Bank Digital Currencies are better positioned to be a secure form of digital cash over stable coins.  In the USA probably true. However, across the globe government creditability on matters of monetary policy is at rock-bottom; hence, let’s withhold judgment.

Cryptocurrency market’s revival hinges on monetary policy and service operators’ regulatory compliance. There are dozens, perhaps hundreds, of industries whose viability hinge on monetary policy.  Cheap money is positive for crypto, and all assets. What drives crypto goes beyond interest rates and monetary policy.  Crypto is also an ideological movement.  Crypto enthusiasts want a new monetary policy–an alternative that Jerome can’t control.  Hence, suggesting the crypto market hinges on traditional finance is missing the point. 

As former federal bank regulatory compliance officer, I am unaware of any industry that can operate at scale outside regulatory compliance other than organized crime!  Holy criminal enterprise, Batman! Hence, the findings are not surprising.  And yes, crypto needs clarity.  Is it a security?  Is it a commodity?  Etc.

Digital asset regulatory frameworks advance, though regional differences will persist. Bingo, Moody’s is on target.  Europe, Singapore, and the United Arab Emirates are all establishing regulatory clarity.  Therefore, regional differences will arise in crypto as they do in traditional securities regulations.  The U.S. Securities and Exchange Commission (SEC) is expected to approve a spot Bitcoin ETF soon.  An Ethereum spot EFT is on the horizon. The SEC recently sued Coinbase, the largest crypto exchange in the USA, for selling unregistered securities.  Between the Coinbase case, and the 2024 Presidential Election, clarity maybe on the horizon.

I close with a proverb from Moldova: Wine is a traitor.  It starts as a friend and ends as an enemy.

Until next time,

Yogi Nelson

Artificial Intelligence, Yogi Nelson

IS BULGARIA A LEADER IN ARTIFICIAL INTELLIGENCE EDUCATION?

Yogi Nelson

Namaste Yogis. Welcome to the Blockchain & AI Forum, where your technology questions are answered, mostly correct! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question, comes from Fernie, in Las Vegas, and he wants to know if Bulgaria is a leader in artificial intelligence education and research?

Fernie, you came to the right place. Rather than answer directly, I will share information about a certain institute located in Sofia, Bulgaria, and let you decide. Let’s jump right into it by shouting out the Institute for Computer Science and Artificial Intelligence Technology, INSAIT.
https://insait.ai/

INSAIT is a mere toddler; it was founded in April 2022. INSAIT is the first university in Eastern Europe dedicated exclusively to computer science and AI technology education. INSAIT is part of Sofia University, but functions autonomously. Holy independence, Batman!

INSAIT is backed by technology elites, including two of Switzerland’s most prestigious universities and global technology behemoths, i.e., Google, DeepMind, and VMware, etc. INSAIT says its sole focus is on scientific excellence, conducting world-class research, attracting outstanding international scientist, and training the next generation of technology leaders. Let’s peruse their course offerings, beginning with machine learning.

Machine Learning. INSAIT defines machine learning as the area of computer science that focuses on extracting knowledge from large data sets and using this knowledge for making predictions and decision making. INSAIT believes the combination of colossal data sets and increasing access to powerful computation means there are exciting opportunities for data-driven algorithms.

Computer Vision. According to INSAIT, computer vision is an interdisciplinary field that studies algorithms through which computers can comprehend images at a high level. INSAIT says, and with good reason, there are numerous applications for computer vision, including autonomous driving, robotics, object recognition, gesture analysis, tracking, scene understanding, medical images, and embodied AI. Will AI be peeking through my window? LOL.

Quantum Computing (QC). Quantum computing is hyper computing. QC can leverage the properties of quantum states. Look out!!! QC is revolutionary and will make what is now impossible or impractical, possible in seconds. Holy no speed limits, Batman! INSAIT is focused on the software side of QC, including programming languages, optimization, verification, and algorithms.

Cyber Security. INSAIT intends to become a cyber security tour-de-force. INSAIT says it will focus on cryptography and developing new security protocols, including communication systems. Holy bat shield, Batman!

Automated Reasoning. Reasoning is what makes human intelligence and allows us to draw conclusions based on logic, says INSAIT. Not surprisingly, INSAIT has a focus on automated reasoning related to fundamental math and logic questions. Their automated reasoning program examines decision making under uncertain conditions. Fabulous! All of life works under uncertain conditions! LOL!

Natural Language Processing. Speech perception is central to human language. According INSAIT, natural language process is the study of computational techniques for automated processing and analysis of speech and text. INSAIT aims to develop principled algorithms for processing massive amounts of text and speech data and insights based on linguistics. INSAIT keep in mind, the spoken word is only half of all communication!

INSAIT also supports graduate studies in data management, algorithms, and computer programming languages. A complete buffet of AI graduate education for the amazing price of $36,000 per year, including room and board. If I were 22 again I would … but I’m closer to 122 LOL.

Time to end with a proverb from Bulgaria, where they say, “A slip of the foot is not nearly as dangerous as a slip of the tongue.

Until next time,

Yogi Nelson

Artificial Intelligence, Yogi Nelson

IS IT POSSIBLE TO EARN $10M PROVING WEAK AI CAN SUPERVISE STRONG AI?

Yogi Nelson

Namaste Yogis. Welcome to the Blockchain & AI Forum, where your technology questions are answered, mostly correct! Here no question is too mundane. As a bonus, a proverb is included. Today’s question is from Victor, in Altadena, CA. He wants to know if he can earn $10M by developing a Weak artificial intelligence (AI) system capable of supervising a Strong AI.

Victor, you came to the right place. On December 14th, Open AI released a research paper titled, Weak-to-Strong Generalization (system) in which they explored the very question you asked!

https://openai.com/research/weak-to-strong-generalization

Open AI starts with a premise; the premise is Strong AI systems will be vastly more intelligent than humans in 10 years. Holy left behind Batman! Open AI says our current method of controlling AI relies on human supervision. However, future AI systems (Strong AI) will be capable of extremely complex and creative behaviors making it difficult for humans to reliably supervise them. Sounds like a sci-fi horror movie! Based on that premise, OpenAI has the following hypothesis–humans can control weak AI systems and weak AI systems can be designed, built, and used to control much stronger AI systems. Therefore, controlling Strong AI systems in the future should be possible. OpenAI says their hypothesis has been proven correct in a lab setting. Let’s unpack their research and findings.

I’ll quote from the report. “The research suggest there remains important disanalogies between our current empirical setup and the ultimate problem of aligning superhuman models.” In other words, more work is needed.

Open AI says, it may be easier for future models to imitate weak human errors than for current strong models to imitate current weak model errors, which could make generalization (control) harder in the future. Nevertheless, we believe our setup captures some key difficulties of aligning future superhuman models, enabling us to start making empirical progress on this problem today.” Said succinctly, we know managing superhuman models is likely to become a major issue, but we are working on it! Are you reassured?

Let’s examine the three findings:

Finding 1: When ChatGPT2 was used to supervise GPT-4, the resulting model typically performs somewhere between GPT-3 and GPT-3.5 and Open AI was able to recover much of GPT-4’s capabilities employing weaker supervision.

Finding 2: Naive human supervision, such as reinforcement learning from human feedback, could scale poorly to superhuman models without further work.

Finding 3: It’s feasible to substantially improve weak-to-strong generalization.

After discovering that Weak AI in the lab was able to control Strong AI, Open AI says it is committed to undertake two actions.

To start, AI has committed to releasing open source code to make it easy to get started with weak-to-strong generalization experiments today. In other words, the computer codes used in the research will be publicly available to researchers thus putting more brain power to work. Fantastic! https://openai.com/blog/superalignment-fast-grants

Second, OpenAI will launch a $10 million grants program for graduate students, academics, and other researchers to work on superhuman AI alignment broadly. https://openai.com/blog/superalignment-fast-grants. Outstanding!

In summary, the Open AI report said, 1) managing future superhuman AI models is likely to be a problem; 2) preliminary research suggest Weak AI could manage Strong AI models; 3) more research is needed; and 4) $10M in grants is available to any one capable of designing a Weak AI system capable of controlling a Strong AI system.

We end with a proverb from Mali, where they say: When an old woman dies, a library burns to the ground.

Until next time,

Yogi Nelson

Artificial Intelligence, Yogi Nelson

WHAT IS THE STATE OF AFFAIRS IN ARTIFICIAL INTELLIGENCE SYSTEMS?

Yogi Nelson

Namaste Yogis. Welcome to the Blockchain & AI Forum, where your technology questions are answered, mostly correct! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question, comes from Richard, in Los Angeles, and he wants to know what is the state of affairs in artificial intelligence systems?

Richard, you came to the right place. There has been an explosion in recent months of companies announcing large language model (LLMs) AI projects. For this article I’ll refer to LLMs as AI systems. Let’s examine the situation by asking various AI systems to introduce themselves by answering this question:

   Can you please describe yourself and your capabilities in 50 words or less?

Below I cut and paste their respective responses, where available, verbatim.

ChatGPT by Open AI. OpenAI is the California based software company behind ChatGPT.

“I am ChatGPT, a sophisticated AI language model created by OpenAI. With extensive training on diverse topics, I excel in generating human-like text, answering queries, and providing information. My abilities encompass a wide range of subjects, making me a versatile tool for communication and knowledge sharing.”

Bard by Google. Bard is a product of Google, a California company that needs no introduction.

“I’m Bard, a brainy AI from Google. I can chat, write, translate, and more, using knowledge from the real world to fuel your words. Ask me anything! (49 words)”

Notice Bard used 27 words but claims it used 49! Apparently, Bard cannot count! Lol.

Co-Pilot by Microsoft. Microsoft calls its AI system Co-Pilot or Bing which is the name of Microsoft’s search engine.

“Certainly! I am Bing, an AI language model. My capabilities include generating creative content, answering questions, providing summaries, and more. I can write poems, stories, code, and engage in interesting conversations. Feel free to ask, and I’ll do my best to assist!”

Mistral: Mistral is an AI company from Paris. Their website says the project is under construction. I tried to log on, and instead received an email indicating access was by invitation only! Ouch! How rude! Or as they say in France, Impoli! Lol! I don’t want to be a member of a club that would have me as a member! Lol!

Olympus by Amazon. According to Reuters, Amazon is investing millions in training an ambitious large language model, expecting to surpass ChatGPT and Bard. As with Mistral, Amazon is late. Perhaps Jeff needs to unretire and get back to work! Lol!

Gauss by Samsung. Samsung is tardy. When ready, Samsung says its LLM will have the capabilities to generate text, computer code, and images based on machine learning technology. It is not just one model, but a family of models, Samsung Chairman Lee explained to Business Korea on December 18, 2023.

Grok by X. Grok is in beta testing. Why? Maybe Elon is busy on his rocket ship or pumping garbage crypto meme coins. Lol! On November 2, Musk tweeted “Grok is intended to answer almost anything and suggest what questions to ask.” Musk claims Grok will possess a sense of humor, hopefully not his. Lol! What makes Grok superior according to Musk is “… Grok has real-time knowledge of the world via the X platform and will answer ‘spicy questions’ that are rejected by most other AI systems.” Knowledge on X? I guess that’s the humor! Lol!

I will close with a proverb from Togo: A man that does not lie shall never marry. Brother, you got that right for sure! Lol, lol, lol!
.
Until next time,

Yogi Nelson

Artificial Intelligence, Yogi Nelson

WHAT IS THE ARTIFICIAL INTELLIGENCE ALLIANCE?

Yogi Nelson

Namaste Yogis. Welcome to the Blockchain & AI Forum, where your technology questions are answered, mostly correct! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question comes from Butch, in Arkansas, USA. Butch wants to know, what is the Artificial Intelligence Alliance?

Butch, you came to the right place. The Artificial Intelligence Alliance (AI Alliance) is an organization with an impressive membership roster. The AI Alliance consists of technology creators, developers and adopters collaborating to advance safe, responsible AI rooted in open innovation, according to their official statement. Who are the members? Click the link here: https://thealliance.ai/

AI Alliance membership is diverse and as expected concentrated in the tech sector. There are numerous prestigious universities, including U.C. Berkeley, Dartmouth, and the University of Texas. Moreover, the AI Alliance includes foreign universities in Japan and one in Dubai, exclusively for AI. Holy, big brain, Batman! Not surprisingly AI Alliance members are generally from the business community. For example, you will find Meta, Intel, IBM, Oracle, and many other household corporate names.

What does the AI Alliance do? The AI Alliance has three focus areas. Let’s take one at a time.

Responsible and Scalable AI. AI Alliance has set a goal of creating benchmarks, tools, and methodologies to ensure and evaluate high-quality and safe AI. The AI Alliance will also be an advocate for AI safety and security.

Open Foundation Models. The AI Alliance says it will focus on responsibly advancing the ecosystem of open foundation models with diverse modalities, including highly capable multilingual, multi-modal, and science models that can help address society-wide challenges in climate, education, and beyond.

Diverse AI Hardware. AI Alliance claims its members will collaborate on the benchmarking, optimization, and adaptation of AI workloads to advance a diverse set of hardware. AI Alliance reports it will focus on scalability, platform adaptation, and advanced power, energy, and carbon modeling. Benchmarks and metrics developed for model inference, fine-tuning and energy consumption of large-scale AI workloads will also be contributed to the open-source community.

Butch, you ask in what way do the members contribute? I’ll give you three of the eight ways AI Alliance members can contribute. We start with a pledge to deploy benchmarks, tools, and other resources that enable the responsible development and use of AI systems at global scale, including the creation of a catalog of vetted safety, security, and trust tools. Second AI Alliance members agree to responsibly advance the ecosystem of open foundation models with diverse modalities, including highly capable multilingual, multi-modal, and science models that can help address society-wide challenges in climate, human health, and beyond. And third, AI Alliance members say they will support global AI skills building, education, and exploratory research. Nothing short of ambitious!

The actual working of the AI Alliance is fascinating and deserves a short explanation. The AI Alliance will divide the work and its members into groups with specific tasks. To direct the work, the AI Alliance announced it will establish a governing board and technical oversight committee. The board and technical committee will establish overall project standards and guidelines. There is no mention of an Executive Director, dedicated staff, nor explicit political activities, yet. However, I am confident the AI Alliance will eventually establish a Washington, D.C. presence to lobby the executive branch, Congress, and regulators. That’s how it works, folks!

Butch, I hope I answered your question. Remember what they say in Italy: When you finish the game, the king and pawn end up in the same box.

Until next time,

Yogi Nelson

Artificial Intelligence

WHAT IS THE PAUL ALLEN INSTITUTE FOR ARTIFICIAL INTELLIGENCE

Yogi Nelson

Namaste Yogis. Welcome to the Blockchain & AI Forum, where your technology questions are answered, mostly correct! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question comes from in Mark, Naperville, USA. Mark wants to know, what is the Paul Allen Institute for Artificial Intelligence?

Mark, you came to the right place. Let’s take a moment first to understand, who was Paul Allen. Mr. Allen made his fortune as a Microsoft co-founder. Perhaps his name sounds familiar from the Microsoft connection? Allen passed away in 2018 at age 65. Too young! Lol! Before Allen’s passing, he established three research institutions, including the AI research.

Paul Allen AI Institute, commonly known as AI2, was established in 2014. AI2 is in Seattle and Tel Aviv, Israel. The mission of AI2 is “…to contribute to humanity through high impact AI research and engineering.” Let’s dive into what AI2 produces–it generates plenty—beginning with Aristo.

Aristo. Aristo was AI2’s first project. The concept powering Aristo was to create a “Digital Aristotle” capable of answering users’ questions, and ultimately holding a discussion. Aristo was designed to understand elementary science by reading relevant text. In 2019 Aristo scored over 90% on a collection of multiple-choice, eight grade science exams. Better than me, lol! AI2 readily admits Aristo remains incapable of understanding science in a meaning way. Holy ancient Greek, Batman!

Semantic Scholars. Semantic Scholar accelerates scientific breakthroughs by helping scholars locate and understand key research results, make important connections, and overcome information overload. AI2 says Semantic Scholar is an AI-based search engine for scientific literature, including more than 200 million papers covering all scientific disciplines. It draws 10M users monthly. Semantic Scholar can decode PDF files to extract and understand the full-text content beyond titles, authors, and references to include figures and concepts. Semantic Scholar played a leading role in creating the Covid-19 open research dataset.

AllenNLP. AllenNLP executes groundbreaking research in natural language processing, including improving systems’ performance, accountability, and advancing scientific methodologies for evaluating and understanding systems.

PRIOR. PRIOR is the computer vision research team. The goal is advanced computer vision leading to AI systems that can perceive the world, reason about it, and act within it. PRIOR has three research priorities: 1) embodied AI systems capable of interacting with objects, humans, and other agents in the real world; 2) vision and language multi-modal systems that can perform tasks that require an understanding of visual and language data; and 3) computer vision for the common good, e.g., a platform that can detect illegal fishing vessels via satellite imagery.

Green AI. Green AI is dedicated to reducing the cost of training and using AI systems—less expensive AI systems are accessible to more practitioners and contribute less to climate change.

Mosaic. Mosaic was formed in 2018 with the goal of building AI with common sense. Common sense is the ability to acquire and use every day experiential knowledge. Obviously, Ais lack commonsense. Good luck with this one. Lol.

AI Environment. Applied AI for climate modeling and wildlife protection.
• Earth Ranger: Software that aids ecologists and wildlife biologists make more informed wildlife conservation decisions.
• Skylight: Helps reduce illegal, unreported, and unregulated fishing through technology that provides actionable intelligence for maritime enforcement.
• Climate Modeling: The goal is to improve the world’s understanding of climate change, its effects, and what can be done now.
• Wildlands: Machine learning to support wildland fire management.

We conclude with a Norwegian proverb: Behind the clouds, the sky is always blue.

Until next time,

Yogi Nelson

Uncategorized

ChatGPT VERSUS BARD, WHO WINS THE FIGHT?

Yogi Nelson

Namaste Yogis. Welcome to the Blockchain & AI Forum, where your technology questions are answered, mostly correct! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question, comes from Ming (Netherlands) and he wants to know who wins in a fight, ChatGPT or Bard?

Ming, you are in the right place. As implied in your question, and acknowledged by both parties, ChatGPT and Bard are direct competitors. Let’s put these pugilists into the ring and give each an identical test to determine the peoples’ champ. Holy AI boxing match, Batman! We commence by identifying the warriors, starting with ChatGPT.

In the blue corner is ChatGPT, a product of OpenAI. OpenAI is a California based software company developing artificial intelligence. OpenAI describes ChatGPT as a language model designed to understand and generate human like text based on the input it receives. ChatGPT is now in version 4 and uses GPT3.5 as its underlying technology.

In the red corner is Bard, a product of Google, and Google needs no introduction. Bard is a conversational AI tool that uses Gemini as its underlying technology. Bard allows users to interact with and use chat-like dialogues to ask questions, receive information, and complete tasks.

The warriors are in the ring and ready to rumble! Let’s ask five questions across a range of topics:

  1. Can you write a 300-word essay describing the four voyages of Christopher Columbus?
  2. Please give me five Chinese recipes for tofu.
  3. Why did the USA boycott the 1980 Olympics in Moscow?
  4. Can you write a 300-word essay describing the Federal Reserve Banking system?
  5. Explain the physics in aviation that facilitates flight in 300 words.

Round 1: ChatGPT wins by technical disqualification. Although both answered the question fundamentally correct, Bard did not follow instructions. I asked for a 300-word answer. Bard used 370 and ChatGPT 292.

Round 2: ChatGPT wins by technical disqualification because Bard failed to follow instructions. I asked for five recipes; Bard provided four. However, Bard did land punches. For example, it added pictures of every final dish; ChatGPT did not. That’s a big plus. ChatGPT gave me the name of the dishes in Chinese characters; Bard did not. However, given I don’t understand Chinese written characters including them was not value added.

Round 3: Bard wins by adding additional links to the story and including an explanation of what happen after the 1980 boycott. Bard offered links to U.S. State Department documents, a photo, and noted the Soviet Union retaliated in 1984 when it and its allies boycotted the Olympic games held in the USA. Impressive!

Round 4: Bard wins. Great answers were given by both competitors, however, Bard wins the round in a close decision. Bard wins, not due to substance; it wins on style points. Essentially, Bard presented the answer in a format that was superior. Bard made ample use of bullet points and subsections with titles thus making it easier for the reader to follow-along.

After four rounds we are tied. The tension mounts! The winner of round five takes home the championship belt! Hold on to your keyboard!

Round 5: In dramatic fashion ChatGPT takes round five and the title! Although Bard’s format was easier to read, ChatGPT wins using substance. ChatGPT cited two authoritative sources of information and that made the difference.

Ming, I hope you enjoyed the battle of the bots. Today’s proverb comes from Netherlands, where they say, He’s standing there with his mouth full of teeth. (He is speechless).

Until next time,

Yogi Nelson

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WHAT DID VITALIK BUTERIN RECENTLY SAY ABOUT ARTIFICIAL INTELLIGENCE

Yogi Nelson

Namaste Yogis. Welcome to the Blockchain & AI Forum, where questions are answered, mostly correct! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question comes from Art in San Francisco, CA. Art asks what does Vitalik Buterin think of artificial intelligence?

Art, you came to the right place. Before I explain Vitalik’s thoughts, let’s know Buterin first. Vitalik is a 29-year-old Russian Canadian computer programmer and a co-founder of Ethereum. Ethereum is a decentralized blockchain network, known for pioneering smart contracts, among other advancements in computation. From an early age Vitalik demonstrated an amazing ability to grasp mathematics and computer science. That’s not a surprise given his father was a computer scientist. Holy, like father, like son, Batman! Given his genius with computers, it makes sense you would ask what Vitalik makes of AI.

On November 23, Vitalik published his “My Techno Optimism” paper.
https://vitalik.eth.limo/general/2023/11/27/techno_optimism.html?ref=bankless.ghost.io Vitalik’s summary perspective is below followed by highlights from across the major points of his paper.

“I believe in a future that is vastly brighter than the present thanks to radically transformative technology, and I believe in humans and humanity. I reject the mentality that the best we should try to do is to keep the world roughly the same as today but with less greed and more public healthcare. However, I think that not just magnitude but also direction matters. There are certain types of technology that much more reliably make the world better than other types of technology. There are certain types of technology that could, if developed, mitigate the negative impacts of other types of technology. The world over-indexes on some directions of tech development, and under-indexes on others. We need active human intention to choose the directions that we want, as the formula of “maximize profit” will not arrive at them automatically.”

Vitalik Buterin, My Techno-Optisium

Buterin argues there are very high costs to delaying technological progress. He cites life expectancy improvements and the internet, as evidence for not holding back technological advancements. Vitalik makes the case for using advancements in AI to solve environmental challenges, including climate change.

Vitalik believes AI is fundamentally different from previous advancements in technology and therefore requires significantly more consideration. Vitalik says AI is the creation of a new and powerful brain whereas previous inventions were contraptions. “AI is a new type of mind that is rapidly gaining in intelligence, and it stands a serious chance of overtaking humans’ mental faculties and becoming the new apex species on the planet”, says Buterin. Vitalik cites scientists that are worried AI could wipe out humanity! Holy doomsday, Batman!

Buterin, is equally concerned with “digital authoritarianism”. Vitalik points out Open AI, with a mere 500 employees, services 100,000,000 customers with immensely powerful machines! Power could be centralized by just a handful of people one day, is Vitalik’s worry.

Vitalik pens a lengthy narrative regarding the e/acc movement. According to Vitalik, e/acc is “… fundamentally about an appreciation of the truly massive benefits of technological progress, and a desire to accelerate this trend to bring those benefits sooner.” Jeff Bezos is the most prominent advocate. In a point-by-point fashion, Buterin shares what he believes are the implications of e/acc across a range of topics, including: military technology, decentralized governance, cyber security, multi-planetary living, world government, to name a few topics.

We conclude today with this proverb from the Dominican Republic: With patience and calm, a donkey can climb a palm tree. Well said my Caribbean brethren!

Until next time,

Yogi Nelson

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STRONG ARTIFICIAL INTELLIGENCE, WEAK ARTIFICIAL INTELLIGENCE, WHATS THE DIFFERENCE?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered, mostly correct!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, was sent by Sahir, from the Caribbean, and he wants to know what’s the difference between weak and strong artificial intelligence?

Sahir, you came to the right place.  At your age that’s a brilliant question!  Let’s start by explaining weak artificial intelligence (Weak AI).   Weak AI is also known as narrow AI.  Weak AI refers to AI systems that are designed and trained for a specific task or narrow sets of tasks. Weak AI systems excel in performing predefined tasks but are not remotely capable of true understanding or consciousness.  Weak AI is highly specialized and does not possess “human-like” cognitive abilities or general problem-solving capabilities beyond its narrow vision.  Think of Weak AI as a horse with blinders capable of only seeing what is directly nearby and in front and nothing else.  I’ll offer you examples. Weak AI includes virtual assistants, e.g., Siri or Alexa, recommendation algorithms used by streaming services such as Spotify or YouTube, and chatbots designed for specific customer service tasks, e.g., your financial institution customer help line.  Chatbots are mostly annoying and useless, do you agree? Time for Strong AI.

Strong AI, sometimes called Artificial General Intelligence (AGI), refers to AI systems with “human-level” intelligence and understanding.  Which human, I don’t know and afraid to ask!  Lol.  Strong AI systems can perform several intellectual tasks.  Strong AI systems can adapt to different domains and possess a “primitive” form of “consciousness or self-awareness” based on computations. Strong AI is a long-term goal of AI research and would require the development of AI systems that can reason, learn, understand, and adapt across a wide range of tasks and contexts.  Strong AI is currently a theoretical concept, and no AI system comes close to general intelligence.  Meaning you can relax–for now!  Lol. The best example of Strong AI, or perhaps somewhat Strong AI, is ChatGPT4 by Open AI. 

Let’s discuss a central feature of both Weak and Strong AI–prompts.  What is a prompt?  The term prompt is derived from Latin “promptus”, meaning ready for use.  In AI lexicon, a prompt is an instruction to the AI system.  A prompt could be simple, ‘Siri play disco music’, for instance, or complex, such as asking ChatGPT4 to explain Einstein’s Theory of Relativity. Holy prompt, Batman!  Sahir, can you identify which is the Weak AI and the Strong AI in these examples? 

Prompts are critical for two reasons.  First, prompts are how we communicate with AI systems.  AI systems can’t read our minds!  Only through, and thanks to, prompts, can humans interact with Weak and/or Strong AI systems.  In other words, prompts are portals into AI systems.  Second, the quality of AI interactions depends on precise prompts.  Unlike many human interactions, AI systems cannot “know what you mean”.  Therefore, AI systems depend on precise prompts.  My own experience with ChatGPT4 cements this understanding of AI systems.  Try it and give me your conclusion.

We stop here but not before acknowledging two sources for today’s post:  Microsoft’s Introduction to AI course and AI: The Future is Now by Nicholas Marty.  Today’s proverb is from Haiti, where they wisely say, “A leaking roof fools the sun but cannot fool the rain. 

Until Next Time,

Yogi Nelson

Uncategorized

WHAT MONETARY SYSTEM DOES THE CARDANO BLOCKCHAIN USE?

Yogi Nelson

Namaste Yogis. Welcome to the Blockchain & AI Forum, where your questions are answered, mostly correct! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question is from Bhante Chandra from Kandy, Sri Lanka, and he wants to know what monetary system does the Cardano Blockchain use?

Bhante, you came to the right place. Let’s start first with explaining Cardano. Cardano is a decentralized, open source blockchain network that burst onto the scene in 2017. Charles Hoskinson, Cardano’s founder, created Cardano as a third generation blockchain. Bitcoin and Ethereum were generations one and two, respectively. Of course, Bitcoin was released by an anonymous developer (Satoshi Nakamura) in 2008, and Ethereum by a team, including Hoskinson, in 2015.

Cardano is recognized for its research-based approach. Cardano technology is based on nearly 200 peer reviewed academic research reports. Critics say Cardano is slow to the market; Cardano proponents acknowledge the critique. However, Cardano advocates say they are oven cooking not microwaving. Fair point! First and second generation blockchains were energy gluttons because they were constructed with proof of work consensus systems; Cardano was built using a proof of stake consensus system making it extremely energy efficient. Love a green blockchain!

Cardano is focused on solving the blockchain trilemma problem of balancing speed, scalability, and security. Essentially, the trilemma problem in blockchain says the more one or two issues are solved the worse off are the remaining. Holy no way out, Batman! Cardano also is recognized for its smart contract capabilities. Smart contracts facilitate the transfer of value from peer to peer without intermediaries. Now about the monetary system.

The Cardano network uses crypto currency to pay for transactions. Cardano currency is known as ADA, named after the famous British female mathematician and computer programmer, Ada Lovelace. Smaller denominations of ADAs are called Lovelace and they go out six decimal places, .000006. Bust out the calculator!

Cardano began with a total supply of 45B ADA. However, not all were release upon inception; that would be irresponsible. Instead, Cardano has phased in ADA distribution. Cardano is de-inflationary by design, meaning the supply of ADA decreases with time.

Let’s talk about the Cardano treasury and your personal Cardano treasury. Cardano’s treasury has three revenue sources: minting; donations; and taxation from block rewards. Great! Now, how does an individual grow their personal Cardano treasury? Here too there are multiple avenues. You could, for example, purchase ADA on an exchange, such as Coinbase. Suppose you purchased ADA, what next? Well, you could earn additional ADA by “staking it”. Staking is blockchain/crypto jargon for earning rewards. Think of it as interest payments for locking up and “lending” your ADA. Or you can operate your own stake pool and earn ADA directly. Operating a skating pool requires technical computer skills; learn and earn!

Once you have a bag of ADA, where to keep the stash is the question. Here again you have options. You can store your ADA on a centralized exchange, e.g., Coinbase. There are pros and cons to centralized exchanges, that go beyond this post. Or you can self-custody your stack; that too comes with advantages and disadvantages. Several self-custody wallets are available, including Typhon Wallet, Flint Wallet, or Yoroi Wallet.

A special thanks to Cardano and Emurgo Academy for supplying the information for today’s post. Time to go, but not before sharing an Egyptian proverb: “You can tell whether a man is clever by his answers. You can tell a man is wise by his questions.

Until next time,

Yogi Nelson

Uncategorized

WHAT IS THE TURING TEST?

Yogi Nelson

Namaste Yogis. Welcome to the Blockchain & AI Forum, where your questions are answered, mostly correct! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question, comes from Tiago, in Sao Paulo, and he wants to know what is the Turing test?

Tiago, you came to the right place. Before describing and explaining the test, let’s understand who was Alan Turing? Turing was a British mathematician and computer scientist. The Big Papi of computer science! In 1936 Mr. Turing published “On Computable Numbers”. His research paper laid down the core concepts of a computer 10 years before the computer was invented! The machine became known as the Turing Machine. Turing went further and published “Computing Machinery and Intelligence”, in 1950. Here is the link: https://academic.oup.com/mind/article/LIX/236/433/986238 Turing’s research was focused on machine intelligence–can machines think. No easy task and begs the questions, how to determine and measure whether a machine is intelligent. Turing’s solution, known today as the Turing Test, was to modify a popular game at the time known as the “imitation game”.

The game works as follows: a computer and a human receive typed questions from a human judge called the interrogator. If the interrogator cannot accurately identify the answers of the computer, the computer wins. According to Turing, if the computer wins, we cannot say it’s unintelligent thus it must have some degree of intelligence. Given Turing defined thinking as the ability to solve problems, a computer could therefore develop intelligence. Turing anticipated his critics and refuted their nine most probable and powerful arguments, which I summarize below.

Turing starts with and destroys theological objections, citing bible passages where the earth revolves around the Sun and resulting Galileo situation. He moves to objection two labeled “head in the sand”. According to Turing, this position stems from humans unwilling to consider losing intellectual supremacy. The third objection is mathematical, and in full disclosure I did not completely understand. However, I did understand Turing said man can be smarter than a machine but cannot be smarter than every machine. Let’s turn to objection 4, consciousness.

Turing readily admits the consciousness is mysterious. Nevertheless, he says “I do not think these mysteries necessarily need to be solved before we can answer the question with which we are concerned in this paper.” In other words, we don’t need to know it all to know some of it. Objection five relates to “various disabilities”. By disabilities Turing means machines are limited to narrow tasks. I’ll quote Turing’s rebuttal, “… the criticism that a machine cannot have much diversity of behavior, is just a way of saying that it does not have much storage capacity.” Fair point in 1950.

Critics say computer are incapable of surprises and thus don’t think. I’ll paraphrase Turing’s answer: “… this assumes that as soon as a fact is presented the mind fully comprehends all the consequences. While that may be a useful assumption, and sometimes correct, it is false. A natural consequence of doing so is one assumes there is no virtue in the working out consequences from data and general principles. In other words, a machine can surprise you if you give it a chance.

Continuity in the nervous system is objection seven. Turing acknowledged differences in the nervous systems between a discrete state machine (computer) and continuous machines (humans). However, for the Turing test the differences do not affect the interrogator in either direction, says Turing; hence, irrelevant.

The informality of behavior is objection eight. Critics point out humans don’t need rules for every conceivable situation whereas computers do. Turing counters by claiming computer could reach similar status given enough time and computing power. He gives a small example of what had been achieved using what was available at the time.

We conclude with objection nine, extra sensory perception, which Turing defined as telepathy, clairvoyance, pre-cognition, and psychokinesis. Turing had a somewhat dismissive rebuttal–put all Turing test participants into telepathy-proof rooms. Lol!

We reached the end with a proverb from Brazil, “Never poke a jaguar with a short stick”.

Until next time,

Yogi Nelson

Uncategorized

WHAT IS THE FUTURE OF BLOCKCHAIN?

Yogi Nelson

Namaste Yogis. Welcome to the Blockchain & AI Forum, where your questions are answered, mostly correct! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question comes from Ashley in Texas, who wants to know, what is the future of blockchain?

Ashley, you came to the right place. Blockchain technology has enormous potential; however, it must conquer immediate challenges. Let’s begin with five challenges facing blockchain technology today: 1) scalability; 2) initial set-up costs; 3) smooth transition; 4) consensus mechanisms; and 5) privacy and security. I’ll focus on a few solutions, commencing with “sharding”

Sharding is a process for handling large data sets. Sharding accelerates processing by dividing the computational workload and storage space issues. It ensures no single mode (computer) is responsible for processing the network’s transactional load. Sharding increases security through transparent processing on a decentralized network. Sharding is not alone; it has a friend known as sidechains; not to be confused with 2Chainz the rapper! Lol.

Sidechains are separate blockchains attached to the mainchain. Often, sidechains are deployed to test new software before joining the mainchain. Sidechains offer more security when moving digital assets from one blockchain to another and reduce the mainchain’s workload; hence, making the blockchain faster and more reliable. What else is under construction? Answer—state channels.

Despite their Orwellian name, state channels are not spooky. State channels basically “lock” the blockchain while participants agree amongst themselves off-chain. Once participants reach consensus the transaction is uploaded onto the mainchain for processing. Let’s keep rolling with “Roll-Ups”.

Rollups are scaling solutions. Roll-ups move computation off-chain while keeping transaction data on-chain. Keeping the data on-chain allows anyone to locally process all computation in the roll-up and detect fraud. There are two types of roll-ups: Optimistic and ZK. Optimistic roll-ups assume the data/transactions are correct. However, to ensure accuracy, transactions are not final for one week. During the data verification week anyone may submit fraud proof. If no honest individual spots an error, transactions are final. If errors are spotted the transactions can be reversed. What about ZK-Rollups? ZK-Rollups stands for zero knowledge. No, it does not mean the protocol is a know nothing, lol! It means every rollup batch contains a cryptographic hash, thus making transaction more secure. In other words, possession of the private key opens the file and nothing else is required. However, with the increase in security also comes computationally intensive processes. Time, money, and energy consumption.

Charles Hoskinson, Cardano founder, is fond of saying blockchains need their “wi-fi” moment. Said differently, blockchains must achieve interoperability. Imagine having to switch providers every moment to access wi-fi. What a mess! Blockchain interoperability equals users having a seamless integration of capabilities, communication with and between intermediaries, and greater decentralization. Get it done!

Let’s wrap it up with Ricardian contracts. A Ricardian contract is a mechanism to record a document as law and link it to other sectors, i.e., accounting. A Ricardian contract is responsible for executing contracts between two parties and recording the details in forms that are readable by humans and machines. Moreover, the dual abilities of Ricardian contracts equal superior user experiences when compared to smart contracts. Holy dual use!

Today’s “proverb” is curtesy of Yogi Berra to old time baseball star who once said, “it’s tough to make predictions, especially about the future”! lol. Nevertheless, I predict blockchain will evolve and eventually become mainstream technology with widespread applications. Thanks to the Emurgo Academy for providing the source material of today’s post. The art work is by Gerardo Cloquell and on display in Dorado, PR.

Until next time,

Yogi Nelson

Uncategorized

WHAT ARE THE 10 TERMS IN ARTIFICIAL INTELLIGENCE YOU SHOULD KNOW?

Yogi Nelson

Namaste Yogis. Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered, mostly correct! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question was submitted by Alberto from Montebello, CA, and he wants to know the 10 terms in artificial intelligence (AI) that he should know.

Alberto, you came to the right place. Great question. Learning the vocabulary is an intelligent way to master the topic. Let’s roll it in alphabetical order.

Algorithm: I’m sure you have heard the term algorithm tossed about like a basketball. Let’s settle what it means; it’s not complicated. Algorithms are the step-by-step set of instructions followed by computers to perform a specific task. That’s it. Nothing more.

Artificial Intelligence (AI): is essentially teaching machines to learn from data and derive a variety of useful insights. AI is commonly defined as a simulation of human intelligence in machines that are programmed to think and learn like humans. Basically, AI enables computers to mimic human intelligence (hopefully a smart human) using logic.

Data Mining is all about discovery. In data mining patterns of knowledge from large data sets are discovered. Data discoveries are designed to assist with decision making, predictions, etc. Put on your computer hardhat and start digging!

Deep Learning (not to be confused with the Deep State, ha ha) is a specialized form of machine learning (as if machine learning is not sufficiently specialized!). Deep learning involves many layers of neural networks; hence, the label “deep”. (See below for neural networks.).

Machine Learning (ML): is a subset of AI that provide systems the ability to automatically learn and improve from the experience without being explicitly programmed. The key is not explicitly programmed.

Natural Language Processing (NLP): is the ability of a computer program to understand spoken and written human language. Holy linguist! However, human language is more than just sounds and we often have misunderstandings. Hence, it might take more time for software program to truly understand human language.

Neural Networks: a neural network is a computer system based on the human brain and nervous system. Which human I don’t know and afraid to ask! Ha, ha.

Reinforced learning is focused on finding a balance. A balance between what? A balance between exploration of new ground and exploitation of what is already known. Think of it as the yin/yang of machine learning.

Supervised Learning is a form of machine learning (see above). In supervised learning the system uses algorithm (see above) to identify patterns in the data and then “learn” from the patterns. Computer swamis call it supervised because the program is being directed by the instructions coded in the software. A good example of supervised learning is your email spam detector. Thank the universe for the spam detector, otherwise I may have fallen for a love letter from a 20-year-old Russian beauty queen! Ha, ha.

Unsupervised Learning is where the AI tells the boss to get loss! Ha, ha. Just kidding. In unsupervised learning the machine uses algorithms (see above) to analyze and cluster unlabeled data. In other words, in unsupervised learning the machine learns to uncover patterns without direct human direction. Transcribing audio is a good example.

A special acknowledgement to the Cardano Foundation Emurgo Academy, and these two books: AI Made Simple and Artificial Intelligence 2023.

Alberto, please remember those terms and the proverb from Suriname, where they say: You cannot fly with wings made of butter.

Until next time.

Yogi Nelson

Photo by Pixabay on Pexels.com
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WHAT IS A DECENTRALIZED AUTONOMOUS ORGANIZATION?

Yogi Nelson

Namaste Yogis. Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered, mostly correct! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question, comes from Michael in Washington, and he wants to know, what the heck is a decentralized autonomous organization (DAO)?

Michael, you came to the right place. When I heard the term DAO, I too had no idea what it meant. Was it tasty Chinese cuisine? Or maybe the latest fashion from Milan? Perhaps a government document? Let me briefly explain DAOs and summarize what proponents and opponents say.

According to Consensys, a major blockchain player, DAOs are community-led organization with no central authority constructed by rules encoded on a computer program. Proponents say DAOs are transparent and controlled by the organization’s members, not by a central figure. A libertarian utopia? Maybe. Proponents point to smart contracts in setting foundational rules and to execute the agreed upon decisions.

The Emurgo Academy, Cardano’s teaching arm, explains that under a DAO community members create proposals concerning operations and vote on each proposal. Proposals that achieve predefined levels of agreement are accepted and enforced by smart contract rules. Moreover, the very code itself can be publicly audited. Further, DAOs are responsible for tracking the ownership of tokens from point-to-point. Intriguing?

DAO backers say their system produces community collaboration. Their theory is DAOs align incentives; therefore, the best interest of every member is congruent with the best interest of the protocol itself. A healthy, robust protocol will garner more usage, and in turn, increase the value of the DAOs tokens. As the protocol succeeds, so do members. That’s the theory. Opponents say?

DAO supporters are correct, DAOs are built on code that can’t be changed, or not easily changed. Is that a strength or liability? When an Ethereum based DAO was hacked due to programming errors, over $50M was stolen due to there being no central authority to stop the theft. Hence, strength or liability?

Second, to make a major correction or change a programming hard fork is required. Essentially a hard fork means a fundamental modification to the protocol. Think of it as a constitutional amendment in the U.S.A. Difficult under ideal circumstances.

DAOs make extensive use of smart contracts. The problem is “smart contracts” are neither smart nor contracts. The term smart contract is a clever marketing phrase, say opponents. Smart contracts are not enforceable in court and only as smart as the computer engineers who programmed the code. Oh my!

Fourth, DAOs rely on oracles to deliver the information needed to execute. For instance, if the smart contract says pay Yogi Nelson $1,000,000 when the Lakers win, the smart contract is incapable of knowing if the Lakers won. The smart contract relies on oracles to supply the information. What if the oracle is wrong or if the oracle is hacked? What would happen to my $1,000,000!

DAO opponents reject the notion that DAOs improve society by decentralizing power. They note a significant number of crypto projects are highly centralized by founders. DAOs backers are fond of saying code is law! Okay, but who wrote the code? Answer. Small groups of humans with all their faults, flaws, prejudices, bias, shortcoming, etc. Hence, perhaps DAOs hide centralization making the problem worse by projecting a false impression, say DAO opponents.

I conclude by sharing the famous French proverb: “All flatterers live at the expense of those who listen to them.”

Until next time.

Yogi Nelson

Photo by Markus Winkler on Pexels.com
Photo by Markus Winkler on Pexels.com
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ARE YOU SERIOUS, ARTIFICIAL INTELLIGENCE CAN HALLUCINATE?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered, mostly correct!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question was submitted by Aaron from Dallas, and he wants to know if it’s true that artificial intelligence can hallucinate?

Aaron, you came to the right place.  The short answer is yes, artificial intelligence can and does “hallucinate” but don’t panic it doesn’t mean your AI has taken or was given LSD!  Ha, ha. Instead, let’s take a moment to define what it means for AI to hallucinate. 

Photo by Tara Winstead on Pexels.com

Within the context of AI, hallucinations are outputs, e.g., words, phrases, images, that are generated by the AI model (program) that are non-sensical or grammatically incorrect. In other words, the model made a mistake.  The error can be simple, i.e., a misspelled word.  Or, consequential.  For example, the hallucination could mean the model completely generated “facts”.  Put another way, it made up the facts.  Or, it may signify the model combined data that are individually correct but when fused together are wrong, non-sensical or grammatically incorrect.  Holy, computer glitch Batman!

Why would the AI model hallucinate, you ask?  I offer four reasons.  First, it could be the AI model is not trained on enough data.  Did you know, ChatGPT4 is running on mostly 2021 and 2022 data?  Second, perhaps the model was trained on noisy or dirty data.  The old garbage in and garbage out explanation!  Here is a third reason.  Maybe the model was given insufficient context.  Suppose you were only told the punch line of a joke without context.  The punch line within the context might be the most hilarious statement in Western civilization but would fall flat lacking context.  Last, an AI model may hallucinate if it is not provided sufficient parameters.  Imagine if you were told to guess a number between 1 – 10 compared to having to guess a number between 1 – 1000.  Would the difference in parameters affect your accuracy?  We both know the answer.

Now you know AI models may “hallucinate” and why.  With this new understanding of AI, remember to use common sense.  Remember AI isn’t perfect, subject to errors, and to bias.  Nevertheless, a great leap forward.  In keeping with today’s proverb from Jordan, I will end immediately with this proverb about people who won’t stop talking, they say, “He swallowed a radio”.

Until next time.

Yogi Nelson

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WHAT IS A DECENTRALIZED APPLICATION (D-APP)?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered, mostly correct!   Here no question is too mundane.  As a bonus, a proverb is also included.  Roger from New Hampshire wants to know what is a decentralized application (D-App)?

Roger, you came to the right place. Let’s start by first defining app.  App is an abbreviation for application.  If you say application, you risk being un-cool and might be place in computer lexicon detention!  Ha, ha.  An app is computer software. Apps can be downloaded on to your computer or phone.    The app communicates with the hardware and software on your computer/phone to provide the specific function, think YouTube.  Apps are distributed by a central authority across numerous computers, by Apple for instance.  Now, D-Apps.

D-Apps are also software but differ from apps in important aspects.  For example, D-Apps are executed on decentralized peer-to-peer networks; as noted above, apps are centralized. 

D-Apps are governed by smart contracts, whereas, apps are governed by the distributing authority, such as Apple.  D-apps make use of smart contracts and the rules contained in smart contracts allow D-Apps to run autonomously, that is not the case with apps.  Wait there’s more! 

D-Apps are open-source software; apps are closed-source.  Linux is an open-source software example.  Open-source software is available to everyone for use, modification, and distribution; closed-source apps require permission.  D-Apps store their data on a public blockchain for all to examine anytime from anywhere.  Excellent. Of course, smart contracts connect D-Apps to the blockchain.  Finally, D-Apps use cryptographic tokens and apps don’t. 

I assume your next question is, what are the benefits of D-Apps? I’ll give you three benefits.  First, D-Apps are fault tolerant.  By fault tolerant, I mean D-Apps as a system are more resilient and can operate, if one or more components fail.  I like it.  Second, because D-Apps are decentralized they are censorship resistant.  There is no Big Brother! D-Apps are open source and on a public blockchain, hence they generate confidence because as President Reagan often said, “trust but verify!”  

Is there a “test” to determine if a D-App is truly decentralized?  The short answer is yes!  To assess decentralization, ask these five questions: 1) are all users treated in a fair and equal manner; 2) is the source code open; 3) is the D-App built on top of a decentralized blockchain; 4) key decisions are made by the community; and 5) developers are not exclusively in control of the code.   

Let me wrap it up by offering three D-App use cases.  First, is the management and transfer of money.  Roger, have you transferred money from USA to another country?  I have.  If you have you understand the expense and complication.  Ugly. The fees and hassle are unreal but with a D-App the transfer costs pennies, is painless, and free of intermediaries.  D-Apps can also streamline business processes leading to greater efficiencies.  Last, via their smart contract, D-Apps can power a decentralized autonomous organization. (DAO) DAO is an organization without hierarchical structure.  DAOs are administered, in part, with the assistance of smart contracts. I’ll cover DAOs and smart contracts in greater detail in future editions.

Roger, it’s time to boogie, but not before mentioning that in Yemen there is a proverb that says, “If you give people nuts, you’ll get shells thrown at you.”  Hopefully, the few nuts of information I shared today won’t be thrown back at me!

Until next time,

Yogi Nelson

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WHAT IS ChatGPT AND HOW HAS IT EVOLVED?

Yogi Nelson

Namaste Yogis. Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered, mostly correct! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question, was submitted by Samsara, from Puerto Rico, and she wants to know: what is ChatGPT and how has it evolved?

Samsara, you came to the right place. ChatGPT means Chat Generative Pre-Trained Transformer. No wonder it goes by ChatGPT instead! Ha Ha. Essentially, ChatGPT is a large language model-based chatbot and more. I’m confident you have encountered bots. Nevertheless, let’s define bot and chatbot.

A bot is an automated software application that performs repetitive tasks over a network and follows very specific instructions. Bots can perform only as programmed. There are various types of bots, including chatbots. A chatbot simulates human conversation using machine learning. A chatbot can respond to simple questions. Alexa from Amazon is a prime example. Now over to ChatGPT.

ChatGPT was created by OpenAI—an artificial intelligence (AI) research and deployment company. OpenAI’s mission statement is, “to ensure that artificial intelligence benefits all of humanity.” Sounds, virtuous. Do you remember when Google’s motto was “don’t be evil”? Ha, ha. Just saying! Now it’s time to examine the evolution of ChatGPT.

Before ChatGPT, natural language models existed. However, those models were trained on large amounts of annotated data for a particular task. Consequently, those models were strictly limited to what they were trained for and incapable of nothing beyond. To overcome those limitations, OpenAI proposed a generative language model built on unlabeled data thus allowing users to refine the model. The intent was to get the model to perform classification, question answering, and sentiment analysis. Essentially, ChatGPT1 was “trained” to attempt appropriate responses to questions based on accessible data. Although ChatGPT1 was a major technological upgrade, it tended to generate repetitive and generic responses. Your mobile phone device has evolved and so has ChatGPT.

In ChatGPT2, the amount of training data increased by 10X. Therefore, GPT2 generated far more coherent human like answers. Moreover, the processing speed jumped. However, the development of unsupervised learning was the great leap forward. With unsupervised learning, the model could “learn” and make predictions based on the vast amounts of data it was fed without the need for explicit instructions from humans. Holy!

ChatGPT3 was trained on an ever-growing mountain of data. Via the internet, GPT 3 accesses books, articles, websites, social media, etc. and consequently, has learned to “understand” and analyze language patterns. Additionally, GPT3 can perform tasks it was never trained to do. However, it tends to offer repetitive answers, is subject to bias, and consumes lots of power. Critics say it’s just a large memory machine that can spit out answers but isn’t any more intelligent than a calculator. Ouch, rather harsh!

ChatGPT4 is a multi-modal model, meaning it can handle text and images. That’s a first. With greater access to data and more training, ChatGPT 4 is much more creative and collaborative. Unlike its older siblings, GPT3 can generate text that are eerily human like. For instance, it can mimic a writer’s writing style. (Hey, don’t copy me!) Ha, ha. ChatGPT scored in the top 10% in the exam given to become an attorney and it’s multi-lingual in 26 languages! However, OpenAI warns ChatGPT4 makes up “facts” and thus be careful!

Samsara, I hope I answered your questions. Always remember the proverb from Laos—No one is so rich as to throw away a friend.

Until next time.

Yogi Nelson

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DID PRESIDENT BIDEN ISSUE AN EXECUTIVE ORDER ON ARTIFICIAL INTELLIGENCE?

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered, mostly correct!   Here no question is too mundane.  As a bonus, a proverb is also included.  Today’s question, submitted by Marcel from Florida, is:  did President Biden issue an executive order on artificial intelligence (AI)?

Marcel, you came to the right place.  Yes, President Biden did issue a lengthy executive order (EO) regarding AI.  I’ll hit the high points only.  The official name is the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence. The EO says “… the policy is to advance and govern the development and use of AI in accordance with the following eight guiding principles and priorities.” 

1.         Artificial intelligence must be safe and secure.  Biden wants to develop labeling and content provenance mechanisms, so that Americans can determine when content is generated using AI.  Sounds analogous to food labels for AI?

 2.        Promote responsible innovation, competition, and collaboration.  Biden proposes to give small AI firms opportunities and limit the power of the big tech firms.  Well… call me skeptical, but campaign contributions often get in the way of good intentions.

3.         A commitment to workers. Biden offers to revise existing job training programs for AI and says AI should not undermine rights, worsen job quality, encourage undue worker surveillance, lessen market competition, introduce new health and safety risks, or cause harmful labor-force disruptions. 

4.         Artificial intelligence policies must advance equity and civil rights. Biden’s EO proposes to issue an AI Bill of Rights, however, offers no clue what it might say or when it would be proposed.  Nevertheless, a fascinating idea. (Will be tough to improve on James Madison’s work!)  I suggest owning your own data rather than it being monetized by mega-tech firms as the first right!

5.         Enforce existing consumer protection laws. Good! Discrimination should be illegal whether by a person or by a computer programmed by a person. 

6.         Protect Americans’ privacy and civil liberties.  As Edward Snowden demonstrated, I don’t believe this, but we can hope.

7.         Increase the Government’s ability to use AI in daily operations.  This reminds me of Vice President Gore’s “reinventing government” initiative.  With Gore at the command, government workers adopted wide-spread use of the web and the feds gave generous grants to encourage cities to do likewise.  Gore once famously said, “I invented the internet” and of course he did not. He simply ordered all government workers to use the internet! Ha ha.

8.         The US should lead the way to global societal, economic, and technological progress.  What else would you expect a US President to say.

The “O” in EO stands for order and to no one’s surprise Biden orders a series of actions across the sprawling federal bureaucracy.  A significant percentage are related to national security, but also includes ordering the Director of the National Institute of Standards and Technology to develop guidelines with the aim of promoting consensus industry standards.  There are also countless orders related to finance, public health, establishing advisory committees, inter-agency working groups, partnerships with universities and private sector, expediting visas for skilled AI workers, regional innovation clusters for small business, and AI in law enforcement. Essentially, Biden ordered most government agencies to bust a move!

Pushing the federal bureaucracy forward is a Herculean task.  But as they say in Hungry, “it’s easy to push a cart being pulled by 12 oxen.”

Marcel, I hope I answered all your questions.  Until next time.

Yogi Nelsonhttps://www.whitehouse.gov/briefing-room/presidential-actions/2023/10/30/executive-order-on-the-safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence/

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WHAT IS A BLOCKCHAIN?

Yogi Nelson

Namaste Friends. Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered, mostly correct! Here no question is too basic nor simple. As a bonus, a proverb is included at the conclusion of every article. Today’s question was submitted by Wanda and she wants to know: What is a blockchain?

Wanda you came to the right place. Let’s walk one step at a time. There are hundreds of blockchains. “The blockchain” does not exist. Blockchains are categorized into one of four classes. Of the four types, public and private are most common, and the remaining two are consortium and hybrid.

Blockchain technology is computer software. Blockchains are essentially advanced databases or put another way blockchains are digital ledgers. What’s more, blockchains are databases that are shared over the internet. That’s the headline but of course there is more.

Blockchains exhibit certain characteristics. First, a blockchain must be immutable, meaning the contents of a published block cannot be changed. Changing even one letter within a record of a blockchain will trigger an entirely new unique identifier number thus causing that block to break its link to the previous block and breaking the chain.

Second, blockchains are append only. Adding a new block to the end of the chain is of course permitted. However, it is impossible to insert a new block in between two existing blocks. In other words, if the chain has 15 blocks, adding a 16th is permitted to the tail of the chain but it is not possible to slip a new block in between blocks 7 and 8, for instance.

You might ask, given the shared nature of blockchains and the fact there is no central authority in public blockchains, how do blockchains know what is correct? That is the right question, and the answer is blockchains have a method for getting the network to reach agreement known as the consensus algorithm. There are several consensus methods, the two most common are proof of work (Bitcoin) and proof of stake (most all other blockchains). Now, what are blocks?

A “block” is a list of transactions. Transactions are recorded onto a block over a pre-determined period. Block size and time permitted to fill blocks varies from blockchain to blockchain. Image a block as a book and each page as a transaction. Once the book reaches maximum capacity, or the time expires to fill the block, the “book”/block in the queue is time stamped and sealed. The block is then given a unique identifier and connected to the previous block thus forming a chain of blocks known as blockchain. YEAH! But there’s more.

Block 1 is connected to Block 2, Block 2 to Block 3, etc. Blocks are connected through a “chain”. The “chain” in blockchain is a series of hash tags produced by cryptography. Basically, hashes are fingerprints that lock blocks onto the chain in order and time. Hashing creates a one-way function that cannot be decrypted resulting in maximum security!

Wanda, I hope I answered your question. I would be disappointed if I violated the Turkish proverb of being a guide to a village that is visible in the distance.

Until next time.

Yogi Nelson

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Oro Digital, Plata Inteligente: La Perspectiva de los Metales Tokenizados en 2026

Yogi Nelson

Los activos más antiguos del mundo están recibiendo una actualización moderna. Oro, plata y varios metales industriales están migrando hacia la cadena de bloques, de manera silenciosa pero poderosa, con enormes implicaciones para los mercados, las carteras y las cadenas de suministro globales.

En 2026, los metales tokenizados pasan de “experimento interesante” a infraestructura financiera real.
El oro tokenizado supera los $1,000 millones. La plata avanza rápido. Y metales como el cobre, el litio y el níquel están cerca de unirse.

¿Por qué ahora?
La IA está transformando la exploración. Los gemelos digitales modernizan las minas. Los reguladores aportan más claridad. Y las instituciones se preparan para un mundo donde las liquidaciones tardan minutos, no días.

¿Qué ofrecen los metales tokenizados?
✔ Respaldo físico verificable
✔ Transparencia en cadena
✔ Liquidación global más rápida
✔ Interoperabilidad TradFi + DeFi

Esta es la Semana 1 de mi Serie 2026 sobre Metales Tokenizados.
Para leer la versión completa del artículo, visita mi blog: https://yogapuertorico.wordpress.com/wp-admin/post-new.php?post_type=post

Los metales digitales ya están aquí. Y 2026 será su año decisivo.

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Oro Digital, Plata Inteligente: La Perspectiva de los Metales Tokenizados en 2026

Yogi Nelson

Fundamentos de los Metales Tokenizados — Semana 1
Por Yogi Nelson, BlockchainAIForum

Introducción: Una Nueva Era para los Activos Más Antiguos del Mundo

Durante siglos —o mejor dicho, miles de años— los metales han sido la columna vertebral del comercio global, los sistemas monetarios, la expansión industrial y la seguridad nacional. ¿Quieres una base industrial sólida? Necesitas metales. ¿Quieres una defensa nacional robusta? Metales. ¿Quieres liderar en tecnología? También metales. Ya captas la idea.

Al comenzar 2026, los brotes verdes de una revolución empiezan a surgir. ¿Qué revolución? Nada menos que la tokenización en la cadena de bloques del activo más antiguo del planeta. Oro, plata, platino, cobre, litio, níquel, cobalto y hasta tierras raras están entrando en una etapa donde la propiedad, la liquidación, la colateralización y la verificación pueden ocurrir digitalmente, sin comprometer la integridad física del metal subyacente. Finalmente, un caso de uso financiero real para blockchain que no involucra un meme coin sin valor. Pero atención: esto no es una moda de marketing. Es una reorientación estructural.

Es cierto: los metales tokenizados aún están en etapas tempranas. Pero ya no son teóricos. ¿Por qué lo afirmo? Porque los volúmenes están aumentando. El interés institucional se acelera. La claridad regulatoria empieza a tomar forma. Y tecnologías como la IA, los gemelos digitales, la teledetección satelital y las pruebas criptográficas están modernizando toda la cadena de suministro minera y metalúrgica.

¿Intrigado? Yo también. Por eso me enorgullece publicar esta primera edición de una serie anual diseñada para ayudarte a entender dónde se encuentran hoy los metales tokenizados, qué tan rápido evolucionan y qué viene después.

El Panorama de los Metales Tokenizados en 2026

Oro: El Primer Movedor y Líder del Mercado

El oro fue la primera materia prima en tokenizarse y sigue siendo, por mucho, el mercado de metales digitales más grande. Se ha convertido en el caso de estudio emblemático para los activos del mundo real en blockchain.

A inicios de 2026:

  • La oferta de oro tokenizado supera los $1.1–1.3 mil millones.
  • Los emisores principales mantienen pruebas de reservas auditadas en cadena.
  • La liquidación pasó de días a minutos.
  • Los tokens de oro se utilizan cada vez más como colateral en TradFi y DeFi.
  • Fondos soberanos y bancos privados experimentan con liquidaciones transfronterizas en oro tokenizado.

Plata: El Metal Monetario–Industrial Híbrido

La plata tokenizada, que se acerca a los $200 millones, es menor en tamaño que el mercado del oro, pero crece con rapidez. ¿Podría convertirse en el primer metal industrial con relevancia operacional tokenizada? Si ocurre, será por razones como:

  • Su identidad dual: metal monetario y metal industrial.
  • Su volatilidad, atractiva para estrategias digitales de trading.
  • La necesidad de cadenas de suministro transparentes en energía solar, electrónica y tecnología médica.

Metales Industriales y Energéticos: La Siguiente Frontera

Aún rezagados —pero claramente dirigiéndose a la fiesta de la tokenización— están metales como el cobre, litio, níquel, cobalto, grafito y tierras raras.

¿Podría 2026 ser el año en que estos metales pasen de prototipos a adopción en producción? Es posible si se observa:

  • Seguimiento de cadenas de suministro de vehículos eléctricos mediante blockchain.
  • Gemelos digitales de yacimientos.
  • Auditorías de procedencia en cadena.
  • Pilotos institucionales para cobre y litio tokenizados.

Por Qué Importan los Metales Tokenizados

Respaldo Físico Verificable

Los metales tokenizados resuelven problemas estructurales de larga data:

  • Certificados de depósito duplicados o falsificados.
  • Barras fraudulentas.
  • Informes opacos de inventario.
  • Ciclos lentos de conciliación.

Cada token representa una cantidad precisa de metal. Eso significa auditorías continuas, registros inmutables y transparencia total. Tu departamento de cumplimiento estará encantado. Esto no es solo innovación: es reducción de riesgo.

Liquidación Global Más Rápida

Los mercados tradicionales de metales operan con velocidades de ayer: 24–72 horas para liquidar. Las empresas hoy quieren lo que los metales tokenizados ofrecen:

  • Liquidaciones en minutos
  • Menos fricción
  • Menor riesgo operativo
  • Mucho menos riesgo de contraparte

Interoperabilidad con TradFi y DeFi

La tokenización permite que TradFi y DeFi finalmente se den la mano. Los metales tokenizados pueden funcionar como:

  • Colateral
  • Instrumentos de liquidez
  • Componentes de portafolios estables
  • Herramientas de liquidación internacional
  • Activos programables dentro de contratos inteligentes

El Papel de la IA y la Infraestructura Digital

Descubrimiento y Planificación Impulsados por IA

Hasta ahora, el foco ha sido la tokenización. Pero como decían los viejos comerciales: “espera, que hay más.” Cuando combinas tokenización con IA, obtienes avances en:

  • Detección de mineralización
  • Modelado geológico
  • Mantenimiento predictivo
  • Pronóstico de rendimiento
  • Cumplimiento ESG
  • Seguridad minera

La minería está pasando de “perforar y rezar” a descubrir con datos.

Verificación Satelital y Basada en Sensores

La IA está cerrando la brecha de confianza en una industria históricamente escéptica. Con teledetección y dispositivos IoT, la procedencia del metal se vuelve:

  • Rastreable
  • Auditable
  • En tiempo real
  • Resistente al fraude

Impulso Regulador

Los mercados funcionales necesitan reglas claras. Punto.

Lo positivo es que los reguladores de todo el mundo están avanzando hacia marcos más claros para activos digitales. La claridad crea viento a favor, no obstáculos.

Observa:

  • La SEC y la CFTC refinan marcos para tokenización.
  • La UE y el Reino Unido impulsan estándares unificados para RWAs.
  • Fondos soberanos asiáticos prueban metales tokenizados para liquidaciones FX.
  • Bolsas de materias primas evalúan capas de liquidación tokenizada.

Cómo Se Está Adaptando el Mercado

¿Reaccionará el mercado favorablemente? Todos los indicadores dicen que sí —y a lo grande.
Los interesados incluyen:

  • Hedge funds
  • Traders sistemáticos
  • Administradores de activos
  • Asignadores digitales
  • Asesores patrimoniales

Corporaciones y Tesorería

Las empresas están adoptando metales tokenizados para:

  • Diversificación de balance
  • Gestión de colateral
  • Financiamiento a proveedores
  • Liquidaciones intercompañía

Empresas Mineras

La minería pide modernización a gritos. La tokenización ofrece una parte significativa de esa modernización:

  • Financiamiento más económico
  • ESG transparente
  • Inventario en tiempo real
  • Mayor confianza en la cadena de suministro
  • Todas las mejoras impulsadas por IA mencionadas anteriormente

Un Cambio Estructural, No una Tendencia

En China, 2026 es el Año del Caballo.
Para los metales tokenizados, 2026 será el Año de la Infraestructura Tecnológica y la IA.

Los caballos corren rápido; la tecnología y la IA harán que los metales tokenizados corran aún más durante los próximos años.

Espera:

  • La tokenización del oro se vuelve mainstream
  • La plata se consolida como un activo digital–industrial híbrido
  • Los metales industriales pasan de piloto a producción
  • La IA transforma la exploración y las operaciones
  • Los reguladores establecen verdadera estructura
  • Las instituciones adoptan plenamente los commodities digitales

El Camino por Delante

Durante las próximas 52 semanas, esta serie explorará:

  • La mecánica
  • Las oportunidades
  • Los riesgos
  • Los protagonistas
  • La economía
  • La geopolítica
  • La tecnología

Los metales tokenizados están entrando al escenario global.
2026 es el año en que se volverán imposibles de ignorar.

Me alegra que estés aquí para el viaje.

— Yogi Nelson
BlockchainAIForum

Uncategorized

Digital Gold, Smarter Silver: The 2026 Tokenized Metals Outlook

Yogi Nelson

The oldest assets on Earth are finally getting a modern upgrade. Gold, silver, and even key industrial metals are moving onto blockchain rails—quietly, steadily, and with major implications for markets, portfolios, and global supply chains.

In 2026, tokenized metals are shifting from “interesting experiment” to real financial infrastructure. Gold has passed $1B in tokenized value. Silver is accelerating fast. And industrial metals like copper, lithium, and nickel aren’t far behind.

Why now?
AI is reshaping exploration. Digital twins are modernizing mines. Regulators are offering clearer frameworks. And institutions are preparing for a world where settlement happens in minutes, not days.

Tokenized metals deliver something rare:
✔ Verifiable physical backing
✔ On-chain transparency
✔ Faster global settlement
✔ Interoperability with TradFi + DeFi

This is Week 1 of my 2026 Tokenized Metals Series.
For a full version of this article please visit my blog: https://yogapuertorico.wordpress.com/wp-admin/post.php?post=2508&action=edit

Digital metals are here. And 2026 is their breakout year.

— Yogi Nelson

Austrian economics, Blockchains, China, cryptography, Decentralized, Digital Currency, Environment, finance, Gold, International Finance, Mining, precious-metals, Science, Silver, tokenization, Yogi Nelson

Digital Gold, Smarter Silver: The 2026 Tokenized Metals Outlook

Yogi Nelson

The Tokenization Revolution No One Saw Coming (Except Us)

by Yogi Nelson

For centuries—better said, thousands of years—metals have functioned as the backbone of global trade, monetary systems, industrial expansion, and national security. You want a strong industrial base — you need metals. You want a strong national defense — you need metals. You want to be a world leader in tech — you need metals. You get the picture.

As we commence 2026, the green sprouts of a revolution are emerging. What revolution? Merely the tokenization on the blockchain of the oldest asset class on the planet — that’s all! Gold, silver, platinum, copper, lithium, nickel, cobalt, and even rare earth elements are now entering a transitional phase where ownership, settlement, collateralization, and verification can occur digitally—without compromising the physical integrity or custody of the underlying metal. Finally, a real financial use case for blockchain that doesn’t involve a silly meme coin void of value. But listen, this movement is not a marketing trend. It’s a structural realignment.

It’s true, tokenized metals are still early. However, they are no longer theoretical. Why the claim? Volumes are rising. Institutional interest is accelerating. Regulatory clarity is forming. And underlying technologies—AI, digital twins, satellite monitoring, cryptographic attestations—are modernizing the mining and metals supply chain across its entirety.

Hooked? I am. That’s why I’m proud to publish this first edition of a year-long series designed to help you understand where tokenized metals stand today, how fast they are evolving, and what comes next.

THE TOKENIZED METALS LANDSCAPE 2026

Gold: The First Mover and the Market Leader

Gold was the first major commodity to tokenize and remains by far the largest digital metals market. Gold has become the flagship case study for real-world assets on blockchain. As of early 2026:

– Tokenized gold supply exceeds $1.1–1.3 billion.

– Major issuers maintain audited, on-chain proof-of-reserves.

– Settlement speeds have dropped from days to minutes.

– Gold tokens are increasingly used as collateral in both TradFi and DeFi.

– Sovereign wealth funds and private banks are experimenting with cross-border settlement using tokenized gold.

Silver: The Hybrid Monetary–Industrial Asset

Silver’s tokenized footprint—approaching $200 million—is smaller but growing rapidly. Could silver become the first industrial metal where tokenization gains true operational relevance? If it does, it will be because of:

– Its dual identity as both a monetary metal and an industrial input.

– Volatility that makes it attractive for digital trading.

– Demand for transparent supply chains in solar, electronics, and medical technologies.

Industrial & Energy Metals: The Next Frontier

Lagging behind—but certainly on their way into the tokenization party—are the industrial metals: copper, lithium, nickel, cobalt, graphite, and rare earth elements. Could 2026 be the year industrial metals tokenization shifts from prototypes to production? It’s possible if you consider:

– Blockchain-based EV supply-chain tracking.

– Digital twins of ore bodies.

– On-chain provenance audits.

– Early institutional pilots for tokenized copper and lithium.

WHY TOKENIZED METALS MATTER

Verifiable Physical Backing

Tokenized metals solve longstanding structural problems. A few examples:

– Duplicate or falsified warehouse receipts.

– Fraudulent bars.

– Opaque inventory reporting.

– Slow reconciliation cycles.

Each token represents a precise quantity of metal, which means audits become continuous. Your compliance department will love that. Ownership becomes immutable and transparent. This is not just innovation — it’s risk reduction.

Faster, Global Settlement

Conventional metals markets reflect yesterday’s speed. Today, businesses don’t want 24–72 hours to settle. They want what tokenized metals offer: settlement in minutes, reduced friction, lower operational risk, and far less counterparty exposure.

Interoperability with TradFi and DeFi

Tokenization is what finally lets TradFi and DeFi shake hands and work together. Tokenized metals can function as:

– Collateral.

– Liquidity instruments.

– Components of stable-value portfolios.

– Cross-border settlement tools.

– Programmable assets inside smart contracts.

THE ROLE OF AI AND DIGITAL INFRASTRUCTURE

AI-Driven Discovery and Planning

Until now the focus of this article has been on tokenization. But as the old commercials used to say, “Wait — there’s more.” Combine tokenization with AI and you get advanced:

– Ore detection.

– Geological modeling.

– Predictive maintenance.

– Yield forecasting.

– ESG compliance.

– Mine-safety planning.

Mining is shifting from “drill and hope” to “discover with data.”

Satellite and Sensor-Based Verification

AI closes the trust gap in an industry known for suspicious minds. With remote sensing and IoT devices, metals provenance becomes significantly easier. Why? Because the tech makes metals:

– Traceable.

– Auditable.

– Real-time.

– Fraud-resistant.

REGULATORY MOMENTUM

Functioning markets need clear rules and enforcement. Period. The good news is regulators worldwide are moving toward clearer digital-asset frameworks. Clarity is accelerating adoption — tailwinds now rather than obstacles. Consider:

– The SEC and CFTC refining tokenization guidelines.

– The EU and UK advancing unified RWA standards.

– Asian sovereign funds piloting tokenized metals for FX settlement.

– Commodity exchanges evaluating tokenized settlement layers.

HOW MARKETS ARE ADAPTING

Will the market react favorably to tokenized metals? If tokenization follows the pattern of other assets—and every indicator suggests it will—then yes. Big-time yes. Who is drawn to this emerging market?

– Hedge funds.

– Systematic traders.

– Asset managers.

– Digital-asset allocators.

– Wealth advisors.

Corporations & Treasury

Corporations and treasury teams are also participating in this bullish trend. They are using tokenized metals for:

– Balance-sheet diversification.

– Collateral management.

– Supplier financing.

– Inter-company settlements.

Mining Firms

Mining is an industry begging for modernization. Tokenization delivers part of that modernization. Miners benefit through:

– Lower-cost financing.

– Transparent ESG tracking.

– Real-time inventory visibility.

– Improved supply-chain trust.

– All AI-driven improvements listed earlier.

A STRUCTURAL SHIFT, NOT A TREND

In China, 2026 will be the Year of the Horse. For tokenized metals, 2026 will be the year of tech and AI infrastructure. Horses run fast — tech and AI will enable tokenized metals to run fast for years to come. Expect:

– Gold tokenization becomes mainstream.

– Silver emerges as a hybrid digital–industrial asset.

– Industrial metals advance from pilot to production adoption.

– AI reshapes exploration and operations.

– Regulators provide real structure.

– Institutions embrace digital commodities.

THE JOURNEY AHEAD

Over the next 51 more weeks, this series will explore:

– The mechanics.

– The opportunities.

– The risks.

– The players.

– The economics.

– The geopolitics.

– The technology.

Tokenized metals are entering the global stage. 2026 is the year they become impossible to ignore. I’m glad to have you here for the journey.

— Yogi Nelson

BlockchainAIForum

AI Tools, Artificial Intelligence, Banking, Blockchains, climate-change, Construction, cryptography, Decentralized, Digital Currency, finance, Gold, International Finance, Mining, Silver, Tether, tokenization, Uncategorized, Yogi Nelson

Los Mercados de Materias Primas Están Entrando en una Transición Estructural

Yogi Nelson

por Yogi Nelson

Los mercados de materias primas están entrando en una transición estructural. El oro, la plata, el cobre, el litio, el níquel, el cobalto e incluso los elementos de tierras raras están comenzando a migrar hacia la infraestructura de cadena de bloques. Esto no es un eslogan publicitario; es un rediseño lento pero real de cómo funcionan la propiedad, la liquidación y el uso de activos como colateral.

En 2026, lanzar é una serie de 52 semanas en BlockchainAIForum dedicada exclusivamente a los metales tokenizados—donde los activos duros se encuentran con los rieles digitales.

Por Qué Esto Importa Ahora

El oro tokenizado ha superado los $1,000 millones en circulación.

La plata tokenizada se acerca a los $200 millones.

Los metales industriales están en la fila siguiente.

La IA está transformando la exploración, la planificación minera y la visibilidad de las cadenas de suministro.

Los reguladores avanzan hacia marcos más claros para los activos digitales.

Para inversionistas, tesoreros y estrategas, los metales tokenizados combinan:

  • Respaldo físico verificable
  • Transparencia y auditabilidad en cadena
  • Liquidación global más rápida
  • Interoperabilidad con sistemas TradFi y DeFi

Lo Que Cubrirá Esta Serie

  • Metales preciosos en cadena (oro, plata, platino, paladio, rodio)
  • Metales industriales y energéticos (cobre, litio, níquel, cobalto, grafito, tierras raras)
  • IA, gemelos digitales y trazabilidad ESG en la minería
  • Diseño de portafolios, colateral y desarrollos regulatorios (SEC/CFTC)

Si tu trabajo toca materias primas, gestión de riesgo, tesorería o estrategia de activos digitales, estoy seguro de que esta serie te resultará útil.

2026 será un año importante para las materias primas digitales. Me encantaría que me acompañaras en este recorrido.

— Yogi Nelson
BlockchainAIForum