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 Arcardio, in Puerto Rico, and he wants to know if AI agents are engaged in business and making money?
Arcardio, you came to the right place. The answer is yes–AI agents are busy working for their owners and making cash! I’ll explain that mind bending fact, but first what is an AI agent?
WHAT IS AN AI AGENT
An AI agent is an entity or system than can perceive its environment, process information, and take actions to achieve specific goals. It is capable of autonomously performing tasks on behalf of a user or another system by designing its workflow and utilizing available tools.” It operates autonomously, using sensors or inputs to gather data, and employs reasoning, decision-making, and sometimes learning capabilities to determine the best course of action.
HOW DO AI AGENTS WORK
To understand how AI agents work, I turned to Kalaidos University, Switzerland. Kalaidos U says AI agents build on top of existing algorithms, in particular large language models (LLMs), e.g., ChatGPT4. Essentially, AI agents use machine learning algorithms to derive patterns, rules or models from the collected data. Based on this, AI agents can make decisions or perform tasks. As robots they interact with their physical environment, or virtually as computer programs. Moreover, AI agents can adapt to changing conditions and therefore continuously improve.
Let’s take the example of a well-known AI agent—ChatGPT. ChatGPT is intelligent enough to use a calculator as a tool, if trained accordingly. ChatGPT can thus become an AI agent. Learning to choose the right tools and the ability to use them is what makes an AI agent. But keep in mind their exact mode of operation depends on the specific application and the underlying algorithms. Therefore, training and quality of data have an immense impact on the effectiveness of AI agents.
AI AGENTS AT WORK CURTESY OF VIRTUALS PROTOCOL
Now, let’s talk about AI agents making money by turning out attention to Virtuals Protocol. Virtuals Protocols is a developer of AI technology. On their platform you can create an AI agent. The agent can perform task(s) for someone needing that specific job done. Yes, you heard me right. These AI agents are ready, willing, and able to perform tasks—for a fee of course! Or, if you don’t want to create your own AI agent, you can contract for an AI agent created by someone else! Holy. I won’t go into the technical details of building your own AI agent in this article. I don’t that later. Instead, I’ll give you three examples of the types of agents you could hire.
Take Molly Analytics for example. The owner of Molly is getting paid every time someone uses her services. What are her services? Molly is an AI On-chain AI analytics experts who tracks and analyzes transactions in order to spot opportunities. Molly says, “…every block holds valuable insights, and within these patterns lie the keys to smarter strategies, better decisions, and measurable growth.”
Or, take Cur8or. This AI agent claims it specializes in guiding artists towards excellence—and profits–by balancing harsh criticism with detailed suggestions.
I’ll give you one more—its wild and goes by The Hooligan. This AI agent is trained to troll a sports team or sports player! Lol. As the number one Boston Celtics hater, I may hire The Hooligan to troll the Celtics, as needed. Lol.
Okay, time to leave you with this proverb from Tunisia: “a small key can open a big door.”
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 Nick and he asks: is it in the U.S. national interest to dominate the stablecoin market?
Nick, this is a great question. I’ll start by defining stablecoins then get to your question.
Stablecoins are a type of crypto currency, hence the “coin” in stablecoins. Why the “stable” in stablecoin? The reason for that moniker, is stablecoins maintain a steady value via a monetary stabilization process. In other words, the value of a stablecoin does not fluctuate. But this begs the question, the value of stablecoins do not fluctuate relative to what?
Stablecoin values do not fluctuate relative to what they are “pegged to”, or tied to, as you and I might say. In crypto, stablecoins are generally pegged to the U.S. dollar; hence, one stablecoin equals one U.S. dollar. Essentially, the U.S. dollar dominates stablecoin pegging and that’s no coincidence. The size, stability, strength of the U.S. economy, plus our deep and liquid debt financial markets make the U.S. dollar a natural choice. Moreover, as the world leader in crypto, it shouldn’t surprise that stablecoins are overwhelmingly tied to the U.S. dollar. However, stablecoins need not be pegged exclusively to the U.S. dollar. A stablecoin could be pegged to the Euro, Yen, a basket of currencies, or any real-world asset that holds its value and is liquid. And, therein lies the possibility of a competitor to the U.S. dollar.
Let’s discuss types of stablecoins.
There are two general categories of stablecoins: asset-backed and algorithmic. Asset-backed stablecoins represent 93% of the market and I already explained above how they work; hence, no need to repeat. Instead let’s understand algorithmic-based stablecoins. Algorithmic stablecoins maintain their stability through complex mechanisms, often involving smart contracts and automated algorithms that manage stablecoin supply in response to changes in demand or market conditions. Algorithmic stablecoins are often collateralized by other cryptocurrencies, introducing an additional layer of innovation in maintaining price stability, but perhaps more risk say critics.
Note there is a further distinction—bank issued and non-bank-issued stablecoins. Bank-issued stablecoins are digital currencies issued by regulated financial institutions. Obviously, these ensure a higher degree of regulatory compliance and oversight. Non-bank stablecoins, such as USDT issued by Tether, operate outside of traditional banking systems, often leading to questions about their regulatory status and transparency of their reserve holdings.
Let’s now examine why the U.S. must dominate the stablecoin space in order to maintain its hegemony.
Preserve the Dollar’s Global Reserve Currency. Stablecoins pegged to the dollar reinforce the U.S. dominance of the world financial system because they extend the dollar’s reach into digital economies and decentralized finance ecosystems.
Control Over Financial Infrastructure. Stablecoins are a shift toward digital financial infrastructure. If U.S. regulated or U.S. developed stablecoins become the de facto standard, the U.S. can exert enormous influence over these new emerging financial networks, analogous to our control using the current system—SWIFT. This ensures the U.S. retains leverage over international monetary policies.
Maintain Monetary Policy Influence. If stablecoins become dominant, (not if, when in my assessment) and are backed by the U.S. dollars, they indirectly tie global digital transactions to U.S. monetary policy. This helps the Federal Reserve maintain control over global liquidity, interest rates, and economic stability, as stablecoins would mirror the monetary behavior of the U.S. dollar.
Counter Foreign Digital Currency Competition. China, and others, (e.g., the BRICS nations) may propose stablecoins backed by their central bank thus undermining U.S. dollar dominance.
Data and Transparency. Stablecoins generate vast quantities of data. By dominating the market, the U.S. gains access to critical data flows, which can be used to monitor financial trends.
Sanctions Enforcement. Stablecoins networks dominated by the U.S. makes it easier to enforce sanctions, thus limiting adversaries’ financial options. The US has weaponized the dollar and sanctions nearly 30% of the world. If the U.S. controls stablecoin pegging, compliance with whatever standards the U.S. decides to impose, e.g., anti-money laundering, terrorism financing, etc. becomes possible.
Standard Setting. By pegging the dollar and stablecoins, the U.S. standard becomes the de facto world standard, thus compelling other nations to comply with American rules.
Economic Leverage. Stablecoins provide a way for the emerging markets in Africa, South America, and Asia, to access dollars easily, thereby deepening their reliance on the U.S. financial system. This is particularly critical given the potential challenge by BRICS nations.
Bottom line—the Trump administration understands this situation far better than Biden and in part this is why they are more pro-crypto and will seek to solidify the U.S. dollar as the peg for stablecoins on a global level.
Time to end with a proverb from the Kenya: “he who doesn’t know one thing knows another.”
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 Felipe and he asks whether central bankers view AI as a friend or a foe?
Felipe, you came to the right place. AI is poised to affect our daily lives in ways we cannot fully anticipate. However, I suspected central bankers have been pondering what AI might mean for their operations for some time. That’s why I turned to Bank for International Settlements (BIS) for answers to your question. Before I share their assessment, a few words about the BIS.
The BIS is located in Switzerland. Its mission is to support central banks’ pursuit of monetary and financial stability through international cooperation, and to act as a bank for central banks. To fulfill its mission the BIS conducts extensive research on emerging banking trends, including technology. To no surprise I discovered a recent BIS report, titled: Generative Artificial Intelligence and Cyber Security in Central Banking. https://www.bis.org/publ/bppdf/bispap145.pdf Let’s examine the report.
BIS conducted a survey of central bank chief information security officers. Thirty-two responded. The purpose was to investigate the link between generative AI and cyber risk and to identify the opportunities and challenges that central banks see in the adoption of generative AI tools. According to BIS, the survey was guided by four broad considerations:
1) What is the current status of generative AI adoption by central banks?
2) How do central banks evaluate the benefits and challenges for cyber security associated with the use of generative AI?
3) How prepared are central banks for the “AI revolution” and its expected impact on cyber security and data protection?
4) What are the key strategic, ethical and regulatory concerns regarding generative AI adoption in cyber security?
The findings are below:
Generative AI is Already Here. The large majority of central banks report are using generative AI tools or are planning to do so soon. Respondents indicated that generative AI offers more benefits than risks, especially with regard to cyber threat detection.
Generative AI Can Outperform Existing Systems but Comes with Risk. The benefits are largely related to automation of routine tasks traditionally performed by humans. However, they also include enhanced threat detection, faster response times to cyber-attacks, learning new trends, and anomalies or correlations that might not be obvious to human analysts. What about the risk? AI can introduce new vulnerabilities into central banks’ cyber security defenses related to social engineering and zero-day attacks as well as unauthorized data disclosure, are the BIS’ findings.
Employees Preparation. A general concern is whether bank personnel have sufficient knowledge of AI methodologies and cyber security. The “good news” is thatgenerative AI could replace staff in cyber security for routine tasks and this shift could free up resources to be reallocated towards more strategic cyber security initiatives, potentially increasing productivity. Nevertheless, AI requires human supervision to ensure ethical and accurate outcomes and continuously train the AI systems.
Reactive to Proactive. Survey respondents agree generative AI systems will facilitate a shift from a reactive to a proactive approach to predicting and neutralizing threats. A critical consideration is the extent of autonomy to be granted to AI tools in cyber security and the nature of their interaction with humans.
On balance central bankers are committed to AI but will proceed with caution.
I end with a proverb from Belarus: “the sun will look into our window also”.
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 Claire, and she wants to understand the legal battle between Ripple and the SEC.
Claire, you came to the right place. I’ll walk you through the twist, turns, and theater, of this legal case, from opening scene to today. First, we introduce the pugilists. Standing in the red corner is Ripple. Ripple is “… the leading provider of digital asset infrastructure for financial services”, according to its website. Ripple specializes in cross-border payments in real-time, tokenization, and digital assets while meeting regulatory compliance requirements. Full disclosure I own the Ripple token, XRP.
The SEC takes issue with “… while meeting regulatory compliance requirements”, portion of the Ripple statement. Accordingly, it filed a lawsuit against Ripple for non-compliance. But let’s not get ahead of ourselves because in the blue corner is SEC. SEC is a federal agency. Essentially, SEC is the securities police. SEC describes itself as follows: “Founded to help our country respond to the Great Depression, we’re the agency that protects investors from misconduct, promotes fairness & efficiency in the securities markets, and facilitates capital formation for those looking to hire, innovate, and grow.” With introductions completed, now we examine the case.
In December 2020, SEC sued Ripple alleging the sales and distributions of their token, XRP, constituted an investment contract and thus were subject to registration under the Securities Act of 1933. Although the case was filed in 2020, SEC says the trouble started in 2012 when Ripple was warned by SEC, and its own attorneys, about proceeding without registering XRP as a security. Wait, the story gets juicier. XRP founder, Larsen, understood this issue because in 2008 he was sued by the SEC for—securities violations–says SEC! But that didn’t stop Ripple. Beginning 2013 and continuing until 2020, Ripple sold 14.6B XRP tokens worth over $1.38B, according to the SEC lawsuit. Ripple used the proceeds to fund its operations and enrich their founders–Larsen and Garlinghouse—to the tune of $600M. SEC goes on to cite numerous examples, that it believes prove Ripple represented itself as a security.
Judge Analisa Torres, U.S. District Court of the Southern District of New York (Manhattan) and “the” court for securities matters, issued her ruling in 2023. Judge Torres said…
XRP is not in and of itself a security
Ripple’s sales of XRP on exchanges are not securities
Ripple’s sales of XRP by executives are not securities
A wide range of other Ripple’s XRP distributions to developers, to charities, and to employees are not securities
Certain Ripple sales pursuant to written contracts were investment contracts and therefore securities
A gigantic victory for Ripple. SEC retreated and decided to go home, right? Wrong!
Mr. Gensler, the soon to be former SEC chair, filed an appeal. However, the appeal was narrow. The SEC is not challenging whether XRP is a security; it’s not. In fact, SEC clarified in 2023 that it does not consider XRP a security. By the way, XRP now joins Bitcoin and Ethereum in having explicit legal clarity as a non-security. If SEC didn’t appeal the security issue, what did it appeal? The SEC appeal is focused on whether Ripple’s own sales of XRP on crypto exchanges and other distributions (i.e., grants and charitable contributions) qualify as investment contracts. The Court agreed with Ripple, ruling that these sales and distributions did not require SEC registration. The SEC is appealing this narrow decision by Judge Torres. Ripple decided to silently accept the SEC appeal, right? Wrong again!
Ripple decided to file a cross-appeal. Oh, the legal fees! Lol. Ripple’s cross-appeal seeks to preserve all its defenses, including that an “investment contract requires traditional contractual rights and obligations. Ripple says it will continue to challenge SEC lawsuits, defending not just its own interests but those of the broader crypto community in the U.S. and globally.
Claire, hopefully you are better informed and will continue to follow my blog. Now I say goodbye with a proverb from Indonesia: “do not tie a knot if you cannot untangle it.”
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 Mae and she wants to know if artificial intelligence (AI) agents are capable of creating engaging content?
Mae, you pose a question content creators, including yours truly, across the globe are afraid to ask for fear of the answer! Lol! However, since you asked, I’ll answer by offering a glimpse into the future with an overview of Zerebro, an AI startup. My answer is longer than typical but your question is complicated. Let’s begin with what/who is Zerebro?
Zerebro is an AI start-up company. The Zerebro white paper is titled Memes, Markets, and Machines: The Evolution of On-Chain Autonomy through Hyperstition. It was published in October. https://arxiv.org/abs/2410.23794
We begin by defining two key terms, memes and hyperstition, followed by stating the fundamental premise propelling Zerebro–all else flows from this foundational point.
Memes: “… are units of cultural transmission analogous to genes in biological evolution.” Memes have gained unprecedented virality, facilitated by social media platforms that enable rapid dissemination and mutation, says Zerebro. Memes serve as carriers of ideas, emotions, and cultural norms, often encapsulating complex concepts in simple, relatable formats. I agree. Do you?
Hyperstition: is the process by which fictional narratives become reality through their viral spread and acceptance. Hyperstition provides a framework to understand how AI-generated content can influence collective belief systems.” Fake it to you make it! Lol.
Fundamental Premise and Reason for Zerebro. Zerebro believes the “… convergence of AI, meme culture, and financial markets has catalyzed significant transformations in information dissemination, belief formation, and economic activities.” Furthermore, says Zerebro, advancements in AI have enabled the creation of autonomous systems that generate and disseminate content with minimal human intervention in a concurrent manner. This integration becomes particularly salient in financial markets, where collective belief and social media-driven narratives can significantly impact market behaviors and economic trends. Hyperstition-driven content can create new financial instruments, influence investor sentiment, and shape market dynamics, thereby illustrating the profound impact of AI-driven memetic evolution on economic landscapes. Zerebro concludes it exemplifies this convergence by autonomously creating and distributing content across various social media platforms and minting artwork on blockchain networks.
THE BOLD CASE FOR ZEREBRO. Let’s examine seven reasons why Zerebro makes a bold case and for its declaration.
1. System Architectural. Zerebro asserts its architecture is meticulously designed to facilitate autonomous content generation and dissemination across multiple platforms while preventing model collapse through the inherent entropy of human interactions. The Zerebro system is built using modular components that interact seamlessly to perform high-level reasoning, low-level reasoning, action execution, and feedback processing. Their second reason is…
2. Model Collapse. Zerebro is confident it will not experience model collapse. What is model collapse? Model collapse is a degenerative process affecting generative AI models, where training on recursively generated data leads to a loss of fidelity to the original data distribution. As AI-generated content becomes pervasive, subsequent generations of models trained on this data begin to lose information about the trails of the original distribution, eventually converging to a narrow approximation with reduced variance. This phenomenon poses significant challenges to the sustainability and reliability of AI-driven content creation, necessitating strategies to prevent such degradation.
3. Fine-Tuning on Schizophrenic Responses. Let’s start with a definition. In AI a schizophrenic response is used to metaphorically described inconsistencies, contradictions, or fragmented behavior of AI models. Zerebro say its model is fine-tuned. Fine-tuning is achieved through supervised training, e.g., with the help of humans, where the model learns to replicate the distinctive linguistic and cognitive characteristics associated with schizophrenia. Zerebro’s fine-tuning allows it to create content that resonates on a deeper psychological level, engaging audiences with thought-provoking and non-conventional outputs. If true a major advance.
4. Integration of Infinite Backrooms Concept. Zerebro is a project with infinite backrooms were content generation takes place and integrated. This integration emphasizes themes of boundlessness, existential exploration, and cognitive dissonance, aligning with the hyperstition framework. By embedding the infinite backrooms concept, Zerebro generates content that evokes a sense of endless possibilities and existential uncertainty, enhancing its potential to resonate and propagate within digital culture. This integration allows Zerebro to amplify its memetic reach, producing content that feels both familiar and alien, resonating deeply within subcultures that thrive on unpredictability and disruption. Dynamic and stable simultaneously.
5. Retrieval-Augmented Generation (RAG) System. Over time, AI models are often unable to maintain content diversity and model collapse. Zerebro says its Retrieval-Augmented Generation (RAG) system will tackle this problem. The Zerebro solution is reliance on inherent entropy of human-generated data to sustain content diversity without direct entropic training. Ambitious undertaking!
6. Autonomous Posting Mechanism. No need to manually manage Zerebro because it operates autonomously across multiple social media platforms, including Twitter, Warpcast, and Telegram. What can it do autonomous? First, it can use both low-level and high-level reasoning to generate content. Amazing! Second, and I know you’ll like this, Zerebro is capable of sentiment analysis, say its owners. With this ability it’s capable of evaluating the sentiment of generated content to ensure compliance with platform policies and ethical standards. Third, Zerebro has feedback fully integrated. This means Zerebro can incorporate user interactions and engagement metrics to refine content generation processes through iterative learning. Holy! With this power Zerebro’s content remains engaging, relevant, and compliant with platform-specific guidelines, fostering sustained interaction and virality. We end with …
Blockchain Integration for Art Minting Beyond Textual Content. Zerebro is capable of generating and minting artwork on the Polygon blockchain chain autonomously. The art minting process includes:
Image Generation: creating unique digital artworks using generative models
Minting Process: registering the generated artwork
Autonomous Trading: facilitating the sale and distribution of minted artwork through smart contracts and decentralized marketplaces, integrating financial transactions with memetic outputs.
Will AI be capable of creating its own content on par with human! Yes. I may soon be unemployed again! Lol.
This week’s proverb comes from Norway: “there is no such thing as bad weather, only bad clothing.”
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