Tag: Blockchain

Artificial Intelligence, Blockchains, cryptography, Maritime, Uncategorized, Urban Planning, Yogi Nelson

Navigating the Future: AI’s Role in Maritime Innovation

Yogi Nelson

Welcome to the Blockchain & AI Forum, where your technology questions are answered. Today’s question: how will artificial intelligence impact the maritime industry?

Trade and tariffs are headlines across the globe.  Trade and tariff share a common feature—shipping. Hence, now is a perfect time to examine AI trends within the maritime industry. 

According to Spire Maritime, a firm dedicated to providing a wide range of services to the industry, maritime companies linger in Ai adoption. Spire Maritime claims the maritime industry is now moving fast, hopefully faster than a cargo ship, in incorporating AI, Large Language Models, and Natural Language Processing (NLP).  In a very recent report, Thetius, a well-known maritime consultancy, says the maritime AI market is valued at $4.1B.  The good news is $4.1B represents a substantial increase from just $1.4B two years ago.  Moreover, 36 shipping companies have implemented or plan to deploy AI-enabled tech this year. 

Let’s briefly examine possible AI use cases in the maritime industry.   

Automation.  For example, in the future could AI lead to autonomous navigation?  The labor savings could be significant.  Or perhaps more immediately, AI could be used to automate mundane tasks such as detection of vessel names, contact information, shipowner, and technical specifications.  With AI maintenance and repairs and anticipated well in advance thus reducing vessel down time. 

Replacement of Manual Inputs with Data-Driven Predictive Information.  Spire Maritime points to the extensive reliance of human, often error-prone inputs as pervasive in maritime.  Rather than manual inputs, AI could be used to determine route optimization based on weather, fuel consumption, speed, and safety considerations.  The fuel savings alone could be significant not to mention the safety of crews nor the favorable impact on the environment. 

Detection of Patterns or Anomalies Using Data.  The maritime industry generate billions of data points.  Consider for a moment the millions of containers processed at a major port, such as the Port of Los Angeles, where I worked for three years.  Now multiply that by the hundreds of ports around world.  The data is overwhelming.  Making sense of the data and turning it into actionable information is the power of AI. 

These are all great use case possibilities, so why the delay or hesitation?  The answer boils down to several considerations:

  1. Data Quality and Accessibility.  As in many industries, the maritime industry faces issues regarding inconsistent or incomplete data.
  2. Integration with Existing Systems.  The maritime industry is ancient and as are its legacy technologies.  Integrating the new without disruption is a daunting task.
  3. Data Standardization.  Worldwide industry are often replete with inconsistent standards, maritime is no exception.
  4. Industry-wide Collaboration.  Can you image the collaboration required to effectively implement AI in the maritime industry; an industry with dozens of stakeholders, including shipping companies, port authorities, tech providers, etc. 
  5. Trust.  Can the technology be trusted with safety decisions, automation, etc. 

Time to go, but first a proverb from a nation with an important maritime industry; the island nation of Malta where they say:

Until next time,

Yogi Nelson

https://spire.com/maritime/maritime-artificial-intelligence-and-machine-learning/#:~:text=What%20is%20the%20role%20of%20AI%20in%20fleet%20management%3F,costs%2C%20and%20maximizes%20fleet%20performance.

https://www.lr.org/en/knowledge/research-reports/2024/beyond-the-horizon/

https://www.mitags.org/ai-impact-maritime-industry/

https://www.adv-polymer.com/blog/artificial-intelligence-in-shipping

https://cmr.berkeley.edu/2024/12/utilizing-ai-for-maritime-transport-optimization/

AI Agents, Artificial Intelligence, Blockchains, content creation, cryptography, Uncategorized, Yogi Nelson

How Personality Traits Shape AI Attitudes

Yogi Nelson

Welcome to the Blockchain & AI Forum, where your technology questions are answered.   Benjamin asks, do personality traits influence attitudes toward artificial intelligence?

Benjamin that’s an awesome question!  To answer your question, I’ll start by defining personality traits. 

Personality Traits.  ScienceDirect tell us that personality traits are relatively stable patterns of thoughts, feelings, and actions in which each individual is different from the others. In other words, personality traits are fairly stable over time and across situations but still open to change. Personality traits are primarily units of analysis of individual differences relative to cognitions, emotions, motivations, and behavior. They do not include physical features, e.g., attractiveness, or abilities, e.g., intelligence.

Personality traits operate within a larger social context.  Hence, the place to begin is obvious—economic.  Let’s be honest, AI makes workers anxious—and workers may have reason to be nervous.  According to Goldman Sachs, McKinsey, and the Nexford University, between 400M and 800M workers worldwide could lose their jobs by 2030 due to AI.  Jobs most at risk include:

Data Entry                                           Customer Service Representative

Manufacturing                                    Transportation & Logistics

Retail Sales                                          Market Research Analyst

Proof Readers & Translators              Radiologists and Diagnostic Technicians

Financial Analysts                               Bookkeepers and Accounts

Economic is not the exclusive concern of humans with AI; people also express worry about the social impact of AI.  For example, will AI reinforce biases?  Will AI leave millions “behind”?  Will AI eliminate all privacy?  Will AI cut my health insurance right before an illness?  The list of concerns is long.

According to “The Role of Personality Traits, AI Anxiety, and Demographic Factors in Attitudes Toward Artificial Intelligence, Journal of Human-Computer Interaction, 2024,” personality traits influence attitudes toward AI. The report is based on a survey taken in Turkey.  Let’s examine the report in detail.

https://www.tandfonline.com/doi/pdf/10.1080/10447318.2022.2151730

The following hypotheses were tested:

  1. Demographic Characteristics (i.e., age, gender, education level, level of computer usage, level of AI) could predict attitudes towards AI.
  2. Higher openness to experience would coincide with greater positive attitudes toward AI.
  3. Higher AI anxiety would predict more negative attitudes toward AI.

RESULTS

Age. Age did not predict attitudes toward AI.  That was somewhat unexpected. 

Agreeable.  Researchers used a series of questions to determine whether agreeable traits.  Researchers concluded people who were determined to be agreeable had positive attitudes toward AI.  Interesting! I suppose I should agree. lol.

AI Configuration Anxiety.  AI configuration anxiety means a fear of humanoid AI, e.g., human-like robots.  The more AI configuration anxiety, the more negative attitude toward AI. Logical.

AI Learning Anxiety.  AI learning anxiety significantly predicted both positive and negative attitudes toward AI.  The less learning anxiety the more positive attitude and vice versa.

Computer Usage. Computer usage was predictive of attitudes toward AI.  The more computer usage the greater was the positive view of AI. No surprise.

Conscientiousness.  Whether people are conscientious or not apparently makes no difference in their attitude toward AI, researchers say.

Extroversion.  The findings were mixed on extroversion.  Technologies that facilitate social interactions may be liked by extroverts but AI technologies can help reduce social interactions.  Thus, the mixed results.

Gender. Gender did not predict attitudes toward AI. However, men tend to view AI more positively than females. 

Job Replacement Anxiety.  People are worried.  Lol.

Self-Rated AI Knowledge.  People who consider themselves tech savvy and AI literate, have a more positive attitude toward AI.  Makes sense.

Time to end with a proverb from Turkey, where they say: “stretch your foot according to your blanket”.

Until next time,

Yogi Nelson

AI Agents, Artificial Intelligence, Blockchains, Environment, Productivity, Railwlays, Uncategorized, Urban Planning, Yogi Nelson

Navigating AI Disruption in the Railway Sector

Yogi Nelson

Welcome to the Blockchain & AI Forum, where your technology questions are answered.   Harold asks, how will artificial intelligence affect the railway industry?

Harold, you came to right place.  I’ll answer your question by citing research reports from McKinsey & Company, International Union of Railways (UIC), and Startus Insights.  Let’s start with the McKinsey report, titled: The Journey Toward AI-Enabled Railway Companies.

Prominent AI Use Cases in the Railway Industry:  McKinsey Report Findings

According to McKinsey, railway companies are focusing their AI efforts on approximately 20 use cases.  It should be noted, the McKinsey identified over 100 potential use cases!  The top 20 use cases are related to four key performance indicators:  on-time performance, customer engagement, safety, and operational performance.  The table below summarizes the use cases by category:

Table 1
ARTIFICIAL INTELLIGENCE USE CASES IN THE RAILWAY INDUSTRY
Business ActivityDescriptionAI Use Case
Railway UndertakingsActivities that are directly & indirectly related to delivering the final productCrew trainingSafetyOnboard operationsRolling stock maintenanceTrain station operationsRolling stock procurement & inventory management
Infrastructure ManagementActivities that are directly & indirectly related to the infrastructure needed to deliver the final railway productNetwork planningNetwork traffic managementNetwork constructionNetwork maintenance Rail safetyNetwork procurement and inventory management
Passenger ExperienceCustomer facing activities related to the operations of the railway companyBooking and ticketingCustomer railway journeyPassenger informationIn-station additional revenue  
Support FunctionsEssential non-operational activitiesHRFinanceIT

Of course, not all use cases have equal priority.  In the table below, the five most common use cases are listed on the left, and the five least used on the right.  The other 10 are in the middle.

Table 2 ATable 2B
Top 5 AI Use Case in Railway IndustryBottom 5 AI Use Cases in Railway Industry
Crew and shift managementNetwork infrastructure digital twin
Rail predictive maintenanceReal time disruption management
Real time intermodal informationTalent training
Energy efficient managementAutonomous trains
Security fraudSoftware development

The Keys to Successful Incorporation of AI in the Railway Industry:  UIC Report

We now turn to the findings by the Union of International Railways; UIC per their French acronym.  The UIC researchers claims that the railways with the most successful AI abilities share certain characteristics. For example, these railway companies dedicate research and development teams to their AI efforts.  Furthermore, they establish cultures of innovation and investment in partnerships to develop new technology.  Yet a third reason is that they build capabilities to implement use cases; and take a business-driven approach (rather than solely relying on IT departments) to drive development.  UIC researches say, there are six specific keys to success: strategic roadmap, skills, agile operating model, technology, data, and adoption and scaling. 

Who Are the AI Disrupters in the Railway Industry:  StartUs Insights Report

According to StartUs Insights, a consultancy specializes in discovery of intelligence trends, innovation, and engagement with the world’s most promising startups, scaleups, and technologies, there are 20 AI startups impacting the railway industry.  I’ll refrain from listing them all, and instead highlight three that best exemplify the AI story in railways. 

Let’s start with rail safety and the startup called RMT.  RMT is based in Italy.  RMT specializes in automatic recognition of defects on rail infrastructure, and employing AI to detect physical defects.  Energy efficiency is the wheelhouse of RailVision Analytics, a Canadian startup dedicated to improving energy efficiency via algorithms that reduce unnecessary braking, throttles, and train handling adjustments.  Last, there is Cervello.  Cervello is an Israeli startup. Cervello says it provides railways with “… comprehensive security solutions and in-depth visibility of the operational network and infrastructure.” With Cervello misleading commands are identified.  Moreover, Cervello produces a contextual view of the affected assets and operational impact.

Time to go but not before ending with this famous lyric from the O’Jays:  …” People from all over the world join hands start a love train, love train …”

Until next time,

Yogi Nelson

Uncategorized

Tornado Cash Legal Update: OFAC Sanctions Lifted

Yogi Nelson

Welcome to the Blockchain & AI Forum, where your questions are answered!  Today I answer Malik’s question: “what’s the latest news in the Tornado Cash legal case”?

What is Tornado Cash. Before jumping to the answer, first a moment to understand what is Tornado Cash.  Tornado Cash is a non-custodialprivacy protocol allowing permissionless shielded transactions on Ethereum and derivative networks. In plain English, Tornado Cash is an application that does not hold your crypto currency–you own it, you store it.  Tornado Cash facilitates transactions on the Ethereum blockchain without requiring permission while maintaining your privacy.  How does Tornado Cash maintains privacy?

Tornado Cash = Privacy.  Tornado Cash achieves anonymity by breaking the on-chain link between source and destination addresses through “anonymity pools”.  However, Tornado Cash does not preserve privacy by comingling assets; it uses zero knowledge cryptography.  What’s more, Tornado Cash relies on Ethereum—a decentralized protocol where transactions neither can be changed or altered.  Hence, nobody – including the original developers – can modify or inhibit the protocol or the transactions. What more information about how Tornado Cash works?  Click   How does Tornado Cash work? and Tips to remain anonymous.

What is the Office of Foreign Assets Control—OFAC.  OFAC is an office within the U.S. Treasury Department.  It claims to enforce economic and trade sanctions against specific countries, regimes, individuals, and entitles that pose threats to U.S. national security, foreign policy, or economy.  In other words, the enemy de jour of the U.S. government.  By the way, although OFAC was formally created in 1950, the use of sanctions by the U.S. government goes back to 1812! 

Tornado Cash Placed on OFAC Sanction List. August 8, 2022, OFAC placed Tornado Cash on the sanctions list.  According to the OFAC press release https://home.treasury.gov/news/press-releases/jy0916, “Tornado Cash, is a crypto currency mixer which has been used to launder more than $7 billion worth of virtual currency since its creation in 2019.”  However, OFAC’s statement is partially incorrect on the facts.  Tornado Cash is not a currency mixer nor is it property.  This error, deliberate or not, is materially important as we will see in a moment.  Let’s move on to what happened last week.

OFAC Removes Tornado Cash from the Sanction List.  Last week, the U.S. Treasury removed Tornado Cash from its sanctions list.  That’s a big deal. To understand what happened let’s take a moment to examine a recent court ruling that led to OFAC removing Tornado Cash from the sanctions list.

Last November, the 5th District Court of Appeals ruled that OFAC exceeded its authority when it put Tornado Cash on the sanctions list.  Essentially, the Court of Appeals reversed an earlier decision by a lower federal court.  The Court of Appeals stated the executive branch’s authority to “block ‘property’ in which a foreign ‘national’ or ‘person’ has an ‘interest’” did not apply in the case of Tornado Cash.  In other words, OFAC has no jurisdiction.  Why?  Because the use of immutable smart contracts — lines of autonomous code on the blockchain intended to preserve anonymity in transactions — do not qualify as property and OFAC can only sanction property.  And, smart contracts, despite their names, are not actually contracts. By the way, Tornado Cash’s legal fees were paid by Coinbase.  Wonderful to have friends with cash! 

No surprise—Tornado Cash value catapulted by 73% after the OFAC full scale retreat.  The story ends with OFAC deciding to “exercise its discretion” by dropping legal actions against Tornado Cash.  Lol! 

Until Next Time,

Yogi Nelson

Artificial Intelligence, Banking, Blockchains, cryptography, International Finance, Uncategorized

GENISUS Act: Implications for Stablecoin Issuers

Yogi Nelson

Namaste Yogis.   Welcome to the Blockchain & AI Forum, where your questions are answered!   As a bonus, a proverb is also included.  Today’s question comes from Latasha and she asks what is the GENISUS Act?

The GENISUS Act is a proposed federal law, introduced by Senator Hagerty of Tennessee–your home state.  To no surprise, GENISUS is an acronym: “Guiding and Establishing National Innovation for U.S. Stablecoins, 2025.” (Feds have the best acronyms!  Lol.)  Let’s review GENISUS Act section-by-section, beginning with definitions.

GENISUS defines 23 terms but none more important than Payment Stablecoin. According to GENISUS, a payment stablecoins is a digital asset that is designed to be used as a method of payment/settlement, and which the issuer is obligated to convert, redeem, or repurchased for a fixed amount of monetary value and represents it will maintain or creates the reasonable expectation that it will maintain, a stable value relative to the value of a fixed amount of monetary value, and is not a national currency or a security issued by an investment company.” We now move on to Sections 3 – 7.

Permitted Stablecoin Issuers:  If GENISUS becomes law only a permitted stablecoin issuer can issue stablecoins.  No free lancers permitted!  Don’t even consider it unless you enjoy living in a 6 x 9-foot prison cell with a dude name Buba!  Lol.

Requirements for Issuing Payment Stablecoins. There are a litany of requirements to issue a payment stablecoin.  Below are a few highlights of what issuers must do:

  1. Maintain reserves backing the issuer’s payment stablecoins outstanding on an at least 1 to 1 basis comprising of: U.S. Dollars, demand deposits held in U.S. banks, treasury bills, notes, and bonds of 93 days or less, repurchase agreements of seven days or less, money market funds, Central Bank reserve deposits.  In other words, liquid reserves that are 1-to-1. 
  2. Issuers must also publicly disclose their redemption policy, establish procedures for redemption, and publish monthly composition of the issuer’s reserve. Disclosure!
  3. Monthly compliance certificates from the issuers, CEO and CFO.

Limitations of Stablecoin Activities.  Stablecoin issuers are limited to the following activities:

  • Issue payment stablecoins
  • Redeem payment stablecoins
  • Manage related reserves
  • Provide custodial or safekeeping services for payment stablecoins
  • Other directly related work.

Stablecoin Regulators.  GENISUS does not establish a new federal stablecoin regulator.  Relief! Consequently, if a nationally chartered bank, e.g. Bank of America, issues a stablecoin the same federal banking regulator, Office of the Comptroller of the Currency, (OCC) that supervised Bank of America for safety and soundness, will be tasked with regulating the bank’s stablecoin operations.  Simple.  The same applies if the bank has a FDIC banking charter.  State chartered banks can issue stablecoins, provided their corresponding state banking regulators follows the GENISUS Act. Standard practice in banking.  What if a federal qualified nonbank wants to issue a stablecoin you ask?  OCC will be the regulator of those nonbank stablecoin issuers.  Let’s move on.

Application and Approvals.  From the date the stablecoin regulator deems the application complete, the applicant must be approved or denied within 120 days.  The catch is from the date the application is deemed complete.  A malicious regulator can string an applicant along with a constant request for additional information. 

If the regulator deems the application unsafe it can reject the application but it must explain with specificity, including all findings made by the regulator with respect to all identified material shortcomings in the application, including actionable recommendations on how the applicant could address the identified material shortcomings.  I find this last section unusual and troublesome.  Essentially GENISUS requires the regulator to explain to the applicant how to do their “homework”.  This is problematic.  Afterall, if an applicant is incapable of preparing a coherent application, doesn’t it portent an institution incapable of running the program effectively?  I think so.  Moreover, if the stablecoin issuer fails, will it blame the banking regulator for its failure given the issuer could reasonably claim it followed the regulator’s instruction? 

Rulemaking.  Did you know that when Congress passed a law it writes into the law a section titled rulemaking?  The purpose of this section is to authorized and require the executive branch to write the regulations necessary to implement the letter and spirit of the law.  In the case of GENISUS, Congress directed the various stablecoin regulators to issue the regulations within 180 days from the day GENISUS becomes law.  Regulators, you better step on the gas!

Time for me to make a genesis appearance at my next engagement but before I go, I leave you with this proverb from Turkey: “a hungry bear does not dance”.

Until next time,

Yogi Nelson