A library of snippets
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Westpac saw a 46 percent productivity gain, with no reduction in code quality, from software engineers that were aided by generative AI compared to a control group that performed the same tasks exclusively by hand, in a recent in-house experiment.
From Westpac sees 46 percent productivity gain from AI coding experiment – Finance – Software – iTnews:
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The issue of what exactly these things are, in legal terms, led the Law Commission to recommend legislation to define them. They are not physical “things in possession” such as cars and nor are they “things in action” like stocks and bonds. They are what I would call “things in wallets” but the Law Commission uses the term “third category things”.
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To make an ML model learn the wrong thing, adversaries take aim at the model’s training data, any foundational models, or both. Adversaries exploit this class of vulnerabilities to influence models using methods, such as data and parameter manipulation, which practitioners term poisoning. Poisoning attacks cause a model to incorrectly learn something that the adversary can exploit at a future time. For example, an attacker might use data poisoning techniques to corrupt a supply chain for a model designed to classify traffic signs. The attacker could exploit threats to the data by inserting triggers into training data that can influence future model behavior so that the model misclassifies a stop sign as a speed limit sign when the trigger is present
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Explainable AI is one of the key requirements for implementing responsible AI, a methodology for the large-scale implementation of AI methods in real organizations with fairness, model explainability and accountability.³ To help adopt AI responsibly, organizations need to embed ethical principles into AI applications and processes by building AI systems based on trust and transparency.
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A bank customer was left stunned when a teller told her they did not have any cash within the branch to meet her withdrawal request, prompting her to close her account on the spot.
Taryn Comptyn had gone to her bank to withdraw $3,500 to pay for renovations
From ANZ Australia no longer keeping cash at some branches | Daily Mail Online.
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Soon, though, the web might consist not only of what was there in the pre-AI era, but all the stuff created by current and future chatbots. Which raises the intriguing possibility of an online world populated by bots inhaling the textual exhaust of their mechanical peers, and a consequent spiral into the infinite recursion that programmers call “stack overflow”!
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Boston Consulting Group reports that asset tokenization can generate annual savings of $20 billion in just the global clearing and settlement costs. By 2030, it could unlock a $16 trillion global market for tokenized illiquid assets, which would account for less than two percent of the total notional value of public and private assets.
From Asset Tokenization – A Trillion Dollar Market Opportunity.
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Non-Blockchain Tokenization is used to safeguard data. It substitutes sensitive data with random tokens that hold no inherent meaning or exploitable value. These tokens act as references or identifiers, facilitating the mapping back to the original sensitive data using a tokenization system. The method is widely used to secure diverse types of sensitive data, including financial transactions, health records, criminal histories, vehicle driver details, loan documents, stock trading, voter registration, and more.
Blockchain Tokenization, on the other hand, converts assets into digital token securities, which act as a proxy for whole or fractional ownership of the underlying asset. Blockchain, smart contracts, and token securities are pivotal in enabling illiquid asset fractionalization by programmatically enforcing the required rules and restrictions, allowing for enhanced mobility of asset ownership, efficient payments and distributions, and a range of financial benefits across the lifecycle of the transactions.
From Asset Tokenization – A Trillion Dollar Market Opportunity.
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Proxying and recording an asset as a programmable token on a blockchain enhances asset ownership (whole or fractional) mobility, empowers instant and atomic settlement, provides real-time on-chain visibility of the asset lifecycle, and enables process automation. Leading banks and financial institutions are embracing asset tokenization as a game-changing blockchain technology innovation, driving its integration into the financial market infrastructure. Significant cost savings can be achieved by enhancing the back-office, middle-office infrastructure, transaction settlement processes, data management systems, and other areas of the operational value chain. Boston Consulting Group reports that asset tokenization can generate annual savings of $20 billion in just the global clearing and settlement costs. By 2030, it could unlock a $16 trillion global market for tokenized illiquid assets, which would account for less than two percent of the total notional value of public and private assets.
From Asset Tokenization – A Trillion Dollar Market Opportunity.
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To support reciprocal trust relationships, defensive tooling and techniques should be developed to support users from accidentally revealing personas in regions they don’t wish to expose them.
With personas driven by wallet-based credentials, it would behove wallet vendors to offer simple user experiences in the selection of credentials during presentation, and separation of credentials associated with a given aspect of an individual’s life.
With multiple credentials that indicate my name, I don’t want to be at risk of sharing a gaming avatar’s name from a gaming persona in place of my actual name from a work persona when queried for it in a professional setting.From The Presentation of Self on Everyday Internet – Persona Grata.
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