NEWS IN BRIEF: AI/ML FRESH UPDATES

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Cutting Emissions: The Power of Eco-Driving

MIT researchers found that eco-driving measures can reduce CO2 emissions at signalized intersections by 11-22% without affecting traffic flow or safety. By using deep reinforcement learning, they showed that even 10% of vehicles using eco-driving could lead to a 25-50% reduction in emissions.

Mastering k-Nearest Neighbors Regression in JavaScript

Article summary: The August 2025 Microsoft Visual Studio Magazine article discusses implementing k-Nearest Neighbors regression using JavaScript, a simple yet highly interpretable technique with a demo showcasing its accuracy. The technique involves finding the k-closest items to an input vector to predict a numeric value, making it a valuable tool in machine learning.

ChatGPT Upgrade: Close, but Not Quite Human

OpenAI's GPT-5 model shows improved coding and writing abilities, but falls short in 'continuous learning'. The startup aims for AGI with its latest upgrade to ChatGPT, acknowledging there are still missing elements in replicating human tasks.

AI Regulation Debate: Labor vs. Coalition

PM prioritizes protecting arts copyright, while government seeks productivity gains from AI. Debate over AI regulation intensifies amid pressure from Labor ministers and warnings against squandering AI benefits.

Revolutionizing Account Planning with Amazon Bedrock

AWS sales teams use account plans to understand customer goals and challenges, leading to the launch of Account Plan Pulse, an AI tool that improved plan quality by 37% and reduced review time by 52%. Built with Amazon Bedrock, Pulse streamlines the account planning process, enhancing collaboration and customer support for better sales outcomes.

AI Vegans: The Future of Plant-Based Living

Handwriting is disappearing due to overreliance on keyboards, raising concerns about AI's impact on our brains. Mark Zuckerberg claims not using AI-powered smart glasses will put you at a "significant cognitive disadvantage."

Ethical AI in Payments

Responsible AI in payments industry is not just a concept but a dynamic process. Implementing responsible AI involves a holistic approach, bias testing, accountability, and cross-functional oversight to ensure transparency and trustworthiness in financial decision-making.