Hardware choices and training time impact energy, water, and carbon footprints during AI model training. Longer training time can decrease energy efficiency by 0.03% per hour, highlighting environmental costs of AI adoption.
New technology FaceAge.Age uses selfies to scientifically assess aging, promising a simple way to track changes over time. This innovative approach could revolutionize how we monitor our aging process.
Amazon EKS and Bedrock create scalable, secure RAG solutions for generative AI apps on AWS, leveraging additional data for accurate responses. Using EKS managed node groups, the solution automates resource provisioning and scales efficiently based on demand, enhancing performance and security.
AI training data may not represent Australia's diversity, posing discrimination risks in job interviews. Videos of faulty AI recruiters on TikTok highlight the issue.
MIT's Shaping the Future of Work Initiative evolves into the James M. and Cathleen D. Stone Center on Inequality, focusing on wealth distribution and technology's impact on the workforce. Led by prominent scholars, the center aims to advance research, inform policymakers, and engage the public on critical economic issues.
Big tech companies exploit human language for AI gain, pushing for trust in products as collaborative tools. Author questions portrayal of book with ChatGPT assistance, highlighting caution against using large language models for self-expression.
Model Context Protocol (MCP) is essential for integrating custom tools with Claude Desktop, providing a centralized way to manage tools across multiple interfaces. Compared to traditional methods like RAG, MCP allows for seamless integration without the need to build a custom server from scratch.
Tech CEOs aim to automate all labor with AI, capturing workers' salaries. Founder of Fairly Trained warns of elite's determination to replace human workers.
Recent large language models like OpenAI's o1/o3 and DeepSeek's R1 use chain-of-thought (CoT) for deep thinking. A new approach, PENCIL, challenges CoT by allowing models to erase thoughts, improving reasoning efficiency.
Article explores data leakage in Data Science, emphasizing examples over theory. Identifies types of leakage like Target Leakage and Train-Test Split Contamination, providing fixes for each.
Training linear SVR is challenging due to its non-calculus differentiable loss function, leading to the exploration of PSO over evolutionary algorithms. Using PSO for linear SVR training yielded superior results, showcasing the importance of parameter tuning for optimizing predictive models.
House of Lords backs amendment to data bill, forcing AI companies to disclose use of copyrighted material, against government wishes. Peers demand transparency in AI models, a blow to government's plans for copyright protection.
Shira Perlmutter, head of US copyright office, fired after AI fair use report. Librarian of Congress also dismissed.
Automated workflows often need human approval; a scalable manual approval system was built using AWS Step Functions, Slack, Lambda, and SNS. The solution includes a state machine with a pause for human decision and a Slack message for approval.
WebAssembly extends browser capabilities beyond HTML, CSS, and JavaScript. Pyodide library enables running Python code in the browser, benefiting data scientists and ML professionals.