Google's TabFM skips per-dataset training and still predicts on tables it's never seen

Google's TabFM skips per-dataset training and still predicts on unseen tables, matching tuned baselines and cutting pipeline ...

ACRouter picks the smartest AI model per task, beating Opus-only setups by 2.6x on cost

ACRouter, a new open-source AI router, learns from execution feedback to pick the best coding model per task, cutting costs 2 ...
Tech Xplore

Easier parameter tuning for prediction using echo state networks

Neural networks, a fascinating technology inspired by the human brain, form the basis of artificial intelligence. These ...
IEEE Spectrum on MSNOpinion

How I turned AI to the dark side

It only took a little prompting to hijack the biggest AI models ...
Unite.AI

Thinking Machines Lab Unveils Inkling, Its First Open-Weights Multimodal AI Model

Thinking Machines Lab has released Inkling, its first general-purpose artificial intelligence model, giving developers access ...
Memeburn

What Is Agentic AI? The Definitive Guide to Autonomous Systems

Discover what agentic AI is and how AI agents work. Uncover the types of agentic AI systems, their enterprise use cases, ...
InfoQ

How Datadog Used Claude and Cursor for Test-Driven Production Migration

In a recent article, Datadog engineer Arnold Wakim shared what worked, what didn't, and the lessons they learned while ...
Major League Baseball

Player Empirical Comparison and Optimization Test Algorithm (PECOTA)

Also a "backronym" for former Major Leaguer Bill Pecota, PECOTA is Baseball Prospectus' system for projecting player performance. The acronym stands for "Player Empirical Comparison and Optimization ...