This article introduces practical methods for evaluating AI agents operating in real-world environments. It explains how to combine benchmarks, automated evaluation pipelines, and human review to ...

A Combination of Techniques Leads to Improved Friction Stir Welding The NESC developed several innovative tools and ...

Dozens of Telegram channels reviewed by WIRED include job listings for “AI face models.” The (mostly) women who land these ...

More seriously, lawyers and judges have suffered reputational damage through citations of AI-hallucinated cases that do not ...

Elon Musk unveils “Macrohard,” a Tesla and xAI AI system designed to perform complex computer tasks and potentially replicate the functions of software companies.

Overview: Automated Python EDA scripts generate visual reports and dataset summaries quicklyLibraries such as YData Profiling ...

Researchers show AI can learn a rare programming language by correcting its own errors, improving its coding success from 39% to 96%.

There's a lot more to a model than just benchmarks.

Savvy developers are realizing the advantages of writing explicit, consistent, well-documented code that agents easily understand. Boring makes agents more reliable.

UK Lords urged the government to reject weaker AI copyright rules, saying creators should not be sacrificed for speculative ...

Alarm bells are ringing in the open source community, but commercial licensing is also at risk Earlier this week, Dan ...

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.