The top stories in the fields you follow, at 08:00 your time.
Kimi K3.1 Pro ranked fourth among 215 AI models on an independent intelligence index while Moonshot AI deliberately removed offensive cyberattack training data before releasing open weights, dropping its cybersecurity benchmark from 90.5% to 81.0% -- a first for any Beijing-based AI lab. Open
Reddit’s r/opensource is banning AI-built projects, but its sweeping new rules are drawing criticism from developers over Linux kernel code and solo contributors.
Read moreAnthropic AEGIS Act, a draft federal AI safety bill circulated secretly on Capitol Hill, would let AI labs pay their own safety auditors and preempt California's SB 53 -- the state law Anthropic publicly championed just thirteen months ago.
Read moreElon Musk's artificial intelligence company xAI has released the first episode of an AI-generated video series adapting Homer's "The Odyssey," fulfilling a...
Read moreMicrosoft Power BI remains a cornerstone of enterprise analytics. However, Data Analysis Expressions...
Read moreSmart contracts, programs that automatically move money on blockchains, cannot be changed once released, so a single bug can lead to irreversible theft. Existing tools mostly flag whole programs as risky without saying where or why. Researchers from JAIST have developed an AI framework that pinpoints the specific function containing a flaw and generates a plain-language explanation of the problem and its fix, outperforming existing methods on real-world contracts.
Read moreIn the fast-evolving landscape of digital assets, the stark warning that "Your Token is worthless" has emerged as a critical reality for countless crypto holders, underscoring the pervasive risks of unvetted blockchain projects, pump-and-dump schemes, and utility-less digital tokens flooding the decentralized finance (DeFi) and Web3 spaces. This blunt truth highlights that a cryptocurrency or token holds no inherent value without robust real-world utility, a transparent development roadmap, a…
Read moreFlint is Recursive’s mixture-of-experts language model for coding agents, with 39.8 billion total parameters and approximately 2.5 billion active per token. It is designed to investigate codebases, fix bugs, implement features, and write tests.
