Dataiku unveils Agent Hub, a centralized platform that lets employees discover and build AI agents from approved templates while IT departments maintain strict control over data access, models, and deployment across the enterprise.
Google enhances its Jules AI coding assistant with new command line tools and API support, while Nvidia introduces a revolutionary 4-bit training format that cuts AI training costs, and MIT researchers use generative AI to dramatically accelerate antibiotic discovery from years to much shorter timeframes.
AstraZeneca strikes a massive $555 million partnership with Algen Biotechnologies, combining cutting-edge AI platform 'AlgenBrain' with CRISPR gene technology to revolutionize drug discovery for chronic inflammatory diseases and unlock next-generation immunology therapies.
Google DeepMind launches CodeMender, an AI agent that autonomously detects and fixes security vulnerabilities in software, having already submitted 72 security patches across 4.5 million lines of open-source code including fixes for exploits used in major attacks.
Gate22 launches an open-source gateway that lets teams control and audit which tools AI agents can access across platforms like Cursor, featuring function-level permissions, credential management, and unified configuration bundles.
Google DeepMind launches CodeMender, an AI agent that automatically detects and fixes software security flaws, successfully delivering 72 patches to open source projects within six months while handling codebases up to 4.5 million lines.
ElevenLabs unveils Agent Workflows platform featuring specialized subagents with individual system prompts and knowledge bases, visual conversation flow design, human operator transfers, and optimized performance through different AI models for various tasks.
Revolutionary AI research systems now deploy orchestrator agents that coordinate multiple subagents to scan vast information sources like Google Drive and Notion, delivering comprehensive answers that surpass traditional keyword searches by synthesizing data from multiple channels before providing users with thorough, well-researched responses.
AI agents powered by large language models now assist scientists with research tasks like data curation and literature reviews, while new collaborative systems mimic medical teams to analyze drug trials and identify unexpected therapeutic effects, though current technology still requires human oversight due to reliability limitations.
AI agent successfully builds complex Python cache system through innovative self-correcting feedback loop that automatically writes code, tests it, and fixes errors, but reveals current limitations including skipping critical features like thread safety due to token constraints.