Training standard AI models against a diverse pool of opponents — rather than building complex hardcoded coordination rules — ...

Instead of one central AI system doing everything, the model emerging here is many bounded agents operating across teams, channels and tasks.

Qdrant's $50M Series B and version 1.17 release make the case that agentic AI didn't simplify vector search — it scaled the ...

Some roads never relax, and safety can suffer. Commuter corridors funnel workers toward bridges and major employers, which ...

When a worker thread completes a task, it doesn't return a sprawling transcript of every failed attempt; it returns a compressed summary of the successful tool calls and conclusions.

Drug discovery has traditionally been a reductive process—narrowing down, filtering out, and optimizing within established ...

Perplexity announced Computer for Enterprise at its Ask 2026 developer conference, launching a multi-model AI agent with ...

Microsoft is launching Agent 365 and the new Microsoft 365 Enterprise E7 on May 1 to govern and secure enterprise AI ...

FriendliAI — founded by the researcher behind continuous batching, the technique at the core of vLLM — is launching InferenceSense, a platform that fills idle neocloud GPU capacity with paid AI ...

To act autonomously and effectively, AI agents need optimized, AI-ready processes and the process data and operational ...

For agents, the value is clearer still: structured JSON output, reusable commands and built-in skills that let models ...

But that instinct can mislead us. AI feels like a bubble because we’re forcing something genuinely discontinuous into a ...