As AI deployments scale and start to include packs of agents autonomously working in concert, organizations face a naturally amplified attack surface.

Large language models (LLMs) can suggest hypotheses, write code and draft papers, and AI agents are automating parts of the research process. Although this can accelerate science, it also makes it ...

The convergence of cloud computing and generative AI marks a defining turning point for enterprise security. Global spending ...

Nvidia researchers developed dynamic memory sparsification (DMS), a technique that compresses the KV cache in large language models by up to 8x while maintaining reasoning accuracy — and it can be ...

AI agents are powerful, but without a strong control plane and hard guardrails, they’re just one bad decision away from chaos.

Abstract: Large Language Models (LLMs) are widely adopted for automated code generation with promising results. Although prior research has assessed LLM-generated code and identified various quality ...

Anthropic’s Claude Opus 4.6 identified 500+ unknown high-severity flaws in open-source projects, advancing AI-driven vulnerability detection.

Discover Claude Opus 4.6 from Anthropic. We analyze the new agentic capabilities, the 1M token context window, and how it outperforms GPT-5.2 while addressing critical trade-offs in cost and latency.

On the Humanity’s Last Exam (HLE) benchmark, Kimi K2.5 scored 50.2% (with tools), surpassing OpenAI’s GPT-5.2 (xhigh) and ...

As LLM applications evolve, conversation flows become increasingly complex. Conversations may branch into multiple paths, run in parallel, or require summarization across different threads. Managing ...

The code (as well as the README) of Claude Code Mate is mainly vibe coded by Claude Code, with some adjustments and enhancements made by the author. 🤖 The models ...