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.

MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, continuously learning agent.

AI agents are a risky business. Even when stuck inside the chatbox window, LLMs will make mistakes and behave badly. Once ...

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 ...

Abstract: With the advent of generative LLMs and their advanced code generation capabilities, some people already envision the end of traditional software engineering, as LLMs may be able to produce ...