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 ...
In the SDLC, there should be no shortcuts. Developers must view AI as a collaborator to be monitored, rather than an autonomous entity to be unleashed.
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 ...
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