If mHC scales the way early benchmarks suggest, it could reshape how we think about model capacity, compute budgets and the ...

AI safety tests found to rely on 'obvious' trigger words; with easy rephrasing, models labeled 'reasonably safe' suddenly fail, with attacks succeeding up to 98% of the time. New corporate research ...

Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models ...

Large language models (LLMs), artificial intelligence (AI) systems that can process human language and generate texts in ...

In practice, the choice between small modular models and guardrail LLMs quickly becomes an operating model decision.

Tests on GPT and Claude found they ignored invented spells Fumbus and Driplo; training data can override new input, trust ...

With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale.

Exposed endpoints quietly expand attack surfaces across LLM infrastructure. Learn why endpoint privilege management is important to AI security.

Users running a quantized 7B model on a laptop expect 40+ tokens per second. A 30B MoE model on a high-end mobile device ...

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...

India’s sovereign AI push is taking shape through a layered stack spanning foundation models, public digital infrastructure, and applied AI systems.

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