As large language models (LLMs) continue to grow in size and complexity, the time it takes to load them from storage to accelerator memory for inference can become a significant bottleneck. This “cold start” problem isn’t just a minor delay — it’s a critical barrier to building resilient, scalable, and cost-effective AI services. Every minute …
Read more “Accelerate model downloads on GKE with NVIDIA Run:ai Model Streamer”
OpenAI researchers have introduced a novel method that acts as a “truth serum” for large language models (LLMs), compelling them to self-report their own misbehavior, hallucinations and policy violations. This technique, “confessions,” addresses a growing concern in enterprise AI: Models can be dishonest, overstating their confidence or covering up the shortcuts they take to arrive …
On December 4, WIRED sat down with some of the biggest names in tech, culture, business, and science for a day full of in-depth interviews.
Watching 3D movies and TV shows is a fun and exciting experience, where images leap out of the screen. To get this effect, you usually have to wear a special pair of glasses. But that could soon be a thing of the past as scientists have developed a new display system that delivers a realistic …
Read more “Scientists develop a glasses-free 3D system with a little help from AI”
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Large language models generate text, not structured data.
Automated interpretability aims to translate large language model (LLM) features into human understandable descriptions. However, these natural language feature descriptions are often vague, inconsistent, and require manual relabeling. In response, we introduce semantic regexes, structured language descriptions of LLM features. By combining primitives that capture linguistic and semantic feature patterns with modifiers for contextualization, composition, …
Read more “Semantic Regexes: Auto-Interpreting LLM Features with a Structured Language”
Just a few short weeks ago, Google debuted its Gemini 3 model, claiming it scored a leadership position in multiple AI benchmarks. But the challenge with vendor-provided benchmarks is that they are just that — vendor-provided. A new vendor-neutral evaluation from Prolific, however, puts Gemini 3 at the top of the leaderboard. This isn’t on …
BMW’s first car on its new EV platform has finally arrived. But will a big range, thumping charging tech, and a new driving brain that aims to deliver the ultimate ride be enough to beat China?
Even networks long considered “untrainable” can learn effectively with a bit of a helping hand. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have shown that a brief period of alignment between neural networks, a method they call guidance, can dramatically improve the performance of architectures previously thought unsuitable for modern tasks.