Recently, the team led by Professor Wang Mengdi at Princeton University proposed a “Trajectory-Aware RL” framework—TraceRL in ...

For AI models, knowing what to remember might be as important as knowing what to forget. Welcome to the era of “sleeptime compute.” ...

Small Language Models (SLMs) are redefining enterprise AI by offering faster, more efficient, and cost-effective solutions ...

Choosing the right large language model for a project can be tricky. That's why Ancestry takes a more-the-merrier approach ...

The rStar2-Agent framework boosts a 14B model to outperform a 671B giant, offering a path to state-of-the-art AI without ...

OpenAI finds a key problem in how large language models work. These models often give wrong information confidently. The ...

This year the world’s four largest tech firms will spend $344 billion on AI, mostly on data centers used to train and run ...

Researchers from Nanyang Technological University, Wuhan University, and ByteDance have proposed a novel paradigm Text4Seg++, ...

Recent years have witnessed AI evolve beyond single-mode systems to generate multiple streams of information for multiple ...

By using this method of attention, SpikingBrain can be 25 to 100 times faster than normal AI models, they say. The new AI ...

A whitepaper by PNY, A Beginner’s Guide to Large Language Models, explains what makes LLMs so groundbreaking and how ...

The vision of Ambient AI in smart homes promises an intelligent system that understands and adapts to its occupants. Despite ...