A marriage of formal methods and LLMs seeks to harness the strengths of both.

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 ...

Judged as an artwork, GPT-4’s unicorn won’t win any prizes. The assortment of geometric shapes produced by the deep-learning algorithm only loosely captures the appearance of the majestic mythical ...

Engineers at the University of California San Diego have developed a new way to train artificial intelligence systems to ...

Call it a reasoning renaissance. In the wake of the release of OpenAI’s o1, a so-called reasoning model, there’s been an explosion of reasoning models from rival AI labs. In early November, DeepSeek, ...

We now live in the era of reasoning AI models where the large language model (LLM) gives users a rundown of its thought processes while answering queries. This gives an illusion of transparency ...

Forbes contributors publish independent expert analyses and insights. I write about the economics of AI. What looks like intelligence in AI models may just be memorization. A closer look at benchmarks ...

AI labs like OpenAI claim that their so-called “reasoning” AI models, which can “think” through problems step by step, are more capable than their non-reasoning counterparts in specific domains, such ...

Large language models are a class of AI algorithm that relies on a high number computational nodes and an equally large number of connections among them. They can be trained to perform a variety of ...

Researchers have identified the key brain regions that are essential for logical thinking and problem solving. A team of researchers at UCL and UCLH have identified the key brain regions that are ...

There are many different kinds of reasoning. Some reasoning is by simple association. If you see very dark clouds coming your way, accompanied by lightning and thunder, you will probably conclude that ...