There is an all-out global race for AI dominance. The largest and most powerful companies in the world are investing billions in unprecedented computing power. The most powerful countries are ...

Support for AI among public safety professionals rose to 90% in 2024, with agencies rapidly adopting large language models (LLMs) to streamline operations and improve engagement. LLMs are being used ...

The U.S. military is working on ways to get the power of cloud-based, big-data AI in tools that can run on local computers, draw upon more focused data sets, and remain safe from spying eyes, ...

Editor’s note (September 9th): This article has been updated. WHEN TECH folk talk about the lacklustre progress of large language models (LLMs), they often draw an analogy with smartphones. The early ...

Are tech companies on the verge of creating thinking machines with their tremendous AI models, as top executives claim they are? Not according to one expert. We humans tend to associate language with ...

Generative AI, especially large language models (LLMs), present exciting and unprecedented opportunities and complex challenges for academic research and scholarship. As the different versions of LLMs ...

Gary Marcus, professor emeritus at NYU, explains the differences between large language models and "world models" — and why he thinks the latter are key to achieving artificial general intelligence.

The main problem with big tech’s experiment with artificial intelligence (AI) is not that it could take over humanity. It’s that large language models (LLMs) like Open AI’s ChatGPT, Google’s Gemini ...

There’s a paradox at the heart of modern AI: The kinds of sophisticated models that companies are using to get real work done and reduce head count aren’t the ones getting all the attention.

Over the past year, the conversation around artificial intelligence (AI) has shifted. After a period of rapid progress, many teams deploying large language models (LLMs) are encountering familiar ...