A recent study questions if large language models (LLMs) truly form coherent world models, despite their accurate outputs in complex tasks like generating directions or playing games.

The first step in leveraging LLMs is understanding their capabilities and how they can impact your organization.

Securing large language models (LLMs) presents unique challenges due to their complexity, scale, and data interactions.

The rise of large language models (LLMs) has sparked questions about their computational abilities compared to traditional models. While recent research has shown that LLMs can simulate a universal ...

Running your favorite AI chatbots requires updated hardware—and this means throwing functional equipment in the trash. It's ...

Because such language is implicit and context-dependent, recognizing manipulative language can be very challenging for large ...

MIT this week showcased a new model for training robots. Rather than the standard set of focused data used to teach robots ...

Leading AI companies such as OpenAI, Google and Meta rely more on content from premium publishers to train their large ...

Large language models (LLMs) have demonstrated impressive capabilities in multilingual machine translation (MT). Research ...

LM Studio is a software that allows users to run large language models (LLMs) on personal devices, using GPU offloading to ...

OpenAI has released a new benchmark dubbed "SimpleQA" that's designed to measure the accuracy of the output of artificial ...

LLMs are the talk of the town, but businesses will find that small models enable AI adoption for business use cases at a ...