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.

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

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

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 ...

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

Generative AI might be impressive given of how large their scope is, but researchers said that they are not entirely reliable yet at the time.

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

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

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

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 ...

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