Not bad for limited hardware ...

With LLMs increasingly working multimodally, there are exciting developments for more performance and leaner sizes.

The generative AI boom has driven the cost of memory into the stratosphere, and Google is a key part of that trend. So it’s only fitting that Google should offer some less RAM-hungry local AI models.

Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context window limits. MeMo, a ...

Stanford University’s recent research, conducted in collaboration with Tsinghua University, has revealed a surprising shift in how we evaluate the performance of large language models (LLMs). Rather ...

As part of its move to an IP workflow, Italian broadcaster Rai has signed a three-year framework agreement with Matrox Video to use its Matrox ConvertIP Series of encoders/decoders and converters.

The challenge of wrangling a deep learning model is often understanding why it does what it does: Whether it’s xAI’s repeated struggle sessions to fine-tune Grok’s odd politics, ChatGPT’s struggles ...

To build a self-supervised magnetic resonance imaging (MRI) foundation model from routine clinical scans and to test whether it can support key glioma-related applications, including post-therapy ...

Large-language models (LLMs) have taken the world by storm, but they’re only one type of underlying AI model. An under-the-radar company, Fundamental, is set to bring a new type of enterprise AI model ...