At random, I chose glm-4.7-flash, from the Chinese AI startup Z.ai. Weighing in at 30 billion "parameters," or neural weights, GLM-4.7-flash would be a "small" large language model by today's ...

Although large language models (LLMs) have the potential to transform biomedical research, their ability to reason accurately across complex, data-rich domains remains unproven. To address this ...

Learning robust linguistic representations from text has long been a central challenge in natural language processing and language sciences. NLP systems ...

AI is an accelerator for Duolingo, enhancing its product and growth opportunities. Click here to read why I rate DUOL stock a ...

New research shows AI language models mirror how the human brain builds meaning over time while listening to natural speech.

SINGAPORE--(BUSINESS WIRE)--Z.ai released GLM-4.7 ahead of Christmas, marking the latest iteration of its GLM large language model family. As open-source models move beyond chat-based applications and ...

Large language models (LLMs) have become crucial tools in the pursuit of artificial general intelligence (AGI). However, as the user base expands and the frequency of usage increases, deploying these ...

Discover how to build a homemade rubber band-powered paper airplane in this easy and engaging tutorial. We’ll guide you step-by-step as you craft the frame with skewers, add aerodynamic paper wings, ...

Lin Tian receives funding from the Advanced Strategic Capabilities Accelerator (ASCA) and the Defence Innovation Network. Marian-Andrei Rizoiu receives funding from the Advanced Strategic Capabilities ...

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 ...

The proliferation of edge AI will require fundamental changes in language models and chip architectures to make inferencing and learning outside of AI data centers a viable option. The initial goal ...

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.