Fine-tuning large language models in artificial intelligence is a computationally intensive process that typically requires significant resources, especially in terms of GPU power. However, by ...

Fine-tuning large language models (LLMs) might sound like a task reserved for tech wizards with endless resources, but the reality is far more approachable—and surprisingly exciting. If you’ve ever ...

A small team of AI researchers from Carnegie Mellon University, Stanford University, Harvard University and Princeton University, all in the U.S., has found that if large language models are ...

Postdoctorate Viet Anh Trinh led a project within Strand 1 to develop a novel neural network architecture that can both recognize and generate speech. He has since moved on from iSAT to a role at ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I examine the recently revealed feature ...

Over the past year, enterprise adoption of generative AI has shifted from small experiments with large language models to ...

Large language models (LLMs) have demonstrated remarkable capabilities in natural language processing (NLP) tasks, yet they face significant challenges when applied to educational contexts. This paper ...

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more Microsoft is a major backer and partner of ...

As recently as 2022, just building a large language model (LLM) was a feat at the cutting edge of artificial-intelligence (AI) engineering. Three years on, experts are harder to impress. To really ...