Enter small language models (SLMs). These language models are trained on specific data sets, rather than the entirety of ...

LexisNexis fine-tuned Mistral models to build its Protege AI assistant, relying on distilled and small models for its AI platform.

Yann LeCun's argues that there are limitations of chain-of-thought (CoT) prompting and large language model (LLM) reasoning.

Together, these open-source contenders signal a shift in the LLM landscape—one with serious implications for enterprises ...

A new framework called METASCALE enables large language models (LLMs) to dynamically adapt their reasoning mode at inference time. This framework addresses one of LLMs’ shortcomings, which is using ...

Security was top of mind when Dr. Marcus Botacin, assistant professor in the Department of Computer Science and Engineering, ...

But AMD’s GPU roadmap is catching up to NVIDIA. Its M350 will match Blackwell 2H/2025. And its M400 will match NVIDIA’s ...

While small model fine-tuning proved efficient but limited in capability, LoRA adaptation of medium-sized models showed promise as a balanced approach for organizations with constrained resources ...

Companies with a high volume of proprietary data are racing to build small language models ... Some are building them over existing models, also known as LLM distillation. Through distillation ...

“H2O Enterprise LLM Studio makes it simple for businesses to build domain-specific models without the complexity.” As organizations scale AI while preserving security, control, and ...

"Distilling and fine-tuning AI models are transforming enterprise workflows, making operations smarter and more efficient," said Sri Ambati, CEO and Founder of H2O.ai. "H2O Enterprise LLM Studio ...