Running large language models at the enterprise level often means sending prompts and data to a managed service in the cloud, much like with consumer use cases. This has worked in the past because ...

Large language models by themselves are less than meets the eye; the moniker “stochastic parrots” isn’t wrong. Connect LLMs to specific data for retrieval-augmented generation (RAG) and you get a more ...

DSPy (short for Declarative Self-improving Python) is an open-source Python framework created by researchers at Stanford University. Described as a toolkit for “programming, rather than prompting, ...

Oct. 12, 2024 — A research team led by the University of Maryland has been nominated for the Association for Computing Machinery’s Gordon Bell Prize. The team is being recognized for developing a ...

A new study by Shanghai Jiao Tong University and SII Generative AI Research Lab (GAIR) shows that training large language models (LLMs) for complex, autonomous tasks does not require massive datasets.

Researchers at the University of Science and Technology of China have developed a new reinforcement learning (RL) framework that helps train large language models (LLMs) for complex agentic tasks ...

Youtuber Ominous Industries provides a training video for setting up your Jetson Nano, installing Pytorch and setting up your own (likely open source LLM). This takes ...

Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of ...