Two popular approaches for customizing large language models (LLMs) for downstream tasks are fine-tuning and in-context learning (ICL). In a recent study, researchers at Google DeepMind and Stanford ...

The offline pipeline's primary objective is regression testing — identifying failures, drift, and latency before production. Deploying an enterprise LLM feature without a gating offline evaluation ...

Small Language Models or SLMs are on their way toward being on your smartphones and other local devices, be aware of what's coming. In today’s column, I take a close look at the rising availability ...

The explosive adoption of large language models (LLMs) within all types and sizes of businesses is well-documented and is only accelerating as corporations build their own LLMs based on local LLMs ...

Model Context Protocol enables a Large Language Model (LLM) to do a lot more than just answer questions. Acting as a translator between the model and the digital world, it can abstract data from a ...

Patrick Richards of Much Shelist PC examines shifts in how business is conducted in light of how clients integrate AI tools ...