After months of testing local LLMs, I found that productivity depends on tools, not just models.

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 ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

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 ...

In the course of human endeavors, it has become clear that humans have the capacity to accelerate learning by taking foundational concepts initially proposed by some of humanity’s greatest minds and ...

In the world of artificial intelligence, the ability to build Large Language Model (LLM) and Retrieval Augmented Generation (RAG) pipelines using open-source models is a skill that is increasingly in ...

AI remains top of mind for many business and industry leaders, and the sector shows no signs of slowing down regarding investment and funding. Most recently, the generative AI startup Writer announced ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...