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 ...

I asked my local LLM to build Pi extensions, and now my coding harness evolves on its own ...

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 ...

NLP and LLM teams often grow their training corpuses to improve model performance but they still do not always obtain p ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more Groq now allows you to make lightning fast ...

Large language models often lie and cheat. We can’t stop that—but we can make them own up. OpenAI is testing another new way to expose the complicated processes at work inside large language models.

Business leaders have been under pressure to find the best way to incorporate generative AI into their strategies to yield the best results for their organization and stakeholders. According to ...