TechCrunch

Instead of fine-tuning an LLM as a first approach, try prompt architecting instead

Amid the generative AI eruption, innovation directors are bolstering their business’ IT department in pursuit of customized chatbots or LLMs. They want ChatGPT but with domain-specific information ...
VentureBeat

Uh-oh! Fine-tuning LLMs compromises their safety, study finds

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More As the rapid evolution of large language models (LLM) continues, ...
VentureBeat

Fine-tuning vs. in-context learning: New research guides better LLM customization for real ...

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 ...
Geeky Gadgets

Build and Fine-Tune LLMs in Record Time with LangGraph Studio

Have you ever found yourself frustrated by the slow pace of developing and fine-tuning language model assistants? What if there was a way to speed up this process while ensuring seamless collaboration ...
InfoWorld

The limitations of model fine-tuning and RAG

The hype and awe around generative AI have waned to some extent. “Generalist” large language models (LLMs) like GPT-4, Gemini (formerly Bard), and Llama whip up smart-sounding sentences, but their ...
Geeky Gadgets

How to fine tune AI models with no-code

Fine-tuning an AI model is like teaching a student who already knows a lot to become an expert in a specific subject. Instead of starting from scratch, we take a model that has learned from a vast ...
eWeek

How to Train an LLM: A Simple, User-Friendly Guide

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 ...