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, ...
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 ...

MIT's new fine-tuning method lets LLMs learn new skills without losing old ones

MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, continuously learning agent.
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 ...
SiliconANGLE

OpenAI rolls out new AI optimization features to its fine-tuning API

OpenAI today debuted a set of new tools that will make it easier to optimize its large language models for specific tasks. Most of the additions are rolling out for the company’s fine-tuning ...
Geeky Gadgets

Easily Fine-Tune AI Models Like a Pro with Google Tunix

Have you ever wondered how to transform a general-purpose language model into a finely tuned expert tailored to your specific needs? The process might sound daunting, but with the right tools, it ...
Semiconductor Engineering

Largest High-Quality Verilog Dataset for LLM Fine-Tuning (Univ. of Florida)

A new technical paper titled “VerilogDB: The Largest, Highest-Quality Dataset with a Preprocessing Framework for LLM-based RTL Generation” was published by researchers at the University of Florida.
Geeky Gadgets

How to Fine-Tune Custom AI Models with Advanced Quality Data

What separates a mediocre large language model (LLM) from a truly exceptional one? The answer often lies not in the model itself, but in the quality of the data used to fine-tune it. Imagine training ...