VentureBeat

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

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 ...
Redmond Magazine

Microsoft Build: Copilot Tuning and Model Context Protocol Expand AI Agent Development

At this year's Build conference, Microsoft unveiled a major expansion of its agent-based AI platform, highlighting new tools to securely build, customize and orchestrate intelligent agents across ...
InfoWorld

12 model-level deep cuts to slash AI training costs

Stop throwing money at GPUs for unoptimized models; using smart shortcuts like fine-tuning and quantization can slash your ...
ZDNet

OpenAI's budget GPT-4o mini model is now cheaper to fine-tune, too

A popular strategy for engaging with generative AI chatbots is to start with a well-crafted prompt. In fact, prompt engineering is an emerging skill for those pursuing career advancement in this age ...
Neowin

Microsoft announces major update to model fine-tuning in Azure AI Foundry

Microsoft has announced significant enhancements to model fine-tuning within Azure AI Foundry, including upcoming support for Reinforcement Fine-Tuning (RFT). Microsoft Azure AI Foundry already ...
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 ...
TechCrunch

OpenAI brings fine-tuning to GPT-3.5 Turbo

OpenAI customers can now bring custom data to the lightweight version of GPT-3.5, GPT-3.5 Turbo — making it easier to improve the text-generating AI model’s reliability while building in specific ...