Fine-tuning of Large Language Models allows customizations of AI models for specific tasks and data. While Fine-tuning used to require a lot of compute, technologies like InstructLab, QLoRA and lam...

watsonx is IBM’s AI & data platform that’s built for business. It supports the complete AI lifecycle including Large Language Models, developer tools, governance and more. This post describes a...

DSPy is a Python-based open-source framework from Stanford university. Developers can write code to build compound systems, for example agents. DSPy is the framework for programming—rather than...

Watsonx Assistant and watsonx Orchestrate are great tools for low-code and no-code developers to build conversational experiences. Additionally, they provide extensibility options for pro-code deve...

Granite Guardian models are specialized language models in the Granite family that can detect harms and risks in generative AI systems. This post describes how to get started using them. Recently ...

Docling is a popular open-source project contributed by IBM. It supports easy and fast parsing of PDFs and several other file types including images. This post gives a quick introduction to Docling...

The Bee Agent Platform is an open-source project from IBM Research to build agentic applications with TypeScript and Python. This post summarizes how to build Python tools. The Bee Agent Platform ...

The first open-source Reasoning Large Language Model is now available. This post describes briefly what reasoning models are and how to run them locally. Model-based Reasoning has been used for qu...

Red Hat Enterprise Linux AI (RHEL AI) comes with InstructLab to fine tune Large Language Models. This post describes how to set it up on IBM Cloud. Red Hat Enterprise Linux AI is a foundation m...

A public preview of watsonx.ai Flows Engine is now available. This post shows an example how to build a simple agent which accesses LLMs from watsonx.ai and pre-built tools. Build performant ge...