IBM open sources Granite models, integrates watsonx.governance with AWS SageMaker

IBM has open sourced its portfolio of Granite large language models under Apache 2.0 licenses on Hugging Face and GitHub, outlined a bevy of AI ecosystem partnerships and launched a series of assistants and watsonx powered tools. The upshot is that IBM is looking to do for foundational models what open source did for software development.

The announcements, made at IBM’s Think 2024 conference, land as the company has made a bevy of partnerships that put it in the middle of the artificial intelligence mix either as a technology provider or services provider. For instance, IBM and Palo Alto Networks outlined a broad partnership that combines Palo Alto Networks’ security platform with IBM’s models and consulting. IBM Consulting also partnered with SAP and ServiceNow on generative AI use cases and building copilots.

IBM also recently named Mohamad Ali Senior Vice President of IBM Consulting. Part of his remit is melding IBM’s consulting and AI assets into repeatable enterprise services.

All these moves add up to IBM positioning itself as a partner to enterprises to scale AI across hybrid cloud and platforms. Here’s how IBM sees itself in the AI ecosystem.

With that backdrop, here’s a look at what IBM announced at Think 2024:

IBM open-sourced its Granite models and made them available under Apache 2.0 licenses on Hugging Face and GitHub. The code models range from 3 billion to 34 billion parameters and are suitable for code generation, bug fixing, explaining and documenting code and maintaining repositories.

IBM launched InstructLab, which aims to make smaller open models competitive with LLMs trained at scale. The general idea is that open-source developers can contribute skills and knowledge to any LLM, iterate and merge skills. Think of InstructLab as the open-source software equivalent of AI models.

Red Hat Enterprise Linux (RHEL) AI will include the open-source Granite models for deployment. RHEL AI will also feature a foundation model runtime inferencing engine to develop, test and deploy models. RHEL AI will integrate into Red Hat OpenShift AI, a hybrid MLOps platform used by Watson.ai. Granite LLMs and code models will be supported and indemnified by Red Hat and IBM. Red Hat will also support distribution of InstructLab as part of RHEL AI.

IBM launched IBM Concert, a watsonx tool that has one interface for visibility across business applications, clouds, networks and assets. The company also launched three AI assistants built on Granite models including watsonx orchestrate Assistant Builder and watsonx Code Assistant for Enterprise Java Applications. For good measure, IBM launched watsonx Assistant for Z for mainframe data and knowledge transfer.

Via a partnership with AWS, IBM is integrating watsonx.governance with Amazon SageMaker for AI governance of models. Enterprises will be able to govern, monitor and manage models across platforms.

IBM will indemnify Llama 3 models, add Mistral Large to watsonx and bring Granite models to Salesforce and SAP. IBM watsonx.ai is also now certified to run on Microsoft Azure.

Watsonx is also becoming an engine for IT automation. IBM is building out its generative AI observability tools with Instana, Turbonomic, network automation tools and Apptio’s Cloudability Premium. These various parts were mostly acquired.