IBM Research

THANK YOU to the developers, engineers, educators, and attendees who visited our booth at PyTorch Conference 2025 this week. We showcased new open-source AI tools that are expanding possibilities in a multi-accelerator world: https://ibm.co/6041BzG07 ▶️ A key highlight was our work with AMD and Red Hat to build Triton-based kernels for vLLM—enabling efficient, hardware-agnostic inference across GPU platforms without proprietary libraries. This effort, presented by Thomas Parnell and Aleksandr M., strengthens support for open, extensible systems in the PyTorch and vLLM communities. ▶️ Researcher Linsong Chu and his team shared a major training milestone: Using torchtitan, a PyTorch-native training framework, they successfully trained one of the first Llama 3-70B-derived models from an open repository—achieving comparable quality with just one-third of the original training budget, half the token count, and FP8 low-precision quantization. ▶️ Lastly, but certainly not least, IBM Research distinguished engineer Mudhakar Srivatsa spotlighted our adoption of vLLM and torch.compile to integrate emerging accelerators like the IBM Spyre AI accelerator. IBM Research is working on a Spyre backend compiler and vLLM plugin with paged attention, with a goal of boosting memory efficiency and scalability for LLM inference. Follow the link above for a full recap #PyTorchCon and of how we’re expanding AI model training and inference for the open-source community.

This week in IBM Research, we’re diving into quantum-centric supercomputing, everything new at PyTorch 2025, and an exciting new dataset named after a colorful bird. Toucan, a new open-source dataset for AI agents, takes flight. IBM and the University of Washington have open-sourced Toucan, a landmark dataset of 1.5 million AI agent task scenarios designed to accelerate tool-use learning in language models. By capturing real-world API executions across 2,000 web services, Toucan enables agents to reason, act, and collaborate more effectively—transforming chatbots into capable digital assistants. At this year’s PyTorch 2025, IBM unveiled a new collection of open-source AI tools redefining possibilities in a multi-AI accelerator world. Highlights included torchtitan, a PyTorch-native framework for efficient low-precision training, and Triton-powered kernels that boost inference throughput on vLLM across multiple GPU architectures. IBM Quantum is expanding the frontier of quantum-centric supercomputing with the release of a new C-language API for Qiskit. Designed for developers working in compiled languages like C++ and Fortran, this interface enables hybrid quantum-classical workflows that are integrated with high-performance computing environments. Included in Qiskit v2.2, the new demo showcases a complete quantum workflow, demonstrating real-world quantum applications in modern HPC systems. Catch up with this week in Research ⤵️

Don’t miss Dr. Zaira Nazario speak on the panel “Accuracy and Trust in the Digital Age” at MetLife’s 2025 Triangle Tech X conference this week: https://ibm.co/6049Bz8iW This free, virtual conference brings together leaders across industries to explore agility, authenticity and inclusion in STEM innovation. Her panel will highlight how organizations can balance fast-paced digital transformation with the integrity and accountability needed to build trust. Register via the link above. #TTX2025

vLLM V1 is now fully supported on AMD GPUs! New blog from vLLM Team at IBM Research, vLLM Team at Red Hat, and vLLM Team at AMD: Learn how the teams at IBM, AMD and Red Hat built an optimized attention backend for vLLM V1 using Triton kernels. In this deep technical blog, we describe the optimizations we performed to ensure that the Triton backend achieves state-of-the-art performance on AMD. Check it out if you are interested in knowing more about the art of writing lighting fast Triton kernels for AI applications! 🔗 Read here: https://hubs.la/Q03PC6kh0 #vLLM #PyTorch #OpenSourceAI

“How can you train better agents? Through diverse, high-quality examples sourced from the real world.” Researchers from IBM and the University of Washington release Toucan-1.5M, the largest tool-calling dataset to date, designed to improve how agents interact with the world: https://ibm.co/6047BK7G3 Comprising over 1.5 million real-life tool-calling task sequences—called trajectories—synthesized from 495 real-world Model Context Protocols (MCPs) servers, Toucan is built to teach AI agents how to call APIs by connecting to MCP servers. Models fine-tuned on Toucan data demonstrated impressive performance gains across common agentic benchmarks, including Berkeley Function-Calling Leaderboard V3, τ-Bench, and MCP-Universe. Now available on Hugging Face, Toucan is currently more than five times larger than the next largest open-source dataset—NVIDIA’s Nemotron, which contains 310,000 trajectories. With over 2,000 tools represented, it’s also likely the most diverse.

AI has a cost problem. The Groq and IBM partnership will solve this: watsonx agentic platform on Groq - 5x faster, at 20% of the cost. Also enabling @RedHat vLLM on Groq.

🚀 CUGA is now open source! We’re thrilled to share that the CUGA Agent, which is top-ranked on WebArena and AppWorld, is now available to the community. CUGA is a configurable, general-purpose AI agent designed to accelerate the development of high-performing, domain-specific agents for real-world applications. It offers built-in enterprise-grade guarantees, integrates seamlessly with MCP, and supports interaction with REST APIs, browser-based web applications, and soon, file systems, data stores, and command-line interfaces. Rather than manually crafting prompts or making complex architectural decisions, developers simply configure MCP tools and supply domain expertise, standard operation proceduers and guardrails. As a result, developers using CUGA will likely see significant improvement in development time and cost, 🔗 Learn more in the official IBM Research blog: https://lnkd.in/d4m5jkJB 🌐 Explore CUGA: www.cuga.dev 📂 Dive into the code and give us a star: https://lnkd.in/d4zCy2W4 We can’t wait to see what the community builds with it. Contributions, feedback, and collaborations are welcome! #OpenSource #AIagents #CUGA #AgentFramework #IBMResearch #WebArena #AppWorld

Quantum leaps in Spain, tiny AI in space, and steerable LLMs. A busy week in Research! The Basque Country and IBM celebrate the launch of Europe’s first IBM Quantum System Two in San Sebastián, providing researchers with direct access to advanced quantum hardware. Scientists are already using the system to simulate strong nuclear force interactions, expanding the frontier of condensed matter physics. In parallel, IBM, NASA - National Aeronautics and Space Administration and European Space Agency - ESA open-sourced lightweight versions of Prithvi and TerraMind Earth observation models, 120 times smaller than their larger predecessors. These compact models maintain high performance and can run on devices like smartphones and satellites, enabling real-time environmental analysis in the field. To improve the safety and controllability of generative AI, we introduced AISteer360, a modular toolkit that allows users to steer large language model behavior efficiently. It offers lightweight methods for customizing output style and content safety, complementing IBM’s broader AI governance tools. Read on and subscribe for more updates across IBM Research. 👇

The agenda for the 2025 AI Hardware Forum in November is set. The lineup includes speakers from AMD, Meta, Foxconn, Red Hat, Harvard University, Massachusetts Institute of Technology, Rensselaer Polytechnic Institute, Cambrian AI, and IBM. We will be discussing the entire hardware and software #AI stack, the open-source community, and the evolution of models. Stay tuned for exciting announcements, and demos of the new IBM Spyre AI accelerator on various platforms. More details at https://lnkd.in/eZ-CANCJ

In partnership with NASA and the European Space Agency, we’ve open-sourced new, lightweight versions of our geospatial and Earth observation models designed to run on edge devices like satellites, laptops, or even smartphones: https://ibm.co/6041BK5kS Despite being up to 120x smaller, these new “tiny” and “small” versions of the Prithvi and TerraMind models benchmark similar performance to their larger, industry-leading predecessors. Follow the link above to learn how these models could reshape how we think about doing science in regions far from the lab, whether that’s in the savanna or the vacuum of space.