Towards a generative future for computing
Release
Mike Murphy
Science
Our focus extends beyond just increasing the rate of scientific discovery; it's about laying new technological foundations that can be applied across multiple fields, driving significant advancements in climate science, materials discovery, healthcare, and more.
Our work
Opening a new era in algorithmic development
Deep DiveAlessandro Curioni and Jay GambettaFrom simulated steps to real-world care: AI learns how we walk for neurology
ResearchPeter HessIBM Research Ireland moves to the heart of Dublin with a new lab at Trinity College Dublin
NewsMike MurphyIBM’s Dmitry Krotov wants to crack the ‘physics’ of memory
ResearchKim MartineauA faster way to screen supply chains for harmful chemicals
ResearchKim Martineau- See more of our work on Science
Topics
Accelerated Discovery
The world is changing rapidly every day, and the way we used to solve problems won’t cut it anymore. At IBM Research, we’re combining our expertise in quantum computing, AI, and hybrid cloud to drastically increase how quickly we can discover solutions to tackle today’s most urgent problems.Materials Discovery
It can take over 10 years to come up with new materials. At IBM Research, we’re looking to accelerate the discovery process using new AI methods, robotics, the hybrid cloud, and quantum computers. Our goal is to unlock new properties and materials to address global challenges in years not decades.
Publications
Stable iterative refinement for solving linear systems with inaccurate computation
- 2026
- J. Comput. Appl. Math.
MDLab: AI frameworks for Carbon Capture and Battery Materials
- Bruce Elmegreen
- Hendrik Hamann
- et al.
- 2025
- Frontiers in Environmental Science
Dynamic Multimodal Fusion for Robust Molecular Representation Learning
- 2025
- ACS Fall 2025
3rd TrustAI Workshop: Building Public Awareness and Engagement
- Miriam Rateike
- Brian Mboya
- et al.
- 2025
- DLI 2025
AI-driven prediction of monoclonal antibody binding and activity against influenza A virus
- Michal Ozery-Flato
- Ella Barkan
- et al.
- 2025
- ACS Fall 2025
Raman Spectrum Prediction from Crystallographic Information with Graph Neural Networks
- 2025
- ACS Fall 2025
The fastest path to progress
Watch a new short film on the computing revolutions that are accelerating the rate of scientific discovery like nothing before.
Watch the film
Projects
We're developing technological solutions to assist subject matter experts with their scientific workflows by enabling the Human-AI co-creation process.
Creating the AI-enabled lab for a new era of reproducible and collaborative experimentation
