Science
Our focus extends beyond just increasing the speed 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
Landmark IBM error correction paper published on the cover of Nature
ResearchRafi Letzter- Impact Science
- Quantum
- Quantum Error Correction & Mitigation
IBM and NASA build language models to make scientific knowledge more accessible
Technical noteBishwaranjan Bhattacharjee, Aashka Trivedi, Masayasu Muraoka, Bharath Dandala, Rong Zhang, and Yousef El-Kurdi- Accelerated Discovery
- AI
- Generative AI
- Science
Inventing the devices that underpin how the world communicates
NewsMike Murphy- Science
- Semiconductors
In search of AI algorithms that mimic the brain
Q & AKim Martineau- AI
- Foundation Models
- Generative AI
- Machine Learning
- Science
A single-molecule magnetic switch
Technical noteShantanu Mishra- Exploratory Science
The 2023 IBM Research annual letter
Deep DiveDarío Gil- Accelerated Discovery
- AI
- Hybrid Cloud
- Quantum
- Science
- Security
- Semiconductors
- See more of our work on Science
Topics
- Accelerated DiscoveryThe 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 DiscoveryIt 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
- Guy Cohen
- Peter Kerns
- et al.
- 2024
- MRS Spring Meeting 2024
- Ching-Tzu Chen
- Hsin Lin
- et al.
- 2024
- MRS Spring Meeting 2024
- Bertram Poettering
- Simon Rastikian
- 2024
- PKC 2024
- Refaldi Intri Dwi Putra
- Tatsuya Ishikawa
- et al.
- 2024
- ICASSP 2024
- Daiki Kimura
- Tatsuya Ishikawa
- et al.
- 2024
- ICASSP 2024
- Leveraging Large Language Models in Analytics Practice: Opportunities, Challenges and Best Practices
- Segev Wasserkrug
- Arnie Greenland
- et al.
- 2024
- INFORMS Analytics Conference 2024
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
Accelerator Technologies
We're developing technological solutions to assist subject matter experts with their scientific workflows by enabling the Human-AI co-creation process.
AI for Scientific Discovery
Creating the AI-enabled lab for a new era of reproducible and collaborative experimentation