Machine Learning
Machine learning uses data to teach AI systems to imitate the way that humans learn. They can find the signal in the noise of big data, helping businesses improve their operations. We've been in the field since since the beginning: IBMer Arthur Samuel even coined the term “Machine Learning” back in 1959.
Our work
In search of AI algorithms that mimic the brain
Q & AKim MartineauHow open source paved the way for computing from anywhere
Q & AKim MartineauAI transformers shed light on the brain’s mysterious astrocytes
ResearchKim MartineauWhat is prompt-tuning?
NewsKim MartineauSaška Mojsilović wants to channel AI for good. She may also make you rethink sour cabbage
NewsKim MartineauWhat is synthetic data?
ExplainerKim Martineau and Rogerio Feris- See more of our work on Machine Learning
Publications
An Online, Probabilistic Distributed Tracing System
- Mert Toslali
- Syed Qasim
- et al.
- 2024
- IC2E 2024
MDLab: AI frameworks for Carbon Capture and Battery Materials
- Bruce Elmegreen
- Hendrik Hamann
- et al.
- 2025
- Frontiers in Environmental Science
Integrating Molecular Dynamics Simulations and Machine Learning to Uncover Important Determinants of protein-protein Interactions
- Tiffany Callahan
- Kevin Cheng
- et al.
- 2025
- ACS Spring 2025
Uncertainty Analysis of Molecular Quantum Properties Prediction Using Chemical Foundation Models
- Siya Kunde
- Emilio Ashton Vital Brazil
- et al.
- 2025
- ACS Spring 2025
Foundation models for materials discovery – current state and future directions
- Edward Pyzer-knapp
- Matteo Manica
- et al.
- 2025
- npj Computational Materials
LionHeart: A Layer-based Mapping Framework for Heterogeneous Systems with Analog In-Memory Computing Tiles
- Corey Liam Lammie
- Yuxuan Wang
- et al.
- 2025
- IEEE TETC