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
How open source paved the way for computing from anywhere
NewsKim Martineau- AI
- Hybrid Cloud Platform
- Machine Learning
- Scaling AI
AI transformers shed light on the brain’s mysterious astrocytes
ResearchKim Martineau- AI
- Foundation Models
- Life Sciences
- Machine Learning
- Natural Language Processing
- Science
What is prompt-tuning?
NewsKim Martineau- AI
- Computer Vision
- Fairness, Accountability, Transparency
- Foundation Models
- Machine Learning
- Natural Language Processing
Saška Mojsilović wants to channel AI for good. She may also make you rethink sour cabbage
NewsKim Martineau- AI Transparency
- Data and AI Security
- Explainable AI
- Fairness, Accountability, Transparency
- Machine Learning
What is synthetic data?
ExplainerKim Martineau- AI
- Data and AI Security
- Machine Learning
Migrating antiquated enterprise software to the cloud with the help of AI
ResearchMaja Vukovic, Saurabh Sinha, Rahul Krishna, and Raju Pavuluri- AI
- Application Modernization
- Machine Learning
- See more of our work on Machine Learning
Projects
AI for Single-cell Research
Understanding spatiotemporal heterogeneity across different scales of biological organization.
Publications
- Jinghui Chen
- Lixin Fan
- et al.
- 2023
- NeurIPS 2023
- Shivaram Subramanian
- Wei Sun
- 2023
- INFORMS 2023
- Vinamra Baghel
- Ayush Jain
- et al.
- 2023
- INFORMS 2023
- Ayush Jain
- Manikandan Padmanaban
- et al.
- 2023
- INFORMS 2023
- Manikandan Padmanaban
- Jagabondhu Hazra
- et al.
- 2023
- INFORMS 2023
- Dzung Phan
- Vinicius Lima
- 2023
- INFORMS 2023