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
What is prompt-tuning?
NewsSaška Mojsilović wants to channel AI for good. She may also make you rethink sour cabbage
NewsWhat is synthetic data?
ExplainerHow IBM is helping a major retailer stay ahead of the holiday crunch
Case studyIBM’s new open-source toolkit for simulation
ReleaseFive ways IBM is using synthetic data to improve AI models
Research- See more of our work on Machine Learning
Projects
Accelerating clinical trials
Developing AI and analytics to understand the drivers of study or clinical trial efficiency.
- Accelerated Discovery
- Natural Language Processing
- Machine Learning
- Knowledge and Reasoning
- Healthcare
- Foundation Models
AI for single-cell research
Understanding spatiotemporal heterogeneity across different scales of biological organization.
- Healthcare
- Accelerated Discovery
- Machine Learning
Extensions and NLU Applications of Logical Neural Networks
Using Logical Neural Networks to demonstrate the benefit of incorporating knowledge and reasoning into neural network learning
- Knowledge and Reasoning
- Neuro-symbolic AI
- Natural Language Processing
- Machine Learning
Machine learning for sub-seasonal weather forecasting
- Climate
- Machine Learning
Machine learning for dynamical systems
- Machine Learning
Publications
- 2023
- IEEE TNSM
- 2023
- SDM 2023
- 2023
- MRS Spring Meeting 2023
- 2023
- ACS Spring 2023
- 2023
- ACS Spring 2023
- 2023
- ACS Spring 2023