What’s Next in AI
is fluid intelligence
Today’s AI is narrow. Applying trained models to new challenges requires an immense amount of new data training, and time. We need AI that combines different forms of knowledge, unpacks causal relationships, and learns new things on its own.
Our work
Breaking the von Neumann bottleneck using phase-change materials
ResearchMachine learning: From “best guess” to best data-based decisions
ReleaseTapping into the inner rhythm of living organisms with AI and ML
ResearchIBM and The Michael J. Fox Foundation use AI to help predict progression of Parkinson’s disease
ResearchWhat's Next in AI: IBM Research Africa to host virtual AI seminar series in August
NewsHow AI can help predict climate extremes
Research- See more of our work on AI
Tools + code
IBM Analog Hardware Acceleration Kit
An open source Python toolkit for exploring and using the capabilities of in-memory computing devices in the context of artificial intelligence.
View project ↗Data Quality for AI
An integrated toolkit to assess data quality for building classification applications. Enables data profiling and quality estimation metrics to assess the quality of ingested data in a systematic and objective manner.
View project ↗Project Debater for Academic Use
The technologies underlying Project Debater available as cloud services. Includes core natural language understanding capabilities, argument mining, and narrative generation.
View project ↗AI FactSheets 360
Toolkit to create factsheets outlining the details about how an AI service operates, how it was trained and tested, its performance metrics, fairness and robustness checks, intended uses, maintenance, and other critical details.
View project ↗
Publication collections
IJCAI 2021
15
International Joint Conference on Artificial Intelligence
21 Aug – 26 AugKDD 2021
17
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
14 Aug – 18 AugACL-IJCNLP 2021
24
Annual Meeting of the Association for Computational Linguistics
01 Aug – 06 AugICML 2021
32
International Conference on Machine Learning
18 Jul – 24 Jul
Teams
- Adversarial Robustness and Privacy
- AI for Asset Management
- AI for Business Automation
- AI for Code
- AI for Supply Chain
- AI Hardware
- AI Testing
- Automated AI
- Causality
- Computer Vision
- Conversational AI
- Explainable AI
- Fairness, Accountability, Transparency
- Human-Centered AI
- Knowledge and Reasoning
- Machine Learning
- Natural Language Processing
- Neuro-symbolic AI
- Speech
- Trusted AI
- Trustworthy Generation
- Uncertainty Quantification
