Automated AI
We're building tools to help AI creators reduce the time they spend designing their models. Our goal is to allow non-experts across industries to build their own AI solutions, without writing complex code or performing tedious tuning and optimization.
Our work
Generative AI could offer a faster way to test theories of how the universe works
NewsKim MartineauSoftware has eaten the world. What now?
Q & AKim MartineauWhat is AI alignment?
ExplainerKim MartineauHow IBM is helping a major retailer stay ahead of the holiday crunch
Case studyKatia MoskvitchGoal-oriented flow assist: supporting low code data flow automation with natural language
Technical noteKartik Talamadupula and Michelle BrachmanSnap ML pushes AutoAI to deliver 4x-faster automated machine learning on IBM Cloud
ReleaseThomas Parnell, Haris Pozidis, Łukasz Ćmielowski, and Daniel Ryszka5 minute read- See more of our work on Automated AI
IBM Solution: AutoAI on IBM Watson Studio
Our recent work was developed into AutoAI in IBM Watson Studio. It enables data scientists to quickly build and train high-quality predictive models, and simplifies AI lifecycle management in a code-optional environment.
Learn more
Publications
- Robin Chan
- Katya Mirylenka
- et al.
- 2024
- EMNLP 2024
- Muhammad Ali
- Mamoona Javaid
- et al.
- 2024
- ICIP 2024
- Bing Zhang
- Mikio Takeuchi
- et al.
- 2024
- arXiv
- Raúl Fernández Díaz
- Rodrigo Cossio-pérez
- et al.
- 2024
- Bioinformatics
- Maximilian Schmidt
- Andrea Bartezzaghi
- et al.
- 2024
- ICANN 2024
- Hadjer Benmeziane
- Imane Hamzaoui
- et al.
- 2024
- IJCAI 2024
Tech Preview: IBM Federated Learning
Our research has been developed into a technology preview on the IBM Cloud Pak for Data. Federated Learning provides the tools for training an AI model collaboratively, by using a federated set of secure data sources.
Learn more