Generative AI could offer a faster way to test theories of how the universe works
News
Kim Martineau
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
Software 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.
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Publications
CIRCUITSYNTH-RL: LLM-Based Circuit Topology Synthesis with RL Refinement
- Prashanth Vijayaraghavan
- Luyao Shi
- et al.
- 2025
- DAC 2025
Schema and Natural Language Aware In-Context Learning for Improved GraphQL Query Generation
- 2025
- NAACL 2025
ASTER: Natural and Multi-language Unit Test Generation with LLMs
- Rangeet Pan
- Myeongsoo Kim
- et al.
- 2025
- ICSE 2025
Rationalization Models for Text-to-SQL
- Gaetano Rossiello
- Nhan Pham
- et al.
- 2025
- ICLR 2025
RAC-GAN: Iterative Dual-Objective Over and Under Sampling for Imbalanced Datasets
- 2025
- ICASSP 2025
Text-Guided Few-Shot Semantic Segmentation with Training-Free Multimodal Feature Matching
- Guillaume Buthmann
- Tomoya Sakai
- et al.
- 2025
- ICASSP 2025
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.
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