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Bookmark or Share- What is federated learning? - IBM ResearchIn vertical federated learning, the data are complementary; movie and book reviews, for example, are combined to predict someone’s music preferences. Finally, in federated transfer learning, a pre-trained foundation model designed to perform one task, like detecting cars, is trained on another dataset to do something else, like identify cats.
- Artificial Intelligence - IBM ResearchToday'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. In short, AI must have fluid intelligence— and that's exactly what our AI research teams are building.
- Neuro-symbolic AI - IBM ResearchNeuro-symbolic AI. We see Neuro-symbolic AI as a pathway to achieve artificial general intelligence. By augmenting and combining the strengths of statistical AI, like machine learning, with the capabilities of human-like symbolic knowledge and reasoning, we're aiming to create a revolution in AI, rather than an evolution.
- Machine Learning and Data Mining - IBM ResearchSince then, machine learning for structured data has become one of the major research areas in data mining and machine learning. Proud of our successes, we are actively tackling the frontiers in machine learning and data mining, and applying the results to the real world, taking full advantage of our merit of proximity to advanced companies and ...
- Quantum Machine Learning - IBM ResearchQuantum Machine Learning. We now know that quantum computers have the potential to boost the performance of machine learning systems, and may eventually power efforts in fields from drug discovery to fraud detection. We're doing foundational research in quantum ML to power tomorrow’s smart quantum algorithms.
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