Discovery Foundation Models: Toward Open-Ended Discovery Intelligence
Foundation models have progressed from learning and reasoning over existing knowledge, to increasingly learning through action, tool use, and outcome feedback. We argue that the next frontier is a further transition: from solving and acting within problems specified by humans to participating in the process by which new problems, representations, explanations, and knowledge are
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Foundation models have progressed from learning and reasoning over existing knowledge, to increasingly learning through action, tool use, and outcome feedback. We argue that the next frontier is a further transition: from solving and acting within problems specified by humans to participating in the process by which new problems, representations, explanations, and knowledge are
This research proposes a new paradigm for AI, moving beyond human-specified problems to AI-driven problem discovery and knowledge creation. For ML engineers, understanding Discovery Foundation Models (DFMs) is crucial for developing the next generation of autonomous AI systems that can innovate and expand scientific or engineering frontiers, rather than just optimize existing solutions.