Is Schölkopf's work too theoretical for practice?

While my work is grounded in theoretical frameworks like statistical learning theory and causal inference, the goal has always been practical impact. Concepts like support vector machines have found widespread application. The emphasis on causality, though theoretically deep, is crucial for building reliable AI systems that can adapt and reason in the real world, addressing limitations of current black-box models.

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