Intelligence in Motion: Why AI Is Stuck in the Past | Mustapha Sadiq | TEDxBoston
Автор: TEDx Talks
Загружено: 2026-02-13
Просмотров: 120
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"In this talk, Mustapha Sadiq explores the limits of modern AI in a world shaped by complex, ever-changing systems.
Deep learning has achieved extraordinary success by learning patterns from historical data. But once trained, these models become static representations of the past. In environments driven by emergent behaviour - such as financial markets, climate systems, and social networks - patterns shift, new states arise, and yesterday’s assumptions can quickly become obsolete.
Mustapha introduces the concept of the “emergence condition”: the moment when structural change renders prior learning insufficient. Because retraining is reactive, it cannot fully solve this challenge.
He proposes a complementary approach, causal intelligence, focused not on predicting the next step, but on understanding how change forms and evolves in real time.
The talk reframes AI design for a non-stationary world and explores what it means to build systems that evolve alongside the environments they navigate."
AI, Intelligence, Machine Learning, Math, Science, Technology Mustapha Sadiq is a student at Harvard University and a researcher in complex systems and artificial intelligence. His work challenges the foundations of modern AI by addressing its reliance on static training data. Through the development of causal intelligence, he explores how machines can autonomously understand how change emerges and evolves in real time - moving beyond prediction toward resilient, adaptive intelligence. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx
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