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EPISODE · Apr 28, 2026 · 18 MIN

Why We Need Continual Learning

from AI + a16z · host Elena Burger, Malika Aubakirova

Elena Burger speaks with Malika Aubakirova, partner on the AI infrastructure team at a16z, about why today’s AI systems struggle to learn over time. They discuss the limits of in-context learning, the case for continual learning, and how models may need to evolve from static systems into ones that learn from experience. Resources: Follow Malika on X: https://x.com/MaikaThoughts Follow Elena on X: https://x.com/VirtualElena Read more on Why We Need Continual Learning: https://a16z.com/why-we-need-continual-learning/ Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Episode metadata supplied by the publisher feed · Published Apr 28, 2026

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Elena Burger speaks with Malika Aubakirova, partner on the AI infrastructure team at a16z, about why today’s AI systems struggle to learn over time. They discuss the limits of in-context learning, the case for continual learning, and how models may need to evolve from static systems into ones that learn from experience.

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Why We Need Continual Learning

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