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.
Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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