{"href":"https://api.simplecast.com/oembed?url=https%3A%2F%2Fai-a16z.simplecast.com%2Fepisodes%2Fwhy-we-need-continual-learning-xKmXoC4Y","width":444,"version":"1.0","type":"rich","title":"Why We Need Continual Learning","thumbnail_width":300,"thumbnail_url":"https://image.simplecastcdn.com/images/89450696-5007-4713-8168-eea085e49626/80ad2223-d8fa-4bb2-9645-8e2c1168a372/ai-a16z-podcast-cover-art-2.jpg","thumbnail_height":300,"provider_url":"https://simplecast.com","provider_name":"Simplecast","html":"<iframe src=\"https://player.simplecast.com/153ddfe2-39ec-4e30-bd0d-e1fb8030dd19\" height=\"200\" width=\"100%\" title=\"Why We Need Continual Learning\" frameborder=\"0\" scrolling=\"no\"></iframe>","height":200,"description":"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."}