Delve into the world of generative AI with leading AI builders and researchers as they discuss scaling laws, reasoning in LLMs, inference compute, and the future implications of AI technology
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Generative AI has rapidly expanded, raising questions on emergent reasoning properties and scaling laws.
The 'Training Data' podcast explores AI developments and challenges with founders and researchers.
Deep dives
The Rapid Expansion of Generative AI in the AI Universe
Generative AI has seen significant growth in the past 18 months, with the AI universe rapidly expanding through trillions of tokens and numerous models. This fast-paced evolution raises questions about emergent reasoning properties in LLMs, the limits of scaling laws, and the role of more inference compute. Understanding AI remains elusive, with debates on whether it will always be a black box.
Training Data Podcast: Navigating the AI Landscape
The 'Training Data' podcast hosted by Sonya Huang and Pat Grady aims to delve into the forefront of AI with founders, builders, and researchers. By seeking insights from experts in the field, the show intends to explore the latest AI developments, challenges, and potential solutions, preparing listeners for the imminent tech advancements impacting technology, business, and society.
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Exploring the Rapidly Expanding World of Generative AI
Join us as we train our neural nets on the theme of the century: AI. Sequoia Capital partners Sonya Huang and Pat Grady host conversations with leading AI builders and researchers to ask critical questions and develop a deeper understanding of the evolving technologies and their implications for technology, business and society.
The content of this podcast does not constitute investment advice, an offer to provide investment advisory services, or an offer to sell or solicitation of an offer to buy an interest in any investment fund.
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