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The Gradient Podcast

The Gradient Podcast

Interviews with various people who research, build, or use AI, including academics, engineers, artists, entrepreneurs, and more.
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Arjun Ramani & Zhengdong Wang: Why Transformative AI is Really, Really Hard to Achieve
On why "AI will change the world" narratives might be less true than you think.
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daniel bashir
Miles Grimshaw: Benchmark, LangChain, and Investing in AI
On investing in AI through the deep learning decade, Benchmark's LangChain investment, and emerging opportunities for AI.
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daniel bashir
1
Shreya Shankar: Machine Learning in the Real World
On what makes ML engineering hard and how to think about it.
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daniel bashir
Stevan Harnad: AI's Symbol Grounding Problem
On Symbol Grounding in AI systems, the Turing Test, the Chinese Room Argument, and category formation.
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daniel bashir
17
Terry Winograd: AI, HCI, Language, and Cognition
On the early years of AI research, understanding language and cognition, design and human-centeredness, and politics as a technologist.
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daniel bashir
9
Gil Strang: Linear Algebra and Deep Learning
On decades of teaching linear algebra, mathematical perspectives on deep learning, and the future of ML and mathematics pedagogy.
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daniel bashir
Anant Agarwal: AI for Education
On new features in EdX for education, ChatGPT's impact on student success, and more!
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The Gradient
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