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1:28:21
The Gradient

The Gradient: Perspectives on AI

Deeply researched, technical interviews with experts thinking about AI and technology.
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1:28:21
Michael Sipser: Problems in the Theory of Computation
1:28:21
Michael Sipser: Problems in the Theory of Computation
On interesting and difficult problems, finite automata, derandomization, and P vs NP.
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daniel bashir
1:03:40
Andrew Lee: How AI will Shape the Future of Email
On developing a smart AI assistant, and how email clients will look in the future.
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daniel bashir
1:23:58
Joss Fong: Videomaking, AI, and Science Communication
On video journalism and science communication, bias in generative AI, incentives in journalism, and how video production is changing.
 • 
daniel bashir
2
41:34
Kate Park: Data Engines for Vision and Language
On the importance of data, training for vision vs. language models, and flywheels.
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daniel bashir
1:07:40
Ben Wellington: ML for Finance and Storytelling through Data
On challenges for ML in quantitative trading and investing, and telling stories through data.
 • 
daniel bashir
2:18:34
Venkatesh Rao: Protocols, Intelligence, and Scaling
On abstractions for AI, why monolithic scaling will stall, LLMs and experiential age, protocols, and value systems.
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daniel bashir
1
54:03
Sasha Rush: Building Better NLP Systems
On architectures for NLP, efficiency, prompting, open-source, and cultivating research environments.
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daniel bashir
1
1:59:26
Cameron Jones & Sean Trott: Understanding, Grounding, and Reference in LLMs
On the study of LLMs, distributional semantics vs embodiment, what it means to understand, theory of mind, and interpreting LLMs' behavior.
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daniel bashir
6
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