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The Gradient: Perspectives on AI

Latest episodes

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Mar 7, 2024 • 2h 19min

Venkatesh Rao: Protocols, Intelligence, and Scaling

Explore the nuanced relationship between AI and society with Venkatesh Rao, discussing voice, time in AI systems, abstract planning, and reasoning. Dive into the intersection of data, intelligence, and reasoning in AI, comparing AI learning to human processes. Discover the importance of protocols in AI scaling, privacy challenges, and evolution of mathematical tools in AI. Delve into real-world AI applications, coordination problems in ML, and the need for real-time commitments.
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Feb 29, 2024 • 54min

Sasha Rush: Building Better NLP Systems

Professor Sasha Rush discusses the importance of learning and inference in AI, state-space models as an alternative to Transformers, efficiency enhancements in NLP systems through techniques like sequence level knowledge distillation, and the evolution of research perspective towards empirical approaches in NLP systems.
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Feb 22, 2024 • 1h 59min

Cameron Jones & Sean Trott: Understanding, Grounding, and Reference in LLMs

Researchers Cameron Jones and Sean Trott discuss the unexpected capabilities of language models, challenges in interpreting results of Turing tests, and the tension in lexical ambiguity. They explore the efficiency of language, internal mechanisms of language models, and the balance of meanings across wordforms. The conversation also delves into physical plausibility in language comprehension, theory of mind abilities in language models, and critiques of evaluating language models like GPT.
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Feb 15, 2024 • 60min

Nicholas Thompson: AI and Journalism

Nicholas Thompson, CEO of The Atlantic, discusses his journey into journalism, perspectives from the industry, examples of good journalism, the role of an editor, and the benefits and limitations of AI in journalism. He also explores topics such as mortality through running and the broken state of online conversations.
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Feb 8, 2024 • 1h 59min

Subbarao Kambhampati: Planning, Reasoning, and Interpretability in the Age of LLMs

Subbarao Kambhampati, Professor of computer science at Arizona State University, discusses planning, reasoning, and interpretability in the age of LLMs. Topics include explanation in AI, thinking and language, scalability in planning, computational complexity in LLMs, and concerns about misinformation generated by LLMs.
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Feb 1, 2024 • 56min

Russ Maschmeyer: Spatial Commerce and AI in Retail

Russ Maschmeyer, Product Lead for AI and Spatial Commerce at Shopify, previously led design for multiple services at Facebook and co-founded Primer. Podcast discusses AI in retail, personalized shopping experiences, challenges in creating immersive web experiences, and the future of spatial commerce.
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Jan 25, 2024 • 1h 8min

Benjamin Breen: The Intersecting Histories of Psychedelics and AI Research

Professor Benjamin Breen discusses the intersecting histories of psychedelics and AI research. They explore end of history narratives, transformative technological change, techno-utopianism, and the importance of historical context in understanding the AI landscape.
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Jan 18, 2024 • 2h 13min

Ted Gibson: The Structure and Purpose of Language

Ted Gibson, Professor of Computational Linguistics, discusses the purpose and structure of language in this podcast. Topics include dependency distances in language processing, sentence parsing and memory costs, the concept of utility in language, the relationship between language, thought, and communication, studying the language system in the brain, and exploring dependency grammar and the Chomskyian approach.
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Jan 11, 2024 • 2h 11min

Harvey Lederman: Propositional Attitudes and Reference in Language Models

Harvey Lederman, a philosophy professor, discusses propositional attitudes and reference in language models. They explore higher-order metaphysics, syntactic types, and ontological categories. They also delve into the challenges of extreme vagueness, perspectivism, and the context-sensitivity of language. The podcast covers topics such as identity statements, propositional attitude psychology, sense and reference, and the attribution of beliefs to language models. Additionally, they discuss n-gram models, novel reference, and the intersection between AI and the philosophy of language.
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Jan 4, 2024 • 1h 30min

Eric Jang: AI is Good For You

In this podcast, Eric Jang, an AI researcher and author of 'AI is Good for You', discusses the problem space of humanoid robots, definitions and timelines of AGI, rediscovering old ideas in AI and robotics, the role of human in the loop learning, levels of abstraction for modeling decision-making, embodiment in AI systems, and the potential benefits and drawbacks of AGI.

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