Episodes (Page 3)
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Sarah Paine dissects Japanese imperial ideology and economics driving WWII expansion, particularly oil shortage as key cause
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Sarah Paine examines pivotal Cold War decisions by Khrushchev, Mao, Nehru, Bhutto, and LBJ shaping South Asian geopolitics
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Tyler Cowen argues humans represent the primary bottleneck to AI progress, not computational resources
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Adam Brown explores theoretical physics including vacuum decay, holographic principle, and black hole mining
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Gwern, pseudonymous researcher, was among first to predict LLM scaling trajectory based on historical analysis
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Dylan Patel and Jon Y analyze semiconductor industry scaling requirements to achieve AGI by decade's end
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Daniel Yergin's Pulitzer Prize-winning analysis shows oil as central to understanding 20th/21st century geopolitics and conflicts
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Geneticist David Reich reveals modern humans (~1k-10k tribe) eliminated all other human species 70,000 years ago
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Joe Carlsmith examines whether we can trust power structures and techno-capital in AGI development
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Patrick McKenzie describes how small Discord-based team circumvented broken government incentives to vaccinate thousands of Americans
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Tony Blair reflects on lessons from Lee Kuan Yew and intelligence agency performance on Iraq and Ukraine assessments
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Discussion on why large AI models struggle with simple puzzles.
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Leopold Aschenbrenner predicts AGI by 2027 and discusses US/China race.
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John Schulman explains how post-training and reinforcement learning tame base model capabilities, discussing the nature of progress toward AGI
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Llama 3 represents Meta's push toward open-sourcing models on the path to AGI; open source releases create dual-use risks including bioweapons and security concerns
Mark Zuckerberg
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LLMs learn through associations rather than explicit reasoning; intelligence emerges from recognizing patterns in training data rather than deliberate computational steps
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Scaling is an artform balancing compute, data, and architecture; adding search, planning, and AlphaZero-style training on top of LLMs unlocks new capabilities
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Patrick Collison advises talented 20-30 year-olds to leave Silicon Valley and pursue founding or domain expertise; building multi-decade APIs, companies, and relationships compounds long-term value
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Tyler Cowen analyzes greatest economists (Keynes, Hayek, Smith, Mill, Coase, Schelling, George) and their relevance to AI, growth, and alignment challenges
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Narration of blog post analyzing Robert Caro's Years of Lyndon Johnson biography and lessons about power, persuasion, and political effectiveness