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Turpentine is building a media outlet for tech by tech people, featuring hit shows across various industries like AI and economics. They are looking for industry-leading hosts and sponsors, aiming to expand their reach and grow within the tech community.
The concept of creating human brain emulations through scanning and computer modeling is discussed. The potential impact of full human-level AI in the next 16 to 90 years is explored, pointing towards AI potentially taking over most jobs and driving economic growth, potentially mitigating population decline effects.
Robin Hanson, an economist, and polymath shares insights on futurism, emphasizing the need to analyze details before jumping to values in discussions. The conversation delves into comparing past AI paradigms with current ones and explores the potential of advancements like state space models in transforming work and society.
The podcast discusses the challenges in deploying AI technology, particularly in medical diagnostics. Legal and regulatory barriers pose obstacles to wider adoption, despite technological advancements showing promising results in areas like medical diagnosis. The conversation highlights the need for societal acceptance and regulatory changes to leverage AI's potential effectively.
The discussion touches on a potential several-century innovation pause before transitioning to the Age of M, where rising populations may decline due to falling fertility rates, impacting innovation rates. Speculation on how insular subcultures like the Amish could evolve to adopt advanced technologies like AI is considered, pointing towards a transformative yet uncertain future.
Predicting whether achieving full human-level AI in the next 60 to 90 years is feasible is uncertain, despite claims of imminent advancements. Historical enthusiasm for AI breakthroughs suggests the need for meaningful milestones instead of singular endpoints to ensure progress.
A study analyzing automation trends from 1999 to 2019 suggests that increased automation did not significantly affect wages or job numbers. Predictions indicate a continued gradual increase in automation over the next 20 years without drastic changes.
Advancements in language models, like GPT-4 and others, demonstrate significant progress in tasks like medical diagnosis and art generation. While challenges exist in merging models, there is potential for parallel processing and future integration of state-space models for enhanced capabilities.
Discussions on the economic consequences of AI automation consider the potential impact on wages and employment in the programming sector. The supply and demand dynamics, as well as the role of programming productivity, pose questions on future wage trends amidst increasing automation.
In this episode, Nathan sits down with Robin Hanson, associate professor of economics at George Mason University and researcher at Oxford’s Future of Humanity Institute. They discuss the comparison of human brains to LLMs and legacy software systems, what it would take for AI and automation to significantly impact the economy, our relationships with AI and the moral weight it has, and much more. Try the Brave search API for free for up to 2000 queries per month at https://brave.com/api
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TIMESTAMPS
(00:00) Preview
(07:10) Why our current time is a “dream time” and the move back to a Malthusian world
(13:30) What sort of world should we be striving for?
(13:40) Sponsor - Brave
(17:50) Distinguishing value talk from factual talk
(18:00) Comparing and contrasting Ems to LLMs
(22:30) The comparison of human brains to legacy software systems
(30:52) Sponsor - Netsuite
(41:01) AIs in medicine
(53:30) A several century innovation pause
(55:30) Achieving full human level AI in the next 60-90 years
(1:03:55) Chess and routine benchmarks not a good predictor of AI performance in the economy
(1:07:44) Reaching and exceeding human-level AI in the next 1000 years
(1:11:40) Losing technologies tied to scale economies
(1:12:00) Why AI is hard to maintain in the long run
(1:12:20) Standard deviation in automation
(1:14:05) Computing power grows exponentially but automation grows steadily
(1:15:50) AI art generation and deepfakes
(01:21:42) The economics of AI-powered coding
(1:33:51) Merging LLMs
(1:36:02) Rot in software and the human brain
(1:40:18) Parallelism in LLMs and brain design
(1:41:00]) Moral weight for AIs, enslavement, and cooperation with AI
(1:47:10) What would change Robin’s mind about the future
(1:49:18) Wrap
This show is produced by Turpentine: a network of podcasts, newsletters, and more, covering technology, business, and culture — all from the perspective of industry insiders and experts. We’re launching new shows every week, and we’re looking for industry-leading sponsors — if you think that might be you and your company, email us at erik@turpentine.co.
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