title
François Chollet: Measures of Intelligence | Lex Fridman Podcast #120
description
François Chollet is an AI researcher at Google and creator of Keras. Support this podcast by supporting our sponsors (and get discount):
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EPISODE LINKS:
Francois's Twitter: https://twitter.com/fchollet
Francois's Website: https://fchollet.com/
On the Measure of Intelligence (paper): https://arxiv.org/abs/1911.01547
PODCAST INFO:
Podcast website: https://lexfridman.com/podcast
Apple Podcasts: https://apple.co/2lwqZIr
Spotify: https://spoti.fi/2nEwCF8
RSS: https://lexfridman.com/feed/podcast/
Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4
Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41
OUTLINE:
0:00 - Introduction
5:04 - Early influence
6:23 - Language
12:50 - Thinking with mind maps
23:42 - Definition of intelligence
42:24 - GPT-3
53:07 - Semantic web
57:22 - Autonomous driving
1:09:30 - Tests of intelligence
1:13:59 - Tests of human intelligence
1:27:18 - IQ tests
1:35:59 - ARC Challenge
1:59:11 - Generalization
2:09:50 - Turing Test
2:20:44 - Hutter prize
2:27:44 - Meaning of life
CONNECT:
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- Support on Patreon: https://www.patreon.com/lexfridman
detail
{'title': 'François Chollet: Measures of Intelligence | Lex Fridman Podcast #120', 'heatmap': [{'end': 3525.3, 'start': 3415.712, 'weight': 0.759}, {'end': 4724.338, 'start': 4624.582, 'weight': 0.842}, {'end': 5468.416, 'start': 5365.16, 'weight': 0.869}, {'end': 6575.852, 'start': 6479.576, 'weight': 1}], 'summary': 'Explores rare scientific study of artificial general intelligence, covers language learning, discusses organizing thoughts, explores views and challenges in ai, delves into intelligence measurement challenges, discusses physical fitness and intelligence, the arc challenge, achieving human parity in general fluid intelligence, and the cultural influence on human existence.', 'chapters': [{'end': 116.766, 'segs': [{'end': 29.03, 'src': 'embed', 'start': 0.049, 'weight': 1, 'content': [{'end': 4.851, 'text': 'The following is a conversation with Francois Chollet, his second time on the podcast.', 'start': 0.049, 'duration': 4.802}, {'end': 12.393, 'text': "He's both a world-class engineer and a philosopher in the realm of deep learning and artificial intelligence.", 'start': 5.451, 'duration': 6.942}, {'end': 23.817, 'text': 'This time we talk a lot about his paper titled On the Measure of Intelligence that discusses how we might define and measure general intelligence in our computing machinery.', 'start': 13.233, 'duration': 10.584}, {'end': 29.03, 'text': 'Quick summary of the sponsors, Babbel, Masterclass, and Cash App.', 'start': 24.707, 'duration': 4.323}], 'summary': 'Francois chollet discusses defining general intelligence in computing machinery.', 'duration': 28.981, 'max_score': 0.049, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO449.jpg'}, {'end': 77.255, 'src': 'embed', 'start': 47.783, 'weight': 0, 'content': [{'end': 52.327, 'text': 'This is very good for incremental and sometimes big incremental progress.', 'start': 47.783, 'duration': 4.544}, {'end': 57.137, 'text': 'On the other hand, the outside, the mainstream, renegade,', 'start': 53.274, 'duration': 3.863}, {'end': 66.605, 'text': 'you could say AGI community works on approaches that verge on the philosophical and even the literary, without big public benchmarks.', 'start': 57.137, 'duration': 9.468}, {'end': 71.709, 'text': "Walking the line between the two worlds is a rare breed, but it doesn't have to be.", 'start': 67.385, 'duration': 4.324}, {'end': 77.255, 'text': 'I ran the AGI series at MIT as an attempt to inspire more people to walk this line.', 'start': 72.469, 'duration': 4.786}], 'summary': 'Agi community focuses on philosophical and literary approaches without big public benchmarks, while the agi series at mit aims to inspire more people to bridge the gap.', 'duration': 29.472, 'max_score': 47.783, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO447783.jpg'}, {'end': 127.656, 'src': 'embed', 'start': 97.875, 'weight': 3, 'content': [{'end': 101.377, 'text': 'support on Patreon or connect with me on Twitter at Lex Friedman.', 'start': 97.875, 'duration': 3.502}, {'end': 105.26, 'text': "As usual, I'll do a few minutes of ads now and no ads in the middle.", 'start': 102.058, 'duration': 3.202}, {'end': 109.942, 'text': 'I try to make these interesting, but I give you timestamps so you can skip.', 'start': 105.8, 'duration': 4.142}, {'end': 114.205, 'text': 'But still, please do check out the sponsors by clicking the links in the description.', 'start': 110.663, 'duration': 3.542}, {'end': 116.766, 'text': "It's the best way to support this podcast.", 'start': 114.625, 'duration': 2.141}, {'end': 123.892, 'text': 'This show is sponsored by Babbel, an app and website that gets you speaking in a new language within weeks.', 'start': 117.947, 'duration': 5.945}, {'end': 127.656, 'text': 'Go to Babbel.com and use code Lex to get three months free.', 'start': 124.373, 'duration': 3.283}], 'summary': 'Podcast promotes babbel app for language learning. use code lex for 3 months free.', 'duration': 29.781, 'max_score': 97.875, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO497875.jpg'}], 'start': 0.049, 'title': 'Artificial general intelligence', 'summary': 'Delves into the rare scientific study of artificial general intelligence, contrasting mainstream and renegade ai communities, and aims to inspire more people to pursue this line of work.', 'chapters': [{'end': 116.766, 'start': 0.049, 'title': 'On the measure of intelligence', 'summary': 'Discusses the rare scientific study of artificial general intelligence, the contrast between mainstream and renegade ai communities, and the attempt to inspire more people to pursue this line of work.', 'duration': 116.717, 'highlights': ['Francois Chollet is a world-class engineer and a philosopher in the realm of deep learning and artificial intelligence, and the chapter focuses on his paper titled On the Measure of Intelligence.', 'The mainstream machine learning community works on very narrow AI with very narrow benchmarks, while the renegade AGI community works on approaches that verge on the philosophical and literary, without big public benchmarks.', 'The AGI series at MIT was an attempt to inspire more people to walk the line between mainstream and renegade AI communities, and DeepMind and OpenAI also occasionally walk this line.', 'The chapter emphasizes the rareness of the serious, rigorous scientific study of artificial general intelligence.', 'The podcast encourages support through various means such as subscribing on YouTube, reviewing with five stars on Apple Podcasts, and supporting on Patreon.']}], 'duration': 116.717, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO449.jpg', 'highlights': ['The chapter emphasizes the rareness of the serious, rigorous scientific study of artificial general intelligence.', 'The mainstream machine learning community works on very narrow AI with very narrow benchmarks, while the renegade AGI community works on approaches that verge on the philosophical and literary, without big public benchmarks.', 'The AGI series at MIT was an attempt to inspire more people to walk the line between mainstream and renegade AI communities, and DeepMind and OpenAI also occasionally walk this line.', 'Francois Chollet is a world-class engineer and a philosopher in the realm of deep learning and artificial intelligence, and the chapter focuses on his paper titled On the Measure of Intelligence.', 'The podcast encourages support through various means such as subscribing on YouTube, reviewing with five stars on Apple Podcasts, and supporting on Patreon.']}, {'end': 986.947, 'segs': [{'end': 310.053, 'src': 'embed', 'start': 285.288, 'weight': 4, 'content': [{'end': 291.73, 'text': 'So again, if you get Cash App from the App Store or Google Play and use code LEXPODCAST, you get $10.', 'start': 285.288, 'duration': 6.442}, {'end': 299.633, 'text': 'And Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world.', 'start': 291.73, 'duration': 7.903}, {'end': 303.635, 'text': "And now, here's my conversation with Francois Chollet.", 'start': 300.494, 'duration': 3.141}, {'end': 310.053, 'text': 'What philosophers, thinkers or ideas had a big impact on you growing up and today?', 'start': 305.069, 'duration': 4.984}], 'summary': 'Use code lexpodcast on cash app for $10 and $10 donation to first.', 'duration': 24.765, 'max_score': 285.288, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO4285288.jpg'}, {'end': 375.091, 'src': 'embed', 'start': 340.779, 'weight': 2, 'content': [{'end': 344.963, 'text': "It's actually superseded by many newer developments in developmental psychology.", 'start': 340.779, 'duration': 4.184}, {'end': 348.807, 'text': 'But to me it was very interesting,', 'start': 345.664, 'duration': 3.143}, {'end': 355.995, 'text': 'very striking and actually shaped the early ways in which I started thinking about the mind and the development of intelligence as a teenager.', 'start': 348.807, 'duration': 7.188}, {'end': 362.18, 'text': 'his actual ideas or the way he thought about it, or just the fact that you could think about the developing mind at all? I guess both.', 'start': 356.235, 'duration': 5.945}, {'end': 375.091, 'text': 'Jean Piaget is the author that really introduced me to the notion that intelligence and the mind is something that you construct throughout your life and that children construct it in stages.', 'start': 362.561, 'duration': 12.53}], 'summary': "Jean piaget's ideas shaped early thinking about mind and intelligence, introducing the notion of constructing intelligence in stages.", 'duration': 34.312, 'max_score': 340.779, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO4340779.jpg'}, {'end': 729.598, 'src': 'embed', 'start': 692.865, 'weight': 0, 'content': [{'end': 695.606, 'text': 'Yeah, I think so.', 'start': 692.865, 'duration': 2.741}, {'end': 702.847, 'text': 'The mind has layers, right? And language is almost like the outermost, the uppermost layer.', 'start': 697.086, 'duration': 5.761}, {'end': 713.19, 'text': 'But before we think in words, I think we think in terms of emotion in space, and we think in terms of physical actions.', 'start': 704.648, 'duration': 8.542}, {'end': 729.598, 'text': "And I think babies in particular probably express these thoughts in terms of the actions that they've seen or that they can perform and in terms of motions of objects in their environment before they start thinking,", 'start': 714.17, 'duration': 15.428}], 'summary': 'Language is like the outermost layer of the mind, which starts with emotions and physical actions before words.', 'duration': 36.733, 'max_score': 692.865, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO4692865.jpg'}], 'start': 117.947, 'title': 'Language learning and ai hierarchy', 'summary': 'Covers language learning with babbel offering 14 languages, sponsorship of masterclass providing all-access pass to courses for $180/year, and the promotion of cash app for digital money transactions. it also explores the concept of hierarchy in ai and the role of language as an operating system for the mind, with insights on cognition, memory, and the fundamental nature of language.', 'chapters': [{'end': 407.075, 'start': 117.947, 'title': 'Language learning, masterclass, and finance', 'summary': 'Discusses language learning with babbel, featuring 14 languages and daily 10-15 minute lessons, followed by sponsorship of masterclass, offering an all-access pass to courses from various experts for $180 a year, and finally, the promotion of cash app, allowing digital money transactions and investment with a 92% digital money existence.', 'duration': 289.128, 'highlights': ['Babbel offers 14 languages and daily 10-15 minute lessons, designed by over 100 language experts. Babbel provides access to 14 languages with daily 10-15 minute lessons, crafted by over 100 language experts, promising quick language acquisition.', 'Masterclass offers an all-access pass to watch courses from various experts for $180 a year, including Chris Hadfield, Neil deGrasse Tyson, Will Wright, Carlos Santana, Gary Kasparov, and Daniel Negrano. For $180 a year, Masterclass provides an all-access pass to courses from experts like Chris Hadfield, Neil deGrasse Tyson, Will Wright, Carlos Santana, Gary Kasparov, and Daniel Negrano, covering topics such as space exploration, scientific thinking, game design, guitar, chess, and poker.', 'Cash App allows digital money transactions and investment with a 92% digital money existence. Cash App facilitates digital money transactions and investment, reflecting the predominant 92% existence of digital money in the world.']}, {'end': 986.947, 'start': 407.915, 'title': 'Hierarchy in ai and language as an operating system', 'summary': 'Explores the concept of hierarchy in ai and its practical implementation in deep learning, as well as the role of language as an operating system for the mind, with insights on cognition, memory, and the fundamental nature of language.', 'duration': 579.032, 'highlights': ['The chapter explores the concept of hierarchy in AI and its practical implementation in deep learning The speaker discusses the idea of hierarchies in AI and how they have been around since the 1980s, finding practical implementation in deep learning.', 'Insights on the role of language as an operating system for the mind Language is likened to an operating system for the brain, fundamental to cognition, and used as a tool for memory storage and retrieval.', 'Discusses the nature of memory and language, including the possibility of deeper languages for thinking The discussion covers the nature of memory, the use of language for memory programming, and the concept of deeper languages for thinking prior to the use of words.']}], 'duration': 869, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO4117947.jpg', 'highlights': ['Babbel offers 14 languages with daily 10-15 minute lessons, designed by over 100 language experts, promising quick language acquisition.', 'Masterclass provides an all-access pass to courses from experts like Chris Hadfield, Neil deGrasse Tyson, Will Wright, Carlos Santana, Gary Kasparov, and Daniel Negrano, covering topics such as space exploration, scientific thinking, game design, guitar, chess, and poker for $180 a year.', 'Cash App facilitates digital money transactions and investment, reflecting the predominant 92% existence of digital money in the world.', 'The speaker discusses the idea of hierarchies in AI and how they have been around since the 1980s, finding practical implementation in deep learning.', 'Language is likened to an operating system for the brain, fundamental to cognition, and used as a tool for memory storage and retrieval.', 'The discussion covers the nature of memory, the use of language for memory programming, and the concept of deeper languages for thinking prior to the use of words.']}, {'end': 2173.193, 'segs': [{'end': 1156.822, 'src': 'embed', 'start': 1131.574, 'weight': 3, 'content': [{'end': 1137.317, 'text': 'So mind map is kind of like a lower level, more free hand way of organizing your thoughts.', 'start': 1131.574, 'duration': 5.743}, {'end': 1145.119, 'text': "And once you've drawn it, then you can start, uh, actually voicing your thoughts in terms of, you know, paragraphs.", 'start': 1137.937, 'duration': 7.182}, {'end': 1148.921, 'text': "It's a two dimensional aspect of layout too, right? Yeah.", 'start': 1145.38, 'duration': 3.541}, {'end': 1152.382, 'text': "And it's a kind of flower, I guess, you start.", 'start': 1149.561, 'duration': 2.821}, {'end': 1155.062, 'text': "There's usually, you want to start with a central concept.", 'start': 1152.842, 'duration': 2.22}, {'end': 1156.822, 'text': 'Yes And then you move out.', 'start': 1155.902, 'duration': 0.92}], 'summary': 'Mind map is a freehand way to organize thoughts, starting with a central concept and expanding outward.', 'duration': 25.248, 'max_score': 1131.574, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO41131574.jpg'}, {'end': 1291.695, 'src': 'embed', 'start': 1260.742, 'weight': 1, 'content': [{'end': 1262.804, 'text': "They're very strong semantic.", 'start': 1260.742, 'duration': 2.062}, {'end': 1269.331, 'text': 'It feels like the mind map forces you to be, semantically clear and specific.', 'start': 1263.284, 'duration': 6.047}, {'end': 1274.979, 'text': 'The bullet points list I have are sparse, disparate thoughts.', 'start': 1269.812, 'duration': 5.167}, {'end': 1283.967, 'text': 'that poetically represent a category, like motion, as opposed to saying motion.', 'start': 1276.519, 'duration': 7.448}, {'end': 1288.952, 'text': "So unfortunately, that's the same problem with the internet.", 'start': 1285.328, 'duration': 3.624}, {'end': 1291.695, 'text': "That's why the idea of semantic web is difficult to get.", 'start': 1288.992, 'duration': 2.703}], 'summary': 'Mind map enforces semantic clarity, but internet struggles with semantic representation.', 'duration': 30.953, 'max_score': 1260.742, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO41260742.jpg'}, {'end': 1391.972, 'src': 'embed', 'start': 1366.322, 'weight': 2, 'content': [{'end': 1372.965, 'text': 'You only have the concept of whether there is a train going from station A to station B.', 'start': 1366.322, 'duration': 6.643}, {'end': 1377.607, 'text': "And what we do in deep learning is that we're actually dealing with geometric spaces.", 'start': 1372.965, 'duration': 4.642}, {'end': 1385.11, 'text': 'We are dealing with concept vectors, word vectors, that have a distance between them, which is expressed in terms of that product.', 'start': 1377.727, 'duration': 7.383}, {'end': 1390.211, 'text': 'We are not really building topological models usually.', 'start': 1386.61, 'duration': 3.601}, {'end': 1391.972, 'text': "I think you're absolutely right.", 'start': 1390.792, 'duration': 1.18}], 'summary': 'Deep learning involves concept vectors with a distance between them, not topological models.', 'duration': 25.65, 'max_score': 1366.322, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO41366322.jpg'}, {'end': 2125.77, 'src': 'embed', 'start': 2099.098, 'weight': 0, 'content': [{'end': 2116.545, 'text': "So the goal of the paper is to clear up some longstanding misunderstandings about the way we've been conceptualizing intelligence in the AI community and in the way we've been evaluating progress in AI.", 'start': 2099.098, 'duration': 17.447}, {'end': 2125.77, 'text': "There's been a lot of progress recently in machine learning and people are extrapolating from that progress that we are about to solve general intelligence.", 'start': 2116.786, 'duration': 8.984}], 'summary': 'Clarifying misconceptions about intelligence in ai and evaluating recent progress in machine learning.', 'duration': 26.672, 'max_score': 2099.098, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO42099098.jpg'}], 'start': 987.368, 'title': 'Organizing thoughts and intelligence', 'summary': 'Covers mind mapping for organizing thoughts, the difference between topological and geometric spaces, and understanding intelligence. it emphasizes the free-form nature of mind maps, the importance of distance in geometric spaces for deep learning, and fundamental aspects of intelligence, such as adaptability and improvisation.', 'chapters': [{'end': 1347.431, 'start': 987.368, 'title': 'Mind mapping for organizing thoughts', 'summary': 'Discusses the concept of mind mapping for organizing thoughts, emphasizing the free-form nature of mind maps and their role in facilitating topological processing in the brain, with a comparison to hierarchical structures and semantic clarity.', 'duration': 360.063, 'highlights': ['Mind maps are a free-form way of organizing thoughts, allowing for associative connections and reorganization for more effective connectivity. The speaker explains that mind maps involve writing down key concepts and adding associative connections like a tree or a graph, allowing for reorganization to make more sense and be connected in a more effective way.', 'The speaker expresses concern about the implied hierarchy and categorization imperfections within mind maps, leading to paranoia and fear of being wrong. The speaker mentions becoming paranoid about the categorization imperfections and the fear of not having the proper hierarchy when creating mind maps, leading to a fear of being wrong.', 'The comparison between mind maps and syntactic structures highlights the lower-level, free-hand nature of mind maps in organizing thoughts. The speaker contrasts mind maps with syntactic structures, explaining that mind maps impose a more free-hand way of organizing thoughts, providing a lower-level, more free-hand approach in contrast to the more syntactic structure of writing down thoughts.', 'The discussion on semantic clarity and the role of mind maps in facilitating topological processing in the brain, emphasizing the associative nature of the brain and the suitability of topological space for encoding thoughts. The chapter touches upon the associative nature of the brain and suggests that a topological space is a better medium to encode thoughts than a geometric space, highlighting the role of mind maps in facilitating topological processing in the brain.']}, {'end': 1614.391, 'start': 1347.691, 'title': 'Difference between topological and geometric spaces', 'summary': 'Discusses the difference between topological and geometric spaces, emphasizing the importance of distance in geometric spaces and its fundamental role in deep learning, with a focus on concept vectors and the efficiency of acquiring new skills as the definition of intelligence.', 'duration': 266.7, 'highlights': ['Deep learning deals with geometric spaces, emphasizing the importance of distance between concept vectors, which is essential for differentiability and continuous aspects.', 'The efficiency with which one acquires new skills at tasks not previously known or prepared for is the definition of intelligence, emphasizing the role of learning in intelligence.', 'In the context of deep learning, topology must be embedded in a geometry to facilitate differentiability, highlighting the need for continuous spaces in deep learning.', 'The chapter delves into a vision of the future where super intelligent AIs may view humans as a historical civilization that no longer exists, with a detailed context of social media hashtags and the potential mistake of human existence in the name of progress.']}, {'end': 2173.193, 'start': 1614.691, 'title': 'Understanding intelligence and measure', 'summary': 'Discusses the fundamental aspects of intelligence, including adaptability, improvisation, generalization, and the distinction between the process of intelligence and its output, with the goal of providing a reliable and actionable measure of general intelligence for evaluating progress in ai.', 'duration': 558.502, 'highlights': ["The measure of intelligence is the ability to change, capturing the importance of adaptability and improvisation as key aspects of intelligence. Einstein's quote emphasizes the significance of the ability to change as a measure of intelligence, highlighting the importance of adaptability and improvisation.", 'The distinction between the process of intelligence and its output, emphasizing that the intelligence lies in the process of developing skills rather than the static program itself. The distinction between the intelligence process and its output is highlighted, emphasizing that the process of developing skills, rather than the static program itself, embodies intelligence.', 'The goal of the paper is to provide a reliable and actionable measure of general intelligence for evaluating progress in AI. The paper aims to offer a reliable and actionable measure of general intelligence to accurately evaluate progress in AI, emphasizing the need for a precise definition and measurement of general intelligence.']}], 'duration': 1185.825, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO4987368.jpg', 'highlights': ['The paper aims to offer a reliable and actionable measure of general intelligence to accurately evaluate progress in AI, emphasizing the need for a precise definition and measurement of general intelligence.', 'The measure of intelligence is the ability to change, capturing the importance of adaptability and improvisation as key aspects of intelligence.', 'In the context of deep learning, topology must be embedded in a geometry to facilitate differentiability, highlighting the need for continuous spaces in deep learning.', 'The discussion on semantic clarity and the role of mind maps in facilitating topological processing in the brain, emphasizing the associative nature of the brain and the suitability of topological space for encoding thoughts.', 'Deep learning deals with geometric spaces, emphasizing the importance of distance between concept vectors, which is essential for differentiability and continuous aspects.', 'The efficiency with which one acquires new skills at tasks not previously known or prepared for is the definition of intelligence, emphasizing the role of learning in intelligence.']}, {'end': 3414.628, 'segs': [{'end': 2427.812, 'src': 'embed', 'start': 2398.277, 'weight': 4, 'content': [{'end': 2403.339, 'text': 'but that had gained a lot of vitality recently with the rise of connectionism, in particular deep learning.', 'start': 2398.277, 'duration': 5.062}, {'end': 2407.161, 'text': 'And so today, deep learning is the dominant paradigm in AI.', 'start': 2404.239, 'duration': 2.922}, {'end': 2416.506, 'text': 'And I feel like lots of AI researchers are conceptualizing the mind via a deep learning metaphor.', 'start': 2408.381, 'duration': 8.125}, {'end': 2427.812, 'text': "Like. they see the mind as a kind of randomly initialized neural network that starts blank when you're born and then that gets trained via exposure to training data.", 'start': 2416.566, 'duration': 11.246}], 'summary': 'Deep learning has become the dominant paradigm in ai, conceptualizing the mind as a neural network trained on data.', 'duration': 29.535, 'max_score': 2398.277, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO42398277.jpg'}, {'end': 2486.348, 'src': 'embed', 'start': 2462.22, 'weight': 1, 'content': [{'end': 2473.67, 'text': "And to me I don't know you might disagree, but it's an open question whether, like like scaling size eventually might lead to incredible results.", 'start': 2462.22, 'duration': 11.45}, {'end': 2476.555, 'text': "to us mere humans will appear as if it's general.", 'start': 2473.67, 'duration': 2.885}, {'end': 2480.702, 'text': 'I mean, if you ask people who are seriously thinking about intelligence,', 'start': 2477.079, 'duration': 3.623}, {'end': 2486.348, 'text': 'they will definitely not say that all you need to do is like the mind is just in your network.', 'start': 2480.702, 'duration': 5.646}], 'summary': 'Scaling size may lead to incredible results in intelligence research.', 'duration': 24.128, 'max_score': 2462.22, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO42462220.jpg'}, {'end': 2721.412, 'src': 'embed', 'start': 2697.705, 'weight': 6, 'content': [{'end': 2707.308, 'text': 'So do you think GPT-3, 4, 5, GPT-10 will eventually like what do you think?', 'start': 2697.705, 'duration': 9.603}, {'end': 2708.088, 'text': "where's the ceiling??", 'start': 2707.308, 'duration': 0.78}, {'end': 2710.149, 'text': "Do you think you'll be able to reason??", 'start': 2708.328, 'duration': 1.821}, {'end': 2713.19, 'text': "No, that's a bad question.", 'start': 2710.169, 'duration': 3.021}, {'end': 2716.511, 'text': 'Like what is the ceiling is the better question.', 'start': 2714.61, 'duration': 1.901}, {'end': 2721.412, 'text': 'How well is it going to scale? How good is GPT-N going to be? Yeah.', 'start': 2716.531, 'duration': 4.881}], 'summary': 'Discussing the potential of gpt-3, 4, 5, 10 and their scaling capabilities.', 'duration': 23.707, 'max_score': 2697.705, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO42697705.jpg'}, {'end': 2831.762, 'src': 'embed', 'start': 2801.679, 'weight': 0, 'content': [{'end': 2804.141, 'text': 'Right, And so, for this reason,', 'start': 2801.679, 'duration': 2.462}, {'end': 2813.527, 'text': 'one thing that I thought was very interesting with GPT-3 is that you can pre-determine the answer it will give you by asking the question in specific way,', 'start': 2804.141, 'duration': 9.386}, {'end': 2821.513, 'text': "because it's very responsive to the way you ask the question, since it has no understanding of the content of the question.", 'start': 2813.527, 'duration': 7.986}, {'end': 2831.762, 'text': 'And if you ask the same question in two different ways that are basically adversarially engineered to produce certain answers,', 'start': 2823.595, 'duration': 8.167}], 'summary': 'Gpt-3 can be manipulated by asking questions in specific ways to pre-determine its answers.', 'duration': 30.083, 'max_score': 2801.679, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO42801679.jpg'}, {'end': 3146.46, 'src': 'embed', 'start': 3113.674, 'weight': 7, 'content': [{'end': 3114.574, 'text': "That's a lot of images.", 'start': 3113.674, 'duration': 0.9}, {'end': 3119.075, 'text': "That's like probably most publicly available images on the web at the time.", 'start': 3114.634, 'duration': 4.441}, {'end': 3128.357, 'text': 'And it was a very noisy dataset because the labels were not originally annotated by hand by humans.', 'start': 3121.116, 'duration': 7.241}, {'end': 3138.153, 'text': 'They were automatically derived from, like, tags on social media or just keywords in the same page as the image was found and so on.', 'start': 3128.457, 'duration': 9.696}, {'end': 3139.054, 'text': 'So it was very noisy.', 'start': 3138.173, 'duration': 0.881}, {'end': 3146.46, 'text': 'And it turned out that you could easily get a better model not just by training.', 'start': 3139.134, 'duration': 7.326}], 'summary': 'A dataset with a large number of noisy images was used for training.', 'duration': 32.786, 'max_score': 3113.674, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO43113674.jpg'}, {'end': 3255.367, 'src': 'embed', 'start': 3222.173, 'weight': 3, 'content': [{'end': 3226.695, 'text': 'for I think the semantic web papers in the 90s.', 'start': 3222.173, 'duration': 4.522}, {'end': 3232.298, 'text': "It's kind of the dream that the internet is full of rich, exciting information.", 'start': 3227.996, 'duration': 4.302}, {'end': 3237.601, 'text': 'Even just looking at Wikipedia, we should be able to use that as data for machines.', 'start': 3232.378, 'duration': 5.223}, {'end': 3241.162, 'text': "The information is not really in a format that's available to machines.", 'start': 3237.901, 'duration': 3.261}, {'end': 3244.544, 'text': "So no, I don't think the semantic web will ever work,", 'start': 3241.242, 'duration': 3.302}, {'end': 3255.367, 'text': 'simply because it would be a lot of work to provide that information in a structured form and there is not really any incentive for anyone to provide that work.', 'start': 3244.544, 'duration': 10.823}], 'summary': "Semantic web's potential hindered by lack of structured data and incentives.", 'duration': 33.194, 'max_score': 3222.173, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO43222173.jpg'}, {'end': 3294.29, 'src': 'embed', 'start': 3266.39, 'weight': 2, 'content': [{'end': 3276.012, 'text': 'So GPT-3 is actually a bigger step in the direction of making the knowledge of the web available to machines than the semantic web was.', 'start': 3266.39, 'duration': 9.622}, {'end': 3289.126, 'text': "Yeah, perhaps in a human-centric sense, it feels like GPT-3 hasn't learned anything that could be used to reason.", 'start': 3276.673, 'duration': 12.453}, {'end': 3292.63, 'text': 'But that might be just the early days.', 'start': 3290.448, 'duration': 2.182}, {'end': 3294.29, 'text': "Yeah, I think that's correct.", 'start': 3292.89, 'duration': 1.4}], 'summary': 'Gpt-3 is a big step in web knowledge for machines, but early for reasoning.', 'duration': 27.9, 'max_score': 3266.39, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO43266390.jpg'}], 'start': 2173.593, 'title': 'Views and challenges in ai', 'summary': "Discusses two views of intelligence in ai, static vs. adaptable, and explores gpt-3's impact, challenges in scaling, and limitations in deep learning models, providing insights into future ai development.", 'chapters': [{'end': 2541.941, 'start': 2173.593, 'title': 'Two views of intelligence', 'summary': 'Discusses two divergent views of intelligence: the static, special-purpose mechanisms shaped by evolutionary psychology and the brain as a blank slate that absorbs knowledge and skills from experience, with the rise of deep learning as the dominant paradigm in ai.', 'duration': 368.348, 'highlights': ['The rise of deep learning as the dominant paradigm in AI and the conceptualization of the mind via a deep learning metaphor. The chapter highlights the dominance of deep learning in AI and the conceptualization of the mind as a randomly initialized neural network that gets trained via exposure to training data.', 'The assessment of the different ways of thinking about intelligence and evaluating progress in AI, shaped by two views of the human mind: evolutionary psychology view and the brain as a blank slate. The chapter emphasizes the assessment of different views of intelligence, including the evolutionary psychology view and the brain as a blank slate, which reflects the complexity of life experience and absorbs knowledge and skills from the outside world.', 'The consideration of learning as not important in early AI research and the rise of machine learning in the 1980s. Early AI research did not consider learning to be important, and it was not featured in AI textbooks until the 1980s with the rise of machine learning.']}, {'end': 2751.274, 'start': 2542.722, 'title': "Gpt-3's impact and potential", 'summary': 'Discusses the emergence of gpt-3, its applications, concerns about its capabilities, and the potential for future models like gpt-n to improve context-awareness and text plausibility.', 'duration': 208.552, 'highlights': ["GPT-3's potential to learn new tasks after being shown a few examples is novel and interesting, but not entirely convincing. The idea of GPT-3 being able to learn new tasks after being shown a few examples is intriguing, but there are doubts about whether it truly accomplishes this or simply engages in pattern matching based on its extensive training data.", "GPT-3 could be seen as a giant associative memory and a querying machine, with the potential for intelligence to be largely based on this aspect. There's a perspective that a significant chunk of intelligence could be attributed to GPT-3 functioning as a giant associative memory and a querying machine, which could impact the potential scalability and capabilities of future models.", 'Expectations for future models like GPT-N to improve context-awareness and text plausibility through larger-scale training. The anticipation is that future models like GPT-N will enhance context-awareness and text plausibility through larger-scale training, leading to monotonically increasing performance in generating increasingly more plausible text in context.']}, {'end': 3035.502, 'start': 2751.274, 'title': 'Challenges of gpt-3 scaling', 'summary': 'Discusses the limitations of gpt-3 in generating plausible text, the lack of constraints leading to factual inaccuracies, susceptibility to adversarial attacks, and the need for explicit programming to overcome these limitations, while considering the challenges of scaling up gpt-3 with more data and parameters.', 'duration': 284.228, 'highlights': ['GPT-3 lacks constraints on factualness and consistency, leading to factually untrue and self-contradictory statements.', 'It is susceptible to adversarial attacks, providing contradictory answers when asked questions in different ways.', 'The need to write explicit reasoning programs over the latent space of these models to overcome the difficulty in getting GPT-3 to perform as desired.', 'The bottleneck in scaling GPT-3 models is the trained data, as it is already trained on a vast amount of data from the web, making it challenging to train on significantly more data.']}, {'end': 3414.628, 'start': 3035.822, 'title': 'Challenges in deep learning models', 'summary': 'Discusses the challenges in deep learning models, such as addressing the bottleneck in training data, the impact of data quality on model performance, and the limitations of gpt-3 in reasoning and adaptation to novel situations.', 'duration': 378.806, 'highlights': ['The bottleneck in deep learning models is the training data quality, as demonstrated by the impact of training on a smaller dataset with higher quality annotations resulting in a better model and less training time.', 'GPT-3 can produce an illusion of reasoning by reproducing patterns from the web, but it lacks the capability to adapt to genuinely new situations, demonstrating the limitations of its reasoning ability.', 'The quality of the data significantly impacts the performance of deep learning models, as evidenced by a model trained on a large but noisy dataset, which performed better when trained on a smaller dataset with higher quality annotations made by humans.']}], 'duration': 1241.035, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO42173593.jpg', 'highlights': ['The dominance of deep learning in AI and the conceptualization of the mind as a randomly initialized neural network that gets trained via exposure to training data.', 'The assessment of different views of intelligence, including the evolutionary psychology view and the brain as a blank slate, reflecting the complexity of life experience and absorption of knowledge and skills from the outside world.', 'Early AI research did not consider learning to be important, and it was not featured in AI textbooks until the 1980s with the rise of machine learning.', 'The idea of GPT-3 being able to learn new tasks after being shown a few examples is intriguing, but there are doubts about whether it truly accomplishes this or simply engages in pattern matching based on its extensive training data.', "There's a perspective that a significant chunk of intelligence could be attributed to GPT-3 functioning as a giant associative memory and a querying machine, impacting the potential scalability and capabilities of future models.", 'Anticipation that future models like GPT-N will enhance context-awareness and text plausibility through larger-scale training, leading to monotonically increasing performance in generating increasingly more plausible text in context.', 'GPT-3 lacks constraints on factualness and consistency, leading to factually untrue and self-contradictory statements.', 'Susceptibility to adversarial attacks, providing contradictory answers when asked questions in different ways.', 'The bottleneck in scaling GPT-3 models is the trained data, as it is already trained on a vast amount of data from the web, making it challenging to train on significantly more data.', 'The bottleneck in deep learning models is the training data quality, as demonstrated by the impact of training on a smaller dataset with higher quality annotations resulting in a better model and less training time.', 'GPT-3 can produce an illusion of reasoning by reproducing patterns from the web, but it lacks the capability to adapt to genuinely new situations, demonstrating the limitations of its reasoning ability.', 'The quality of the data significantly impacts the performance of deep learning models, as evidenced by a model trained on a large but noisy dataset, which performed better when trained on a smaller dataset with higher quality annotations made by humans.']}, {'end': 4230.405, 'segs': [{'end': 3441.694, 'src': 'embed', 'start': 3415.712, 'weight': 0, 'content': [{'end': 3429.103, 'text': 'Google had a paper a couple of years back showing that something like 30 million different road situations were actually completely insufficient to train a driving model.', 'start': 3415.712, 'duration': 13.391}, {'end': 3432.766, 'text': "It wasn't even L2, right? And that's a lot of data.", 'start': 3429.944, 'duration': 2.822}, {'end': 3441.694, 'text': "That's a lot more data than the 20 or 30 hours of driving that a human needs to learn to drive, given the knowledge they've already accumulated.", 'start': 3432.806, 'duration': 8.888}], 'summary': "Google's paper found that 30 million road situations were insufficient to train a driving model, much more data than the 20-30 hours needed for humans.", 'duration': 25.982, 'max_score': 3415.712, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO43415712.jpg'}, {'end': 3525.3, 'src': 'heatmap', 'start': 3415.712, 'weight': 0.759, 'content': [{'end': 3429.103, 'text': 'Google had a paper a couple of years back showing that something like 30 million different road situations were actually completely insufficient to train a driving model.', 'start': 3415.712, 'duration': 13.391}, {'end': 3432.766, 'text': "It wasn't even L2, right? And that's a lot of data.", 'start': 3429.944, 'duration': 2.822}, {'end': 3441.694, 'text': "That's a lot more data than the 20 or 30 hours of driving that a human needs to learn to drive, given the knowledge they've already accumulated.", 'start': 3432.806, 'duration': 8.888}, {'end': 3444.324, 'text': 'Well, let me ask you on that topic.', 'start': 3441.983, 'duration': 2.341}, {'end': 3454.267, 'text': 'Elon Musk, Tesla Autopilot, one of the only companies I believe is really pushing for a learning-based approach.', 'start': 3445.644, 'duration': 8.623}, {'end': 3462.47, 'text': 'Are you skeptical that that kind of network can achieve level four? L4 is probably achievable.', 'start': 3454.808, 'duration': 7.662}, {'end': 3464.031, 'text': 'L5 probably not.', 'start': 3462.83, 'duration': 1.201}, {'end': 3470.853, 'text': "What's the distinction there? Is L5 is completely, you can just fall asleep? Yeah, L5 is basically human level.", 'start': 3464.511, 'duration': 6.342}, {'end': 3474.714, 'text': 'Well, driving, you have to be careful saying human level, because like..', 'start': 3471.173, 'duration': 3.541}, {'end': 3475.974, 'text': 'Yeah, there are all kinds of drivers.', 'start': 3474.714, 'duration': 1.26}, {'end': 3485.856, 'text': "Yeah, that's the clearest example of like, you know, cars will most likely be much safer than humans in many situations where humans fail.", 'start': 3477.274, 'duration': 8.582}, {'end': 3487.837, 'text': "It's the vice versa.", 'start': 3486.717, 'duration': 1.12}, {'end': 3495.462, 'text': "So I'll tell you you know the thing is the amounts of trained data you would need to anticipate,", 'start': 3488.917, 'duration': 6.545}, {'end': 3505.528, 'text': "for pretty much every possible situation you'll encounter in the real world is such that it's not entirely unrealistic to think that at some point in the future,", 'start': 3495.462, 'duration': 10.066}, {'end': 3511.932, 'text': "we'll develop a system that's trained on enough data, especially provided that we can simulate a lot of that data.", 'start': 3505.528, 'duration': 6.404}, {'end': 3516.275, 'text': "We don't necessarily need actual cars on the road for everything.", 'start': 3512.412, 'duration': 3.863}, {'end': 3525.3, 'text': "But it's a massive effort and it turns out you can create a system that's much more adaptive, that can generalize much better,", 'start': 3517.756, 'duration': 7.544}], 'summary': 'Google found 30m road situations insufficient to train driving model. l5 may not be achievable.', 'duration': 109.588, 'max_score': 3415.712, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO43415712.jpg'}, {'end': 3722.801, 'src': 'embed', 'start': 3695.663, 'weight': 1, 'content': [{'end': 3702.825, 'text': 'despite having had no contact with the novel complexity that is contained in this environment.', 'start': 3695.663, 'duration': 7.162}, {'end': 3713.869, 'text': "And that novel complexity is not just an interpolation over the situations that you've encountered previously, like learning to drive in the US.", 'start': 3704.326, 'duration': 9.543}, {'end': 3722.801, 'text': 'I would say the reason I ask is one of the most interesting tests of intelligence we have today actively, which is driving.', 'start': 3715.17, 'duration': 7.631}], 'summary': 'Novel complexity challenges intelligence in driving tests.', 'duration': 27.138, 'max_score': 3695.663, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO43695663.jpg'}, {'end': 4230.405, 'src': 'embed', 'start': 4203.699, 'weight': 2, 'content': [{'end': 4213.131, 'text': 'So if your goal is to create AIs that are more human-like, then it will be super valuable, obviously, to have a test.', 'start': 4203.699, 'duration': 9.432}, {'end': 4215.714, 'text': "that's universal.", 'start': 4214.272, 'duration': 1.442}, {'end': 4227.422, 'text': 'that applies to both AIs and humans, so that you could establish a comparison between the two, that you could tell exactly how intelligent,', 'start': 4215.714, 'duration': 11.708}, {'end': 4230.405, 'text': 'in terms of human intelligence, a given system is.', 'start': 4227.422, 'duration': 2.983}], 'summary': 'Establish universal test for comparing human-like ai intelligence.', 'duration': 26.706, 'max_score': 4203.699, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO44203699.jpg'}], 'start': 3415.712, 'title': 'Challenges in training autonomous vehicles and intelligence in driving', 'summary': 'Discusses the challenges in training autonomous vehicles, emphasizing the amount of data required, the potential of learning-based approaches, and the need for explicit models and reasoning in ai systems. it also explores the test of intelligence in driving, the limitations of end-to-end deep learning models, the need for efficient generalization in ai, and the measure of intelligence as the efficiency of generalization.', 'chapters': [{'end': 3673.175, 'start': 3415.712, 'title': 'Challenges in training autonomous vehicles', 'summary': 'Discusses the challenges in training autonomous vehicles, with a focus on the amount of data required, the potential of learning-based approaches, and the need for explicit models and reasoning in ai systems.', 'duration': 257.463, 'highlights': ['The chapter discusses the challenges in training autonomous vehicles, with a focus on the amount of data required, the potential of learning-based approaches, and the need for explicit models and reasoning in AI systems. Focuses on challenges in training autonomous vehicles, amount of data required, learning-based approaches, and need for explicit models and reasoning in AI systems.', "Google's paper showed that around 30 million different road situations were insufficient to train a driving model, which is more data than the 20 or 30 hours of driving a human needs to learn. Google's paper highlighted the insufficiency of around 30 million road situations to train a driving model in comparison to the 20-30 hours of driving required for humans.", "Elon Musk's Tesla Autopilot adopts a learning-based approach, with skepticism about achieving level 5 autonomy but potential for level 4, indicating the distinction between human and machine capabilities in driving. Tesla Autopilot adopts a learning-based approach, skepticism about achieving level 5 autonomy, potential for level 4, distinction between human and machine capabilities in driving.", 'Explicit models of the surroundings of the car and deep learning for perception are emphasized for creating a more adaptive and generalizable system for autonomous vehicles. Emphasis on explicit models and deep learning for perception to create adaptive and generalizable autonomous vehicle systems.', 'Strong generalization in AI systems tends to come from explicit models and abstractions, not from weak abstractions learned by neural networks, highlighting the limitations of deep learning in reasoning. Strong generalization in AI systems comes from explicit models and abstractions, not from weak abstractions learned by neural networks, illustrating the limitations of deep learning in reasoning.']}, {'end': 4230.405, 'start': 3674.156, 'title': 'Intelligence and driving', 'summary': 'Discusses the test of intelligence in driving, the limitations of end-to-end deep learning models, the need for efficient generalization in ai, and the measure of intelligence as the efficiency of generalization.', 'duration': 556.249, 'highlights': ['The chapter discusses the test of intelligence in driving, the limitations of end-to-end deep learning models, the need for efficient generalization in AI, and the measure of intelligence as the efficiency of generalization. The chapter delves into the test of intelligence in driving, emphasizing the limitations of end-to-end deep learning models, the necessity of efficient generalization in AI, and defining intelligence as the efficiency of generalization.', 'The efficiency with which you can adapt to truly new situations defines intelligence, not mere lookup tables or sets of rules. Intelligence is defined as the efficiency with which one adapts to truly new situations, not reliant on lookup tables or sets of rules.', 'A smart agent efficiently utilizes little information and prior knowledge to cover a large area of potential situations, demonstrating intelligence. Smart agents efficiently utilize minimal information and prior knowledge to cover a broad range of potential situations, showcasing intelligence.']}], 'duration': 814.693, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO43415712.jpg', 'highlights': ["Google's paper showed that around 30 million different road situations were insufficient to train a driving model, which is more data than the 20 or 30 hours of driving a human needs to learn.", 'Tesla Autopilot adopts a learning-based approach, skepticism about achieving level 5 autonomy, potential for level 4, distinction between human and machine capabilities in driving.', 'Strong generalization in AI systems tends to come from explicit models and abstractions, not from weak abstractions learned by neural networks, highlighting the limitations of deep learning in reasoning.', 'The efficiency with which you can adapt to truly new situations defines intelligence, not mere lookup tables or sets of rules.', 'A smart agent efficiently utilizes little information and prior knowledge to cover a large area of potential situations, demonstrating intelligence.']}, {'end': 4913.642, 'segs': [{'end': 4389.611, 'src': 'embed', 'start': 4358.806, 'weight': 1, 'content': [{'end': 4372.241, 'text': 'And your priors are things like, well, Go is a game on a 2D grid, and we have lots of hard-coded priors about the organization of 2D space.', 'start': 4358.806, 'duration': 13.435}, {'end': 4374.885, 'text': 'And the rules of how..', 'start': 4373.363, 'duration': 1.522}, {'end': 4379.887, 'text': 'the dynamics of this, the physics of this game in the studio space.', 'start': 4376.365, 'duration': 3.522}, {'end': 4383.469, 'text': 'Yes And the idea that what winning is.', 'start': 4380.027, 'duration': 3.442}, {'end': 4384.989, 'text': 'Yes, exactly.', 'start': 4384.389, 'duration': 0.6}, {'end': 4389.611, 'text': 'And all other board games can also share some similarities with Go.', 'start': 4385.63, 'duration': 3.981}], 'summary': 'Priors and dynamics of go game on 2d grid, with similarities to other board games.', 'duration': 30.805, 'max_score': 4358.806, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO44358806.jpg'}, {'end': 4522.687, 'src': 'embed', 'start': 4491.834, 'weight': 2, 'content': [{'end': 4494.777, 'text': 'you know what, what, what are the priors it brings to the table?', 'start': 4491.834, 'duration': 2.943}, {'end': 4498.42, 'text': "So uh, it's a field with a with a fairly long history.", 'start': 4495.457, 'duration': 2.963}, {'end': 4502.147, 'text': "Um, It's so.", 'start': 4498.44, 'duration': 3.707}, {'end': 4509.034, 'text': 'you know, psychology sometimes gets a bad reputation for not having very reproducible results,', 'start': 4502.147, 'duration': 6.887}, {'end': 4513.419, 'text': 'and some psychometrics has actually some fairly solidly reproducible results.', 'start': 4509.034, 'duration': 4.385}, {'end': 4522.687, 'text': 'So the ideal goals of the field is, you know, a test should be be reliable, which is a notion tied to reproducibility.', 'start': 4514.2, 'duration': 8.487}], 'summary': 'Psychometrics aims for reliable, reproducible test results in psychology.', 'duration': 30.853, 'max_score': 4491.834, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO44491834.jpg'}, {'end': 4724.338, 'src': 'heatmap', 'start': 4624.582, 'weight': 0.842, 'content': [{'end': 4633.729, 'text': 'When you run these very different tests at scale, what you start seeing is that there are clusters of correlations among test results.', 'start': 4624.582, 'duration': 9.147}, {'end': 4644.817, 'text': 'So for instance, if you look at homework at school, you will see that people who do well at math are also likely statistically to do well in physics.', 'start': 4634.169, 'duration': 10.648}, {'end': 4655.661, 'text': "And what's more, people who do well at math and physics are also statistically likely to do well in things that sound completely unrelated,", 'start': 4645.658, 'duration': 10.003}, {'end': 4657.882, 'text': 'like writing an English essay, for instance.', 'start': 4655.661, 'duration': 2.221}, {'end': 4667.225, 'text': 'And so when you see clusters of correlations in statistical terms, you would explain them with a latent variable.', 'start': 4658.642, 'duration': 8.583}, {'end': 4669.427, 'text': 'And the latent variable that would, for instance,', 'start': 4667.745, 'duration': 1.682}, {'end': 4676.516, 'text': 'explain the relationship between being good at math and being good at physics would be cognitive ability.', 'start': 4669.427, 'duration': 7.089}, {'end': 4680.821, 'text': 'And the g-factor is the latent variable.', 'start': 4677.337, 'duration': 3.484}, {'end': 4690.351, 'text': 'that explains the fact that every test of intelligence that you can come up with, results on this test end up being correlated.', 'start': 4680.821, 'duration': 9.53}, {'end': 4697.754, 'text': 'So there is some single, unique variable that explains these correlations.', 'start': 4690.511, 'duration': 7.243}, {'end': 4698.635, 'text': "That's the g-factor.", 'start': 4697.794, 'duration': 0.841}, {'end': 4700.336, 'text': "So it's a statistical construct.", 'start': 4698.935, 'duration': 1.401}, {'end': 4704.458, 'text': "It's not really something you can directly measure, for instance, in a person.", 'start': 4700.376, 'duration': 4.082}, {'end': 4706.3, 'text': "But it's there.", 'start': 4705.599, 'duration': 0.701}, {'end': 4707.18, 'text': "But it's there.", 'start': 4706.64, 'duration': 0.54}, {'end': 4708.702, 'text': "It's there at scale.", 'start': 4707.281, 'duration': 1.421}, {'end': 4713.026, 'text': "And that's also one thing I want to mention about psychometrics.", 'start': 4708.822, 'duration': 4.204}, {'end': 4720.094, 'text': 'Like, you know, when you talk about measuring intelligence in humans, for instance, some people get a little bit worried.', 'start': 4713.567, 'duration': 6.527}, {'end': 4721.936, 'text': 'They will say, you know, that sounds dangerous.', 'start': 4720.114, 'duration': 1.822}, {'end': 4724.338, 'text': 'Maybe that sounds potentially discriminatory and so on.', 'start': 4721.976, 'duration': 2.362}], 'summary': 'Clusters of correlations in test results reveal latent variables like cognitive ability, as seen in the g-factor, a statistical construct explaining intelligence correlations at scale.', 'duration': 99.756, 'max_score': 4624.582, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO44624582.jpg'}, {'end': 4734.607, 'src': 'embed', 'start': 4698.935, 'weight': 3, 'content': [{'end': 4700.336, 'text': "So it's a statistical construct.", 'start': 4698.935, 'duration': 1.401}, {'end': 4704.458, 'text': "It's not really something you can directly measure, for instance, in a person.", 'start': 4700.376, 'duration': 4.082}, {'end': 4706.3, 'text': "But it's there.", 'start': 4705.599, 'duration': 0.701}, {'end': 4707.18, 'text': "But it's there.", 'start': 4706.64, 'duration': 0.54}, {'end': 4708.702, 'text': "It's there at scale.", 'start': 4707.281, 'duration': 1.421}, {'end': 4713.026, 'text': "And that's also one thing I want to mention about psychometrics.", 'start': 4708.822, 'duration': 4.204}, {'end': 4720.094, 'text': 'Like, you know, when you talk about measuring intelligence in humans, for instance, some people get a little bit worried.', 'start': 4713.567, 'duration': 6.527}, {'end': 4721.936, 'text': 'They will say, you know, that sounds dangerous.', 'start': 4720.114, 'duration': 1.822}, {'end': 4724.338, 'text': 'Maybe that sounds potentially discriminatory and so on.', 'start': 4721.976, 'duration': 2.362}, {'end': 4725.86, 'text': "And they're not wrong.", 'start': 4724.438, 'duration': 1.422}, {'end': 4734.607, 'text': "And the thing is, personally, I'm not interested in psychometrics as a way to characterize one individual person.", 'start': 4726.68, 'duration': 7.927}], 'summary': 'Psychometrics is a statistical construct that can be worrying and potentially discriminatory when used to measure intelligence in individuals.', 'duration': 35.672, 'max_score': 4698.935, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO44698935.jpg'}, {'end': 4776.61, 'src': 'embed', 'start': 4745.036, 'weight': 0, 'content': [{'end': 4750.3, 'text': 'I think psychometrics is most useful as a statistical tool.', 'start': 4745.036, 'duration': 5.264}, {'end': 4751.602, 'text': "So it's most useful at scale.", 'start': 4750.32, 'duration': 1.282}, {'end': 4760.645, 'text': "It's most useful when you start getting test results for a large number of people and you start cross-correlating these test results,", 'start': 4752.582, 'duration': 8.063}, {'end': 4769.768, 'text': 'because that gives you information about the structure of the human mind, in particular about the structure of human cognitive abilities.', 'start': 4760.645, 'duration': 9.123}, {'end': 4776.61, 'text': "So at scale, psychometrics paints a certain picture of the human mind, and that's interesting.", 'start': 4769.848, 'duration': 6.762}], 'summary': 'Psychometrics is most useful at scale for cross-correlating test results for a large number of people to gain insight into the structure of cognitive abilities.', 'duration': 31.574, 'max_score': 4745.036, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO44745036.jpg'}], 'start': 4230.465, 'title': 'Intelligence measurement challenges', 'summary': 'Addresses the challenges in comparing artificial and human intelligence, emphasizing the need to control for priors and experience, and discusses the g factor and its relevance to understanding human cognitive abilities.', 'chapters': [{'end': 4582.147, 'start': 4230.465, 'title': 'Constraints in measuring artificial and human intelligence', 'summary': 'Discusses the challenges in comparing the intelligence of artificial systems and humans, emphasizing the need to control for priors and experience in intelligence testing, and the principles of creating reliable, valid, standardized, and unbiased psychometric tests.', 'duration': 351.682, 'highlights': ['The importance of controlling for priors and experience in comparing the intelligence of artificial systems and humans, emphasizing the need for both to start from the same set of knowledge priors and control for training data. N/A', 'Definition and distinction between priors (pre-learning information about a task) and experience (acquired knowledge), using the example of playing Go to illustrate the concept. N/A', 'Explanation of psychometrics as the subfield of psychology that measures and quantifies aspects of the human mind, including cognitive abilities, intelligence, and personality traits, and the principles of creating reliable, valid, standardized, and unbiased psychometric tests. N/A']}, {'end': 4913.642, 'start': 4582.147, 'title': 'Understanding the g factor in intelligence', 'summary': 'Discusses the concept of the g factor, a statistical construct that explains the correlations among different tests of intelligence, and its relevance to understanding the structure of human cognitive abilities, highlighting the chc theory and its impact on psychometrics.', 'duration': 331.495, 'highlights': ['The G factor is a latent variable that explains the relationship between different aspects of intelligence, and it is observed through clusters of correlations among test results. The G factor serves as a latent variable that explains the correlations among different aspects of intelligence, as observed through clusters of correlations among test results.', 'Psychometrics is most useful as a statistical tool at scale, providing insights into the structure of human cognitive abilities and its relevance to AI. Psychometrics is most valuable as a statistical tool at scale, offering insights into the structure of human cognitive abilities and its relevance to AI.', 'The CHC theory describes a hierarchy of cognitive abilities with the G factor at the top, followed by broad and narrow cognitive abilities, emerging from statistical analyses of IQ test results. The CHC theory outlines a hierarchy of cognitive abilities with the G factor at the top, followed by broad and narrow cognitive abilities, derived from statistical analyses of IQ test results.']}], 'duration': 683.177, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO44230465.jpg', 'highlights': ['The G factor serves as a latent variable that explains the correlations among different aspects of intelligence, as observed through clusters of correlations among test results.', 'The CHC theory outlines a hierarchy of cognitive abilities with the G factor at the top, followed by broad and narrow cognitive abilities, derived from statistical analyses of IQ test results.', 'Psychometrics is most valuable as a statistical tool at scale, offering insights into the structure of human cognitive abilities and its relevance to AI.', 'The importance of controlling for priors and experience in comparing the intelligence of artificial systems and humans, emphasizing the need for both to start from the same set of knowledge priors and control for training data.']}, {'end': 6255.766, 'segs': [{'end': 5333.076, 'src': 'embed', 'start': 5306.212, 'weight': 5, 'content': [{'end': 5316.439, 'text': 'is a question where the input prompt is very surprising and unexpected given the training examples.', 'start': 5306.212, 'duration': 10.227}, {'end': 5320.062, 'text': "Just even the nature of the patterns that you're observing in the input prompt.", 'start': 5316.519, 'duration': 3.543}, {'end': 5322.844, 'text': "For instance, let's say you have a rotation problem.", 'start': 5320.202, 'duration': 2.642}, {'end': 5325.386, 'text': 'You must rotate the shape by 90 degrees.', 'start': 5323.324, 'duration': 2.062}, {'end': 5333.076, 'text': 'If I give you two examples and then I give you one prompt, which is actually one of the two training examples,', 'start': 5326.807, 'duration': 6.269}], 'summary': 'Addressing surprising and unexpected input prompts in training examples for pattern recognition tasks.', 'duration': 26.864, 'max_score': 5306.212, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO45306212.jpg'}, {'end': 5468.416, 'src': 'heatmap', 'start': 5365.16, 'weight': 0.869, 'content': [{'end': 5371.403, 'text': "So consider, I don't know, you're teaching a class on quantum physics or something.", 'start': 5365.16, 'duration': 6.243}, {'end': 5383.366, 'text': 'Um, if, uh, if you wanted to kind of test the understanding that students have of the material, you would come up with.', 'start': 5372.303, 'duration': 11.063}, {'end': 5385.207, 'text': 'uh, an exam.', 'start': 5383.366, 'duration': 1.841}, {'end': 5391.068, 'text': "uh, that's very different from anything they've seen like on the internet when they were cramming.", 'start': 5385.207, 'duration': 5.861}, {'end': 5396.53, 'text': 'uh, on the other hand, if you wanted to make it easy, you would just give them something that.', 'start': 5391.068, 'duration': 5.462}, {'end': 5406.637, 'text': "are very similar to the mock exams that they've taken, something that's just a simple interpolation of questions that they've already seen.", 'start': 5397.41, 'duration': 9.227}, {'end': 5409.18, 'text': 'And so that would be an easy exam.', 'start': 5407.478, 'duration': 1.702}, {'end': 5411.501, 'text': "It's very similar to what you've been trained on.", 'start': 5409.38, 'duration': 2.121}, {'end': 5419.067, 'text': 'And a difficult exam is one that really probes your understanding, because it forces you to improvise.', 'start': 5412.082, 'duration': 6.985}, {'end': 5424.37, 'text': 'it forces you to do things that are different from what you were exposed to before.', 'start': 5419.067, 'duration': 5.303}, {'end': 5432.635, 'text': "So that said, it doesn't mean that the exam that requires improvisation is intrinsically hard, right?", 'start': 5424.79, 'duration': 7.845}, {'end': 5440.36, 'text': "Because maybe you're a quantum physics expert, so when you take the exam, this is actually stuff that, despite being new to the students,", 'start': 5432.695, 'duration': 7.665}, {'end': 5441.881, 'text': "it's not new to you, right?", 'start': 5440.36, 'duration': 1.521}, {'end': 5454.107, 'text': 'It can only be difficult with respect to what the test-taker already knows and with respect to the information that the test-taker has about the task.', 'start': 5443.041, 'duration': 11.066}, {'end': 5462.592, 'text': "That's what I mean by controlling for priors, the information you bring to the table, and experience, which is the training data.", 'start': 5455.248, 'duration': 7.344}, {'end': 5468.416, 'text': 'In the case of the quantum physics exam, that would be, uh, all the the,', 'start': 5463.352, 'duration': 5.064}], 'summary': 'Quantum physics exams can be easy or difficult based on familiarity and improvisation, testing understanding and knowledge.', 'duration': 103.256, 'max_score': 5365.16, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO45365160.jpg'}, {'end': 5432.635, 'src': 'embed', 'start': 5385.207, 'weight': 0, 'content': [{'end': 5391.068, 'text': "uh, that's very different from anything they've seen like on the internet when they were cramming.", 'start': 5385.207, 'duration': 5.861}, {'end': 5396.53, 'text': 'uh, on the other hand, if you wanted to make it easy, you would just give them something that.', 'start': 5391.068, 'duration': 5.462}, {'end': 5406.637, 'text': "are very similar to the mock exams that they've taken, something that's just a simple interpolation of questions that they've already seen.", 'start': 5397.41, 'duration': 9.227}, {'end': 5409.18, 'text': 'And so that would be an easy exam.', 'start': 5407.478, 'duration': 1.702}, {'end': 5411.501, 'text': "It's very similar to what you've been trained on.", 'start': 5409.38, 'duration': 2.121}, {'end': 5419.067, 'text': 'And a difficult exam is one that really probes your understanding, because it forces you to improvise.', 'start': 5412.082, 'duration': 6.985}, {'end': 5424.37, 'text': 'it forces you to do things that are different from what you were exposed to before.', 'start': 5419.067, 'duration': 5.303}, {'end': 5432.635, 'text': "So that said, it doesn't mean that the exam that requires improvisation is intrinsically hard, right?", 'start': 5424.79, 'duration': 7.845}], 'summary': 'Different exam types: easy=known questions, hard=improvisation challenge', 'duration': 47.428, 'max_score': 5385.207, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO45385207.jpg'}, {'end': 5596.145, 'src': 'embed', 'start': 5566.9, 'weight': 1, 'content': [{'end': 5572.984, 'text': "Like there's a kind of intuitive simplicity and elegance to the correct solution.", 'start': 5566.9, 'duration': 6.084}, {'end': 5578.368, 'text': 'Yes I am personally not a fan of ambiguity in test questions, actually.', 'start': 5573.004, 'duration': 5.364}, {'end': 5584.673, 'text': 'But I think you can have difficulty without requiring ambiguity simply by making the test.', 'start': 5578.728, 'duration': 5.945}, {'end': 5589.257, 'text': 'require a lot of extrapolation over the training examples.', 'start': 5585.673, 'duration': 3.584}, {'end': 5596.145, 'text': 'But the beautiful question is difficult, but gives away everything when you give the training example.', 'start': 5589.498, 'duration': 6.647}], 'summary': 'Difficulty without ambiguity by requiring extrapolation over training examples.', 'duration': 29.245, 'max_score': 5566.9, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO45566900.jpg'}, {'end': 5643.772, 'src': 'embed', 'start': 5616.318, 'weight': 2, 'content': [{'end': 5623.502, 'text': 'I think an ideal test of human and machine intelligence is a test that is actionable.', 'start': 5616.318, 'duration': 7.184}, {'end': 5631.426, 'text': 'that highlights the need for progress and that highlights the direction in which you should be making progress.', 'start': 5624.402, 'duration': 7.024}, {'end': 5637.189, 'text': "I think we'll talk about the Arc Challenge and the test you've constructed, and you have these elegant examples.", 'start': 5631.546, 'duration': 5.643}, {'end': 5643.772, 'text': "I think that highlight, like, this is really easy for us humans, but it's really hard for machines.", 'start': 5637.209, 'duration': 6.563}], 'summary': 'Ideal test of human and machine intelligence: actionable and highlights progress direction.', 'duration': 27.454, 'max_score': 5616.318, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO45616318.jpg'}, {'end': 5837.546, 'src': 'embed', 'start': 5816.129, 'weight': 7, 'content': [{'end': 5825.714, 'text': 'So for instance, it should not be possible to brute force the space of possible questions, right? To pre-generate every possible question and answer.', 'start': 5816.129, 'duration': 9.585}, {'end': 5834.663, 'text': 'Um, so it should be tasks that cannot be anticipated, not just by the system itself, but by the creators of the system.', 'start': 5826.614, 'duration': 8.049}, {'end': 5836.325, 'text': 'Right Yeah.', 'start': 5835.143, 'duration': 1.182}, {'end': 5837.546, 'text': "You know, what's fascinating.", 'start': 5836.605, 'duration': 0.941}], 'summary': 'System should handle unanticipated tasks, not brute force every possible question.', 'duration': 21.417, 'max_score': 5816.129, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO45816129.jpg'}, {'end': 5892.661, 'src': 'embed', 'start': 5864.301, 'weight': 3, 'content': [{'end': 5870.124, 'text': 'So the the next step is like once you have those priors, how do you use them to, uh, solve a novel task?', 'start': 5864.301, 'duration': 5.823}, {'end': 5875.486, 'text': 'but like just even making the priors explicit is a really difficult and really powerful step.', 'start': 5870.124, 'duration': 5.362}, {'end': 5884.37, 'text': "And, and that that's like visually beautiful and conceptually philosophically beautiful part of the work you did with, uh, uh,", 'start': 5875.506, 'duration': 8.864}, {'end': 5888.032, 'text': 'and I guess continue to do, uh, probably with the, with the paper and the arc challenge.', 'start': 5884.37, 'duration': 3.662}, {'end': 5892.661, 'text': "Can you talk about some of the priors that we're talking about here? Yes.", 'start': 5888.532, 'duration': 4.129}], 'summary': 'Using priors to solve tasks is difficult but powerful.', 'duration': 28.36, 'max_score': 5864.301, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO45864301.jpg'}, {'end': 6146.293, 'src': 'embed', 'start': 6117.644, 'weight': 10, 'content': [{'end': 6122.789, 'text': 'This is something that is fundamentally hardwired into our brain.', 'start': 6117.644, 'duration': 5.145}, {'end': 6130.376, 'text': "it's, in fact, backed by very specific neural mechanisms like, for instance, grid cells and place cells.", 'start': 6122.789, 'duration': 7.587}, {'end': 6139.205, 'text': "So it's something that's literally hard-coded at the neural level in our hippocampus.", 'start': 6130.857, 'duration': 8.348}, {'end': 6143.309, 'text': 'And the last prior would be the notion of numbers.', 'start': 6139.985, 'duration': 3.324}, {'end': 6146.293, 'text': 'Like numbers are not actually a cultural construct.', 'start': 6143.59, 'duration': 2.703}], 'summary': 'Our brain is hardwired with specific neural mechanisms, such as grid cells and place cells, and numbers are not a cultural construct.', 'duration': 28.649, 'max_score': 6117.644, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO46117644.jpg'}], 'start': 4914.162, 'title': 'Understanding intelligence and physical fitness', 'summary': 'Discusses the analogy between physical fitness and intelligence, emphasizing constraints and correlations, comparing measurement methods. it also covers the generality of human morphology and cognition, the nature of difficult questions in iq tests and exams, challenges of creating difficult iq test questions, and testing for skill acquisition efficiency.', 'chapters': [{'end': 5012.937, 'start': 4914.162, 'title': 'Understanding intelligence and physical fitness', 'summary': 'Discusses the analogy between physical fitness and intelligence, emphasizing the constraints and correlations, and comparing the measurement methods for both concepts.', 'duration': 98.775, 'highlights': ['Intelligence and physical fitness are analogous concepts, as both are constrained to specific skills, with the inability to perform certain tasks such as flying.', 'The measurement of physical fitness involves a battery of tests, which results in correlations between different physical abilities, similar to the correlations between cognitive abilities.', 'Correlations between biological characteristics and physical abilities, such as lung volume being correlated with running speed, are similar to neurophysical correlates of cognitive abilities.']}, {'end': 5230.814, 'start': 5014.178, 'title': 'Generality of human morphology and cognition', 'summary': 'Discusses the remarkable generality of human morphology and cognition, emphasizing the specialized yet adaptable nature of physical and cognitive abilities within the constraints of the human condition.', 'duration': 216.636, 'highlights': ['Our morphology, bodies, and cognitive abilities possess a remarkable degree of generality, allowing us to perform activities completely unrelated to our evolutionary origins, such as climbing mountains and playing table tennis.', 'Human cognition and body evolved in specific environments, yet they exhibit a high degree of generalization, enabling us to improvise in various physical or cognitive environments.', 'The g-factor signifies a broad cognitive ability rather than strong generality, with strong cognitive biases making us well-suited for certain types of problems but ill-adapted for others within the human condition.']}, {'end': 5475.945, 'start': 5230.934, 'title': 'Understanding difficulty in iq tests and exams', 'summary': "Explains the nature of difficult questions in iq tests and exams, emphasizing the role of test time adaptation and improvisation, and how it relates to the test-taker's existing knowledge and experience.", 'duration': 245.011, 'highlights': ["The nature of difficult questions in IQ tests and exams is determined by the level of test time adaptation and improvisation required, rather than intrinsic difficulty, and is relative to the test-taker's existing knowledge and experience.", "IQ test questions are structured as a set of demonstration input and output pairs, and difficult questions are characterized by very surprising and unexpected input prompts given the training examples, challenging the test-taker's ability to generalize and improvise at test time.", "In the context of exams, a difficult exam probes the test-taker's understanding by presenting questions that force improvisation and are different from what they have been exposed to before, whereas an easy exam is similar to what the test-taker has been trained on and requires simple interpolation of questions they have already seen.", "The difficulty of an exam or test question is not intrinsically hard but is relative to the test-taker's existing knowledge, experience, and the information they bring to the table, emphasizing the role of controlling for priors and experience in evaluating difficulty."]}, {'end': 5796.399, 'start': 5475.945, 'title': 'Designing challenging iq tests', 'summary': 'Discusses the challenges of creating difficult iq test questions, protecting against correct answers, the need for novelty, and the distinction between testing human and machine intelligence.', 'duration': 320.454, 'highlights': ['Protecting against correct answers is essential as the question is ruined once the approach is known. The approach to protecting against correct answers is implicit in the training examples and releasing the training examples would ruin the question.', 'Designing challenging IQ tests requires the inclusion of ambiguous elements and a focus on difficulty without requiring ambiguity. Difficulty can be achieved without requiring ambiguity by making the test require a lot of extrapolation over the training examples.', 'Novelty is a requirement for creating challenging IQ test questions to ensure that individuals cannot practice for the questions they will be tested on. Novelty is crucial as individuals should not be able to practice for the questions they will be tested on to truly exhibit intelligence.', "A challenging IQ test for machines should probe their understanding and be unlike anything they've seen to avoid simple interpolation of mock exams. To distinguish a machine's understanding from simple interpolation, the test should be unlike anything they've seen and should probe their understanding.", 'Acknowledging and being explicit about the priors and assuming human cognitive priors are important for comparing machine intelligence and human intelligence. Explicitly acknowledging the priors and assuming human cognitive priors is essential when comparing machine intelligence and human intelligence.']}, {'end': 6255.766, 'start': 5797.299, 'title': 'Testing for skill acquisition efficiency', 'summary': 'Discusses the importance of testing for skill acquisition efficiency and the innate knowledge priors, including objectness, agentness, basic geometry, and numbers, with specific examples and their relevance to human cognition and development.', 'duration': 458.467, 'highlights': ["Elizabeth Spelke's core knowledge theory outlines four innate core knowledge systems, such as objectness and basic physics, agentness, basic geometry and topology, and numbers, which are hardwired into human cognition and development. The core knowledge theory by Elizabeth Spelke defines four innate core knowledge systems, including objectness, agentness, basic geometry and topology, and numbers, which are fundamental to human cognition and development.", 'Babies as young as three months can identify agentness and goal-directedness in their environment, showing the early acquisition of innate knowledge priors. Research by Spelke demonstrates that babies as young as three months can identify agentness and goal-directedness in their environment, indicating the early acquisition of innate knowledge priors.', 'The understanding of innate knowledge priors, such as objectness and agentness, provides insights into the fundamental cognitive processes and development of individuals. The comprehension of innate knowledge priors, like objectness and agentness, offers insights into the fundamental cognitive processes and development of individuals, showcasing the importance of these priors.']}], 'duration': 1341.604, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO44914162.jpg', 'highlights': ['Intelligence and physical fitness are analogous concepts, constrained to specific skills.', 'Correlations between biological characteristics and physical abilities are similar to neurophysical correlates of cognitive abilities.', 'Our morphology and cognitive abilities possess a remarkable degree of generality.', 'The g-factor signifies a broad cognitive ability rather than strong generality.', 'The nature of difficult questions in IQ tests and exams is determined by the level of test time adaptation and improvisation required.', "Difficult questions are characterized by very surprising and unexpected input prompts challenging the test-taker's ability to generalize and improvise at test time.", "The difficulty of an exam or test question is relative to the test-taker's existing knowledge, experience, and the information they bring to the table.", 'Designing challenging IQ tests requires the inclusion of ambiguous elements and a focus on difficulty without requiring ambiguity.', 'Novelty is a requirement for creating challenging IQ test questions to ensure that individuals cannot practice for the questions they will be tested on.', "Elizabeth Spelke's core knowledge theory outlines four innate core knowledge systems hardwired into human cognition and development.", 'Babies as young as three months can identify agentness and goal-directedness in their environment, showing the early acquisition of innate knowledge priors.', 'The comprehension of innate knowledge priors offers insights into the fundamental cognitive processes and development of individuals.']}, {'end': 7115.642, 'segs': [{'end': 6281.709, 'src': 'embed', 'start': 6256.166, 'weight': 4, 'content': [{'end': 6263.609, 'text': "So it's almost like you have somewhere in your brain a turntable with a fixed speed.", 'start': 6256.166, 'duration': 7.443}, {'end': 6271.131, 'text': 'And if you want to know if two objects are rotated versions of each other, you put the object on the turntable.', 'start': 6264.089, 'duration': 7.042}, {'end': 6279.184, 'text': "You, you, you let it move around a little bit and then you, and then you stop when you have a match and, and that that's really interesting.", 'start': 6271.692, 'duration': 7.492}, {'end': 6281.709, 'text': "So what's the arc challenge?", 'start': 6280.226, 'duration': 1.483}], 'summary': 'Brain has turntable analogy for identifying rotated objects.', 'duration': 25.543, 'max_score': 6256.166, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO46256166.jpg'}, {'end': 6575.852, 'src': 'heatmap', 'start': 6479.576, 'weight': 1, 'content': [{'end': 6485.339, 'text': 'One of the things you wanted to try to understand was this idea of abstraction.', 'start': 6479.576, 'duration': 5.763}, {'end': 6499.006, 'text': 'Yes, So clarifying my own ideas about abstraction by forcing myself to produce tasks that would require the ability to produce that form of abstraction in order to solve them.', 'start': 6486.08, 'duration': 12.926}, {'end': 6500.31, 'text': 'Got it.', 'start': 6499.969, 'duration': 0.341}, {'end': 6504.036, 'text': 'Okay, So, and by the way, just to I mean people should check out.', 'start': 6501.011, 'duration': 3.025}, {'end': 6512.692, 'text': "I'll probably overlay if you're watching the video part, but the the grid input output with the different colors on the grid.", 'start': 6504.036, 'duration': 8.656}, {'end': 6514.013, 'text': "And that's it.", 'start': 6512.712, 'duration': 1.301}, {'end': 6517.214, 'text': "I mean, it's a very simple world, but it's kind of beautiful.", 'start': 6514.333, 'duration': 2.881}, {'end': 6519.495, 'text': "It's very similar to classic IQ tests.", 'start': 6517.594, 'duration': 1.901}, {'end': 6521.516, 'text': "Like it's not very original in that sense.", 'start': 6519.555, 'duration': 1.961}, {'end': 6528.139, 'text': 'The main difference with IQ tests is that we make the priors explicit, which is not usually the case in IQ tests.', 'start': 6521.596, 'duration': 6.543}, {'end': 6533.122, 'text': 'So you make it explicit that everything should only be built out of core knowledge priors.', 'start': 6528.599, 'duration': 4.523}, {'end': 6539.046, 'text': "I also think it's generally more diverse than IQ tests in general.", 'start': 6534.042, 'duration': 5.004}, {'end': 6548.474, 'text': 'And it perhaps requires a bit more manual work to produce solutions because you have to click around on a grid for a while.', 'start': 6540.427, 'duration': 8.047}, {'end': 6551.617, 'text': 'Sometimes the grids can be as large as 30 by 30 cells.', 'start': 6548.534, 'duration': 3.083}, {'end': 6559.509, 'text': "So how did you come up, if you can reveal, with the questions like what's the process of the questions??", 'start': 6552.037, 'duration': 7.472}, {'end': 6563.436, 'text': 'Was it mostly you that came up with the questions? What,', 'start': 6559.549, 'duration': 3.887}, {'end': 6570.649, 'text': 'how difficult is it to come up with a question like is this scalable to a much larger number?', 'start': 6563.436, 'duration': 7.213}, {'end': 6575.852, 'text': 'If we think, you know, with IQ tests, you might not necessarily want it to or need it to be scalable.', 'start': 6570.689, 'duration': 5.163}], 'summary': 'Developed a grid-based iq test, more diverse and manual, with grids as large as 30x30 cells.', 'duration': 96.276, 'max_score': 6479.576, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO46479576.jpg'}, {'end': 6663.21, 'src': 'embed', 'start': 6636.632, 'weight': 3, 'content': [{'end': 6641.076, 'text': 'And so you have to pace the creation of these tasks quite a bit.', 'start': 6636.632, 'duration': 4.444}, {'end': 6644.16, 'text': 'There are only so many unique tasks that you can do in a given day.', 'start': 6641.117, 'duration': 3.043}, {'end': 6648.33, 'text': 'So that means coming up with truly original new ideas.', 'start': 6645.666, 'duration': 2.664}, {'end': 6653.156, 'text': "Um, did, uh, psychedelics help you at all? No, I'm just kidding.", 'start': 6649.391, 'duration': 3.765}, {'end': 6658.143, 'text': "But I mean, that's fascinating to think about, like, so you would be like walking or something like that.", 'start': 6653.837, 'duration': 4.306}, {'end': 6663.21, 'text': 'Are you constantly thinking of something totally new? Yes.', 'start': 6658.163, 'duration': 5.047}], 'summary': 'Limit task creation, focus on original ideas, maintain creativity.', 'duration': 26.578, 'max_score': 6636.632, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO46636632.jpg'}, {'end': 7017.631, 'src': 'embed', 'start': 6992.475, 'weight': 6, 'content': [{'end': 7002.762, 'text': 'in the sense that machine performance on Arc started at very much zero initially, while humans found actually the tasks very easy.', 'start': 6992.475, 'duration': 10.287}, {'end': 7011.468, 'text': 'And that alone was like a big red flashing light saying that something is going on and that we are missing something.', 'start': 7003.482, 'duration': 7.986}, {'end': 7017.631, 'text': 'And at the same time, machine performance did not stay at zero for very long.', 'start': 7012.488, 'duration': 5.143}], 'summary': 'Machine performance on arc initially at zero, improved over time.', 'duration': 25.156, 'max_score': 6992.475, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO46992475.jpg'}, {'end': 7073.954, 'src': 'embed', 'start': 7045.442, 'weight': 0, 'content': [{'end': 7049.223, 'text': 'At the same time, we are still very far from having solved it.', 'start': 7045.442, 'duration': 3.781}, {'end': 7061.267, 'text': "And that's actually a very positive outcome of the competition is that the competition has proven that there was no obvious shortcut to solve these tasks.", 'start': 7049.583, 'duration': 11.684}, {'end': 7062.788, 'text': 'Yeah, so the test held up.', 'start': 7061.747, 'duration': 1.041}, {'end': 7063.848, 'text': 'Yeah, exactly.', 'start': 7063.228, 'duration': 0.62}, {'end': 7073.954, 'text': 'That was the primary reason to the Kaggle competition is to check if some, you know, clever person was going to hack the benchmark.', 'start': 7063.868, 'duration': 10.086}], 'summary': 'Kaggle competition proved no shortcut to solve tasks.', 'duration': 28.512, 'max_score': 7045.442, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO47045442.jpg'}], 'start': 6256.166, 'title': 'Arc challenge and machine intelligence principles', 'summary': 'Discusses the arc challenge, a test of machine and human intelligence embodying principles of core knowledge priors and specific forms of abstraction, aiming to clarify ideas about the nature of abstraction. it also delves into the development and future prospects of arc, including potential for crowdsourcing, collaboration with psychology departments, and the correlation between machine and human performance, with the state of the art machine performance currently at around 20% of the test set solved.', 'chapters': [{'end': 6500.31, 'start': 6256.166, 'title': 'Arc challenge and machine intelligence principles', 'summary': 'Discusses the arc challenge, a test of machine and human intelligence embodying principles of core knowledge priors and specific forms of abstraction, aiming to clarify ideas about the nature of abstraction.', 'duration': 244.144, 'highlights': ['The ARC challenge embodies principles of core knowledge priors and specific forms of abstraction, aiming to clarify ideas about the nature of abstraction. The ARC challenge attempts to embody principles of core knowledge priors and specific forms of abstraction, aiming to clarify ideas about the nature of abstraction.', "The format of ARC is very similar to classic IQ tests, particularly Raven's Progressive Matrices. The format of ARC resembles classic IQ tests, specifically Raven's Progressive Matrices, with tasks involving training data of inputs and output pairs.", 'The ARC tasks are explicitly designed to probe specific forms of abstraction and should only require core knowledge priors, not outside knowledge. ARC tasks are explicitly designed to probe specific forms of abstraction and should only require core knowledge priors, not outside knowledge like language or concepts taken from human experience.', 'Creating ARC was to clarify ideas about the nature of abstraction and co-evolve the solution and the problem. Creating ARC was to clarify ideas about the nature of abstraction and co-evolve the solution and the problem, aiming to understand the autonomous generation of abstraction in machines.']}, {'end': 7115.642, 'start': 6501.011, 'title': 'The future of arc and its impact', 'summary': 'Discusses the development of arc, an intelligence test, and its future prospects, including the potential for crowdsourcing, collaboration with psychology departments, and the correlation between machine and human performance, with the state of the art machine performance currently at around 20% of the test set solved.', 'duration': 614.631, 'highlights': ['The state of the art machine performance on Arc is around 20% of the test set solved, indicating the need for progress and the absence of an obvious shortcut, with the test proving to be a very actionable challenge. The machine performance on Arc started at zero and has now reached around 20% of the test set solved within two weeks of the Kaggle competition, highlighting the need for progress and the absence of an obvious shortcut.', 'The potential future prospects for Arc include crowdsourcing for the creation of tasks and collaboration with psychology departments to conduct human testing and explore correlations between machine and human performance. The potential future prospects for Arc include crowdsourcing for the creation of tasks and collaboration with psychology departments to conduct human testing and explore correlations between machine and human performance.', 'The need to keep refining Arc, opening up the creation of tasks to a broad audience through crowdsourcing, and ensuring that the test remains hidden to avoid human engineers solving the tasks themselves and encoding their solutions. There is a need to keep refining Arc, open up the creation of tasks to a broad audience through crowdsourcing, and ensure that the test remains hidden to avoid human engineers solving the tasks themselves and encoding their solutions.']}], 'duration': 859.476, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO46256166.jpg', 'highlights': ['The ARC challenge embodies principles of core knowledge priors and specific forms of abstraction, aiming to clarify ideas about the nature of abstraction.', "The format of ARC resembles classic IQ tests, specifically Raven's Progressive Matrices, with tasks involving training data of inputs and output pairs.", 'ARC tasks are explicitly designed to probe specific forms of abstraction and should only require core knowledge priors, not outside knowledge like language or concepts taken from human experience.', 'Creating ARC was to clarify ideas about the nature of abstraction and co-evolve the solution and the problem, aiming to understand the autonomous generation of abstraction in machines.', 'The state of the art machine performance on Arc is around 20% of the test set solved, indicating the need for progress and the absence of an obvious shortcut, with the test proving to be a very actionable challenge.', 'The potential future prospects for Arc include crowdsourcing for the creation of tasks and collaboration with psychology departments to conduct human testing and explore correlations between machine and human performance.', 'There is a need to keep refining Arc, open up the creation of tasks to a broad audience through crowdsourcing, and ensure that the test remains hidden to avoid human engineers solving the tasks themselves and encoding their solutions.']}, {'end': 9250.949, 'segs': [{'end': 7783.832, 'src': 'embed', 'start': 7754.777, 'weight': 5, 'content': [{'end': 7759.459, 'text': 'Non-human systems are probably not contributing much, but AIs are definitely contributing to that.', 'start': 7754.777, 'duration': 4.682}, {'end': 7761.78, 'text': 'Like Google search, for instance, is a big part of it.', 'start': 7759.819, 'duration': 1.961}, {'end': 7770.264, 'text': "Yeah Yeah, a huge part, a part we can't probably introspect.", 'start': 7764.381, 'duration': 5.883}, {'end': 7773.806, 'text': 'Like how the world has changed in the past 20 years.', 'start': 7771.164, 'duration': 2.642}, {'end': 7778.269, 'text': "it's probably very difficult for us to be able to understand until.", 'start': 7773.806, 'duration': 4.463}, {'end': 7783.832, 'text': "of course, whoever created the simulation we're in is probably doing metrics measuring the progress.", 'start': 7778.269, 'duration': 5.563}], 'summary': "Ais, like google search, significantly impact the world; difficult to comprehend change without introspection or creator's metrics.", 'duration': 29.055, 'max_score': 7754.777, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO47754777.jpg'}, {'end': 7960.184, 'src': 'embed', 'start': 7936.65, 'weight': 9, 'content': [{'end': 7944.913, 'text': "But nowadays I think it's fairly well accepted that the mind is an information processing system and that you could probably encode it into a computer.", 'start': 7936.65, 'duration': 8.263}, {'end': 7960.184, 'text': "So, another reason why I'm not a fan of this type of test is that The incentives that it creates are incentives that are not conducive to proper scientific research.", 'start': 7945.514, 'duration': 14.67}], 'summary': 'Mind seen as an information processing system, not conducive to proper scientific research', 'duration': 23.534, 'max_score': 7936.65, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO47936650.jpg'}, {'end': 8040.504, 'src': 'embed', 'start': 8009.303, 'weight': 6, 'content': [{'end': 8012.646, 'text': "It's not making any progress in our understanding of the universe, right?", 'start': 8009.303, 'duration': 3.343}, {'end': 8015.188, 'text': "To push back on that, it's possible, that's.", 'start': 8012.666, 'duration': 2.522}, {'end': 8026.598, 'text': "the hope with these kinds of subjective evaluations is that it's easier to solve it generally than it is to come up with tricks that convince a large number of judges.", 'start': 8015.188, 'duration': 11.41}, {'end': 8028.019, 'text': "that's the whole in practice.", 'start': 8026.598, 'duration': 1.421}, {'end': 8034.381, 'text': "what it turns out that it's very easy to deceive people in the same way that you know you can, you can do magic in vegas.", 'start': 8028.019, 'duration': 6.362}, {'end': 8040.504, 'text': "you can actually very easily convince people, uh, that they are talking to human when they're actually talking to an algorithm.", 'start': 8034.381, 'duration': 6.123}], 'summary': 'Subjective evaluations aim for general solutions but can be easily deceived, as seen in convincing people to talk to algorithms.', 'duration': 31.201, 'max_score': 8009.303, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO48009303.jpg'}, {'end': 8769.143, 'src': 'embed', 'start': 8743.131, 'weight': 12, 'content': [{'end': 8747.533, 'text': 'which is like local or robust generalization versus extreme generalization.', 'start': 8743.131, 'duration': 4.402}, {'end': 8749.574, 'text': "It's much closer to that side of..", 'start': 8747.893, 'duration': 1.681}, {'end': 8753.336, 'text': 'being able to generalize in the local sense.', 'start': 8750.835, 'duration': 2.501}, {'end': 8762.86, 'text': "That's why as humans, when we are children, in our education, a lot of it is driven by place, driven by curiosity.", 'start': 8753.396, 'duration': 9.464}, {'end': 8769.143, 'text': "We are not efficiently compressing things, we're actually exploring.", 'start': 8764.341, 'duration': 4.802}], 'summary': "Humans' education is driven by place and curiosity, promoting local generalization and exploration.", 'duration': 26.012, 'max_score': 8743.131, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO48743131.jpg'}, {'end': 8863.008, 'src': 'embed', 'start': 8839.737, 'weight': 14, 'content': [{'end': 8846.799, 'text': 'And the same is true of the human mind, is that it needs to behave appropriately in the future.', 'start': 8839.737, 'duration': 7.062}, {'end': 8851.242, 'text': "And it has no idea what the future is going to be like, but it's not going to be like the past.", 'start': 8846.859, 'duration': 4.383}, {'end': 8858.726, 'text': 'So compressing the past is not appropriate because the past is not proactive with the future.', 'start': 8851.522, 'duration': 7.204}, {'end': 8863.008, 'text': 'Yeah History repeats itself, but not perfectly.', 'start': 8860.587, 'duration': 2.421}], 'summary': 'The human mind needs to adapt for the future, as history does not perfectly repeat.', 'duration': 23.271, 'max_score': 8839.737, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO48839737.jpg'}, {'end': 9053.206, 'src': 'embed', 'start': 9021.548, 'weight': 0, 'content': [{'end': 9026.992, 'text': 'And we keep influencing people thousands of years from now.', 'start': 9021.548, 'duration': 5.444}, {'end': 9031.053, 'text': 'So our actions today create reports.', 'start': 9027.692, 'duration': 3.361}, {'end': 9036.956, 'text': 'And these reports, I think, basically sum up the meaning of life.', 'start': 9031.073, 'duration': 5.883}, {'end': 9047.2, 'text': 'Like, in the same way that we are the sum of the interactions between many different reports that came from our past,', 'start': 9037.376, 'duration': 9.824}, {'end': 9050.281, 'text': 'we are ourselves creating reports that will propagate into the future.', 'start': 9047.2, 'duration': 3.081}, {'end': 9053.206, 'text': "And that's why, you know, we should be.", 'start': 9050.785, 'duration': 2.421}], 'summary': 'Our actions today create reports that influence people for thousands of years, summing up the meaning of life.', 'duration': 31.658, 'max_score': 9021.548, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO49021548.jpg'}, {'end': 9156.378, 'src': 'embed', 'start': 9121.753, 'weight': 1, 'content': [{'end': 9126.154, 'text': 'Click the sponsor links in the description to get a discount and to support this podcast.', 'start': 9121.753, 'duration': 4.401}, {'end': 9132.735, 'text': 'If you enjoy this thing, subscribe on YouTube, review it with five stars on Apple Podcasts, follow on Spotify,', 'start': 9126.834, 'duration': 5.901}, {'end': 9136.716, 'text': 'support on Patreon or connect with me on Twitter at Lex Friedman.', 'start': 9132.735, 'duration': 3.981}, {'end': 9142.986, 'text': 'And now let me leave you with some words from René Descartes in 1668,', 'start': 9137.881, 'duration': 5.105}, {'end': 9146.809, 'text': 'an excerpt of which Francois includes in his On the Measure of Intelligence paper.', 'start': 9142.986, 'duration': 3.823}, {'end': 9156.378, 'text': 'If there were machines which bore a resemblance to our bodies and imitated our actions as closely as possible for all practical purposes,', 'start': 9147.87, 'duration': 8.508}], 'summary': 'Encourage audience engagement and support through various channels; ends with a quote from rene descartes about machine resemblance.', 'duration': 34.625, 'max_score': 9121.753, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO49121753.jpg'}, {'end': 9206.561, 'src': 'embed', 'start': 9179.612, 'weight': 2, 'content': [{'end': 9190.675, 'text': 'but it is not conceivable that such a machine should produce different arrangements of words so as to give an appropriately meaningful answer to whatever is said in its presence,', 'start': 9179.612, 'duration': 11.063}, {'end': 9191.955, 'text': 'as the dullest of men can do.', 'start': 9190.675, 'duration': 1.28}, {'end': 9197.397, 'text': 'Here, Descartes is anticipating the Turing test, and the argument still continues to this day.', 'start': 9192.815, 'duration': 4.582}, {'end': 9206.561, 'text': 'Secondly, he continues, even though some machines might do some things as well as we do them, or perhaps even better,', 'start': 9198.817, 'duration': 7.744}], 'summary': 'Descartes anticipates turing test, stating machines may perform tasks better than humans.', 'duration': 26.949, 'max_score': 9179.612, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO49179612.jpg'}, {'end': 9250.949, 'src': 'embed', 'start': 9247.317, 'weight': 4, 'content': [{'end': 9250.949, 'text': 'So thank you for listening and hope to see you next time.', 'start': 9247.317, 'duration': 3.632}], 'summary': 'Thanking the audience for listening and expressing hope for future engagement.', 'duration': 3.632, 'max_score': 9247.317, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO49247317.jpg'}], 'start': 7115.642, 'title': 'Ai generalization and human parity', 'summary': 'Discusses achieving human parity in general fluid intelligence and the ability of ai systems to perform developer-aware generalization, the three key attributes of machine intelligence, limitations of the turing test, intelligence test compression, and the cultural influence on human existence.', 'chapters': [{'end': 7318.777, 'start': 7115.642, 'title': 'Ai generalization and human parity', 'summary': 'Discusses the concept of generalization in ai, highlighting the importance of achieving human parity in general fluid intelligence and the ability of ai systems to perform developer-aware generalization, which is crucial for dealing with unforeseen edge cases.', 'duration': 203.135, 'highlights': ['AI systems reaching human parity in general fluid intelligence The discussion emphasizes the significance of AI systems achieving human parity in general fluid intelligence, indicating that these systems will likely be close to human-level in terms of general fluid intelligence.', 'Developer-aware generalization as a crucial aspect of AI intelligence The concept of developer-aware generalization is highlighted as a crucial aspect of AI intelligence, enabling the system to generalize to novelty or uncertainty that neither the system itself nor the developer has access to, emphasizing its importance for handling unforeseen edge cases.', 'Different levels of generalization and machine learning The discussion presents different levels of generalization in machine learning, emphasizing the lowest level of generalization where new situations are assumed to be sampled from a static distribution of possible situations, and the system generalizes to known unknowns for a specific task, indicating the focus on robustness to known variations.']}, {'end': 7778.269, 'start': 7319.537, 'title': 'The future of machine intelligence', 'summary': 'Discusses the three key attributes of machine intelligence - robustness, flexibility, and extreme generalization - with the ultimate goal of achieving human-level extreme generalization, and explores the potential of augmenting human intelligence through externalized cognition.', 'duration': 458.732, 'highlights': ['The Ultimate Goal: Human-level Extreme Generalization The ultimate goal of machine intelligence is to achieve human-level extreme generalization, enabling systems to achieve human skill parity over arbitrary tasks and domains, with the same level of improvisation and adaptation power as humans, using the same amount of training and experience.', 'Attributes of Machine Intelligence: Robustness, Flexibility, Extreme Generalization Machine intelligence is characterized by three key attributes - robustness, flexibility, and extreme generalization - which collectively aim to equip systems with the ability to handle unknown unknowns, generalize across a wide range of domains, and achieve human-level extreme generalization.', 'Augmenting Human Intelligence through Externalized Cognition The discussion explores the potential of augmenting human intelligence through externalized cognition, encompassing cultural systems, language, books, and non-human contributions, with the capacity to scale externalized cognition far beyond individual brain capabilities.']}, {'end': 8221.165, 'start': 7778.269, 'title': 'Turing test and lobner prize', 'summary': 'Examines the limitations of the turing test and its impact on ai research, highlighting biases in human judgment and the need for more pragmatic evaluation methods such as the alexa prize.', 'duration': 442.896, 'highlights': ["The Turing test's reliance on human judges violates core psychometrics principles, including reliability, standardization, and freedom from bias, hindering the proper evaluation of machine intelligence.", 'Incentives created by the Turing test prioritize trickery over scientific progress, leading to a focus on convincing human judges rather than developing genuinely intelligent systems, as exemplified by the more pragmatic approach of the Alexa Prize.', 'The chapter also discusses the limited practical inspiration drawn from the Turing test by engineers, emphasizing the need for evaluation methods that prioritize genuine cognitive abilities over human likeness in AI development.']}, {'end': 8863.008, 'start': 8221.726, 'title': 'Intelligence test compression', 'summary': 'Discusses the limitations of using compression as a measure of intelligence, emphasizing that cognition, driven by future uncertainty and novelty, leverages compression as a tool for efficiency and simplicity in models, but requires diversity to hedge for future uncertainty.', 'duration': 641.282, 'highlights': ["Cognition leverages compression as a tool to promote efficiency and simplicity in our models, but it's antagonistic to compression as it requires diversity to hedge for future uncertainty. Emphasizes the antagonistic relationship between cognition and compression, where cognition uses compression as a tool for efficiency and simplicity in models, but requires diversity to hedge for future uncertainty.", 'The fundamental difference between compression and cognition lies in the ability to operate in future situations that include fundamental uncertainty and novelty. Explains the fundamental difference between compression and cognition, highlighting the ability of cognition to operate in future situations with uncertainty and novelty.', 'The chapter discusses the limitations of using compression as a measure of intelligence, emphasizing that cognition, driven by future uncertainty and novelty, leverages compression as a tool for efficiency and simplicity in models, but requires diversity to hedge for future uncertainty. Discusses the limitations of using compression as a measure of intelligence and emphasizes the need for diversity in cognition to hedge for future uncertainty and novelty.']}, {'end': 9250.949, 'start': 8864.81, 'title': 'Meaning of life and cultural influence', 'summary': 'Delves into the meaning of life, emphasizing the cultural influence on human existence, the propagation of ideas into the future, and the impact of actions on shaping the collective edifice of culture, leading to the creation of reports that propagate into the future.', 'duration': 386.139, 'highlights': ['Human existence is shaped by cultural influence, as everything about ourselves is an echo of the past, and our actions create ripples that propagate into the future. Francois Chollet emphasizes the cultural influence on human existence, stating that everything about ourselves is an echo of the past and our actions create ripples that propagate into the future.', 'Contributions to culture, such as new ideas, music, art, and theories, become a part of the minds of future humans, essentially forever, shaping the collective edifice of culture. The contributions to culture, such as new ideas, music, art, and theories, become a part of the minds of future humans, essentially forever, shaping the collective edifice of culture.', 'Actions today create reports that propagate into the future, and the sum of these interactions essentially sums up the meaning of life, emphasizing the importance of kindness and the impact of actions on shaping the future. Actions today create reports that propagate into the future, essentially summing up the meaning of life, emphasizing the importance of kindness and the impact of actions on shaping the future.']}], 'duration': 2135.307, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/PUAdj3w3wO4/pics/PUAdj3w3wO47115642.jpg', 'highlights': ['AI systems reaching human parity in general fluid intelligence, indicating their closeness to human-level intelligence.', 'Developer-aware generalization as a crucial aspect of AI intelligence, enabling the system to handle unforeseen edge cases.', 'Different levels of generalization in machine learning, focusing on robustness to known variations.', 'The ultimate goal of machine intelligence is to achieve human-level extreme generalization over arbitrary tasks and domains.', 'Machine intelligence is characterized by three key attributes - robustness, flexibility, and extreme generalization.', 'The potential of augmenting human intelligence through externalized cognition, encompassing cultural systems and non-human contributions.', "The Turing test's reliance on human judges violates core psychometrics principles, hindering the proper evaluation of machine intelligence.", 'Incentives created by the Turing test prioritize trickery over scientific progress, leading to a focus on convincing human judges.', 'The limited practical inspiration drawn from the Turing test by engineers, emphasizing the need for evaluation methods prioritizing genuine cognitive abilities.', 'The antagonistic relationship between cognition and compression, where cognition uses compression for efficiency but requires diversity for future uncertainty.', 'The fundamental difference between compression and cognition lies in the ability to operate in future situations with uncertainty and novelty.', 'The limitations of using compression as a measure of intelligence, emphasizing the need for diversity in cognition to hedge for future uncertainty and novelty.', 'Human existence is shaped by cultural influence, as everything about ourselves is an echo of the past, and our actions create ripples that propagate into the future.', 'Contributions to culture become a part of the minds of future humans, shaping the collective edifice of culture.', 'Actions today create reports that propagate into the future, emphasizing the importance of kindness and the impact of actions on shaping the future.']}], 'highlights': ['The chapter emphasizes the rareness of the serious, rigorous scientific study of artificial general intelligence.', 'The mainstream machine learning community works on very narrow AI with very narrow benchmarks, while the renegade AGI community works on approaches that verge on the philosophical and literary, without big public benchmarks.', 'The AGI series at MIT was an attempt to inspire more people to walk the line between mainstream and renegade AI communities, and DeepMind and OpenAI also occasionally walk this line.', 'The paper aims to offer a reliable and actionable measure of general intelligence to accurately evaluate progress in AI, emphasizing the need for a precise definition and measurement of general intelligence.', 'The measure of intelligence is the ability to change, capturing the importance of adaptability and improvisation as key aspects of intelligence.', 'The G factor serves as a latent variable that explains the correlations among different aspects of intelligence, as observed through clusters of correlations among test results.', 'Intelligence and physical fitness are analogous concepts, constrained to specific skills.', 'The ARC challenge embodies principles of core knowledge priors and specific forms of abstraction, aiming to clarify ideas about the nature of abstraction.', 'AI systems reaching human parity in general fluid intelligence, indicating their closeness to human-level intelligence.', 'Human existence is shaped by cultural influence, as everything about ourselves is an echo of the past, and our actions create ripples that propagate into the future.']}