title
Andrew Ng: Deep Learning, Education, and Real-World AI | Lex Fridman Podcast #73

description
Andrew Ng is one of the most impactful educators, researchers, innovators, and leaders in artificial intelligence and technology space in general. He co-founded Coursera and Google Brain, launched deeplearning.ai, Landing.ai, and the AI fund, and was the Chief Scientist at Baidu. As a Stanford professor, and with Coursera and deeplearning.ai, he has helped educate and inspire millions of students including me. This episode is presented by Cash App. Download it & use code "LexPodcast": Cash App (App Store): https://apple.co/2sPrUHe Cash App (Google Play): https://bit.ly/2MlvP5w 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 EPISODE LINKS: Andrew Twitter: https://twitter.com/AndrewYNg Andrew Facebook: https://www.facebook.com/andrew.ng.96 Andrew LinkedIn: https://www.linkedin.com/in/andrewyng/ deeplearning.ai: https://www.deeplearning.ai landing.ai: https://landing.ai AI Fund: https://aifund.ai/ AI for Everyone: https://www.coursera.org/learn/ai-for-everyone The Batch newsletter: https://www.deeplearning.ai/thebatch/ OUTLINE: 0:00 - Introduction 2:23 - First few steps in AI 5:05 - Early days of online education 16:07 - Teaching on a whiteboard 17:46 - Pieter Abbeel and early research at Stanford 23:17 - Early days of deep learning 32:55 - Quick preview: deeplearning.ai, landing.ai, and AI fund 33:23 - deeplearning.ai: how to get started in deep learning 45:55 - Unsupervised learning 49:40 - deeplearning.ai (continued) 56:12 - Career in deep learning 58:56 - Should you get a PhD? 1:03:28 - AI fund - building startups 1:11:14 - Landing.ai - growing AI efforts in established companies 1:20:44 - Artificial general intelligence CONNECT: - Subscribe to this YouTube channel - Twitter: https://twitter.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Facebook: https://www.facebook.com/LexFridmanPage - Instagram: https://www.instagram.com/lexfridman - Medium: https://medium.com/@lexfridman - Support on Patreon: https://www.patreon.com/lexfridman

detail
{'title': 'Andrew Ng: Deep Learning, Education, and Real-World AI | Lex Fridman Podcast #73', 'heatmap': [{'end': 4283.714, 'start': 4219.561, 'weight': 1}], 'summary': 'In a conversation with andrew ng, the podcast discusses his key roles in ai, machine learning education, and the potential of ai to reshape various industries, emphasizing the global impact of mooc movement, the significance of deep learning, and the potential economic growth from ai adoption in non-tech industries.', 'chapters': [{'end': 118.98, 'segs': [{'end': 32.603, 'src': 'embed', 'start': 0.069, 'weight': 0, 'content': [{'end': 6.571, 'text': 'The following is a conversation with Andrew Ng, one of the most impactful educators, researchers,', 'start': 0.069, 'duration': 6.502}, {'end': 11.112, 'text': 'innovators and leaders in artificial intelligence and technology space in general.', 'start': 6.571, 'duration': 4.541}, {'end': 22.135, 'text': 'He co-founded Coursera and Google Brain, launched Deep Learning AI, Lending AI, and the AI Fund, and was the chief scientist at Baidu.', 'start': 12.052, 'duration': 10.083}, {'end': 32.603, 'text': 'As a Stanford professor and with Coursera and Deep Learning AI, he has helped educate and inspire millions of students, including me.', 'start': 23.235, 'duration': 9.368}], 'summary': 'Andrew ng is a prominent figure in ai, having co-founded coursera and google brain, and educated millions of students.', 'duration': 32.534, 'max_score': 0.069, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig69.jpg'}, {'end': 126.487, 'src': 'embed', 'start': 93.829, 'weight': 1, 'content': [{'end': 97.931, 'text': 'Debits and credits on ledgers started over 30,000 years ago.', 'start': 93.829, 'duration': 4.102}, {'end': 101.832, 'text': 'The US dollar was created over 200 years ago.', 'start': 97.951, 'duration': 3.881}, {'end': 107.575, 'text': 'And Bitcoin, the first decentralized cryptocurrency, released just over 10 years ago.', 'start': 102.313, 'duration': 5.262}, {'end': 116.759, 'text': "So, given that history, cryptocurrency is still very much in its early days of development, but it's still aiming to, and just might,", 'start': 108.255, 'duration': 8.504}, {'end': 118.98, 'text': 'redefine the nature of money.', 'start': 116.759, 'duration': 2.221}, {'end': 126.487, 'text': "So again, if you get Cash App from the App Store or Google Play and use the code LexPodcast, you'll get $10,", 'start': 119.84, 'duration': 6.647}], 'summary': 'Cryptocurrency, a 10-year-old innovation, aims to redefine money.', 'duration': 32.658, 'max_score': 93.829, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig93829.jpg'}], 'start': 0.069, 'title': 'Conversation with andrew ng', 'summary': 'Features a conversation with andrew ng, a prominent figure in artificial intelligence and technology, who co-founded coursera and google brain, launched deep learning ai, lending ai, and the ai fund, and was the chief scientist at baidu, and discusses the early days of cryptocurrency and its potential to redefine the nature of money.', 'chapters': [{'end': 118.98, 'start': 0.069, 'title': 'Conversation with andrew ng', 'summary': 'Features a conversation with andrew ng, a prominent figure in artificial intelligence and technology, who co-founded coursera and google brain, launched deep learning ai, lending ai, and the ai fund, and was the chief scientist at baidu, and discusses the early days of cryptocurrency and its potential to redefine the nature of money.', 'duration': 118.911, 'highlights': ["Andrew Ng is a prominent figure in artificial intelligence and technology, co-founded Coursera and Google Brain, launched Deep Learning AI, Lending AI, and the AI Fund, and was the chief scientist at Baidu. Andrew Ng's significant contributions to the fields of artificial intelligence and technology, including co-founding Coursera and Google Brain, and launching Deep Learning AI, Lending AI, and the AI Fund.", 'Cryptocurrency, with Bitcoin being the first decentralized cryptocurrency, is still in its early days of development and has the potential to redefine the nature of money. The history of money, including the release of Bitcoin over 10 years ago, suggests that cryptocurrency is still in its early days of development and has the potential to redefine the nature of money.']}], 'duration': 118.911, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig69.jpg', 'highlights': ["Andrew Ng's significant contributions to the fields of artificial intelligence and technology, including co-founding Coursera and Google Brain, and launching Deep Learning AI, Lending AI, and the AI Fund.", 'Cryptocurrency, with Bitcoin being the first decentralized cryptocurrency, is still in its early days of development and has the potential to redefine the nature of money.']}, {'end': 627.677, 'segs': [{'end': 274.229, 'src': 'embed', 'start': 243.138, 'weight': 2, 'content': [{'end': 247.559, 'text': 'So I think a lot of my work since then has centered on the theme of automation.', 'start': 243.138, 'duration': 4.421}, {'end': 254.322, 'text': "Even the way I think about machine learning today, we're very good at writing learning algorithms that can automate things that people can do.", 'start': 247.76, 'duration': 6.562}, {'end': 258.183, 'text': 'Or even launching the first MOOCs Mass Open Online Courses.', 'start': 254.342, 'duration': 3.841}, {'end': 260.204, 'text': 'that later led to Coursera.', 'start': 258.183, 'duration': 2.021}, {'end': 265.165, 'text': 'I was trying to automate what could be automatable in how I was teaching on campus.', 'start': 260.204, 'duration': 4.961}, {'end': 274.229, 'text': 'The process of education tried to automate parts of that to make it more, sort of to have more impact from a single teacher, a single educator.', 'start': 265.185, 'duration': 9.044}], 'summary': 'Work focused on automation, led to launching moocs, aiming to automate education processes for greater impact.', 'duration': 31.091, 'max_score': 243.138, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig243138.jpg'}, {'end': 333.569, 'src': 'embed', 'start': 308.144, 'weight': 0, 'content': [{'end': 312.966, 'text': 'teaching thousands of people in person and then millions of people online?', 'start': 308.144, 'duration': 4.822}, {'end': 317.163, 'text': 'You know, teaching online.', 'start': 314.502, 'duration': 2.661}, {'end': 326.066, 'text': 'what not many people know was that a lot of those videos were shot between the hours of 10 p.m. and 3 a.m..', 'start': 317.163, 'duration': 8.903}, {'end': 331.108, 'text': 'A lot of times launching the first Microsoft Stanford.', 'start': 327.807, 'duration': 3.301}, {'end': 332.689, 'text': "we'd already announced the course.", 'start': 331.108, 'duration': 1.581}, {'end': 333.569, 'text': 'about 100,000 people had signed up.', 'start': 332.689, 'duration': 0.88}], 'summary': 'Taught thousands in person and millions online, with videos shot from 10 p.m. to 3 a.m., attracting about 100,000 sign-ups for the first microsoft stanford course.', 'duration': 25.425, 'max_score': 308.144, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig308144.jpg'}, {'end': 474.018, 'src': 'embed', 'start': 450.114, 'weight': 1, 'content': [{'end': 460.158, 'text': "And I think one of the things we got right launched the first few MOOCs and later building Coursera was putting in place that bedrock principle of let's just do what's best for learners and forget about everything else.", 'start': 450.114, 'duration': 10.044}, {'end': 466.521, 'text': 'And I think that as a guiding principle turned out to be really important to the rise of the MOOC movement.', 'start': 460.558, 'duration': 5.963}, {'end': 474.018, 'text': 'And the kind of learner you imagined in your mind is as broad as possible, as global as possible.', 'start': 467.037, 'duration': 6.981}], 'summary': "Focusing on learner needs drove success in moocs and coursera's global reach.", 'duration': 23.904, 'max_score': 450.114, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig450114.jpg'}, {'end': 510.453, 'src': 'embed', 'start': 484.84, 'weight': 3, 'content': [{'end': 491.382, 'text': "And I think sometimes I've actually had people ask me hey, why are you spending so much time explaining gradient descent?", 'start': 484.84, 'duration': 6.542}, {'end': 500.767, 'text': 'And my answer was If I look at what I think the learner needs and would benefit from, I felt that having a good understanding of the foundations,', 'start': 492.182, 'duration': 8.585}, {'end': 505.91, 'text': 'coming back to the basics, would put them in a better stead to then build on a long-term career.', 'start': 500.767, 'duration': 5.143}, {'end': 510.453, 'text': "So we've tried to consistently make decisions on that principle.", 'start': 505.93, 'duration': 4.523}], 'summary': 'Explaining gradient descent is crucial for building a strong foundation and long-term career prospects.', 'duration': 25.613, 'max_score': 484.84, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig484840.jpg'}], 'start': 119.84, 'title': "Andrew ang's journey into machine learning education", 'summary': "Highlights andrew ang's dedication to filming online courses, reaching millions of people with late-night recordings, and discusses the global reach of the mooc movement, emphasizing its impact on machine learning and ai education.", 'chapters': [{'end': 417.872, 'start': 119.84, 'title': 'Andrew ang: teaching and automating machine learning', 'summary': "Highlights andrew ang's journey into computer science and machine learning, his motivation to automate the education process, and his dedication to filming online courses, reaching millions of people despite late-night recordings.", 'duration': 298.032, 'highlights': ["Andrew Ang's early exposure to coding and computer science at a young age in Hong Kong and Singapore, igniting his fascination with writing code and creating simple video games. ", "His teenage interest in expert systems and neural networks, influenced by his father's reading, and his realization of the potential for automation while working as an office assistant in Singapore. ", 'The motivation behind his work focusing on automation, including the development of learning algorithms and the launch of the first MOOCs, aimed at automating the teaching process to reach a broader audience. ', "Andrew Ang's dedication to filming online courses, often recording between 10 p.m. and 3 a.m., driven by the pressure to produce content for the thousands and eventually millions of people eager to learn about machine learning. "]}, {'end': 627.677, 'start': 418.152, 'title': 'Delivering education for learners', 'summary': "Discusses the importance of prioritizing learners' needs, reaching a global audience, and the substantial interest in machine learning and ai, with a focus on doing what's best for learners and the global reach of the mooc movement, emphasizing reaching millions of people interested in machine learning and ai.", 'duration': 209.525, 'highlights': ["The guiding principle of doing what's best for learners was instrumental in the rise of the MOOC movement, focusing on reaching a broad and global audience interested in machine learning and AI, with millions of people from around the world demonstrating substantial interest in the field.", 'Prioritizing the foundational understanding of concepts, such as explaining gradient descent, was aimed at putting learners in a better position for long-term career growth in machine learning and AI.', 'Iterating and learning from various versions of websites and features, such as building a website for multiple simultaneous logins, allowed for the refinement of ideas and understanding what resonates with the audience.', 'The initial online education efforts involved filming Stanford classes, posting videos on YouTube, and building websites to iterate and learn about effective educational strategies.']}], 'duration': 507.837, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig119840.jpg', 'highlights': ["Andrew Ang's dedication to filming online courses, often recording between 10 p.m. and 3 a.m., driven by the pressure to produce content for the thousands and eventually millions of people eager to learn about machine learning.", "The guiding principle of doing what's best for learners was instrumental in the rise of the MOOC movement, focusing on reaching a broad and global audience interested in machine learning and AI, with millions of people from around the world demonstrating substantial interest in the field.", 'The motivation behind his work focusing on automation, including the development of learning algorithms and the launch of the first MOOCs, aimed at automating the teaching process to reach a broader audience.', 'Prioritizing the foundational understanding of concepts, such as explaining gradient descent, was aimed at putting learners in a better position for long-term career growth in machine learning and AI.']}, {'end': 1379.443, 'segs': [{'end': 675.241, 'src': 'embed', 'start': 649.789, 'weight': 4, 'content': [{'end': 657.734, 'text': 'It turns out people studying online, they want to watch the videos by themselves so you can playback, pause at your own speed rather than in groups.', 'start': 649.789, 'duration': 7.945}, {'end': 664.558, 'text': 'So that was one example of a tiny lesson learned out of many that allowed us to hone in to the set of features.', 'start': 657.834, 'duration': 6.724}, {'end': 666.418, 'text': 'And it sounds like a brilliant feature.', 'start': 664.898, 'duration': 1.52}, {'end': 675.241, 'text': "So I guess the lesson to take from that is there's something that looks amazing on paper and then nobody uses it.", 'start': 666.498, 'duration': 8.743}], 'summary': 'Online learners prefer self-paced videos, leading to feature refinement and user engagement insights.', 'duration': 25.452, 'max_score': 649.789, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig649789.jpg'}, {'end': 740.178, 'src': 'embed', 'start': 708.811, 'weight': 0, 'content': [{'end': 709.852, 'text': "And I think we're still growing.", 'start': 708.811, 'duration': 1.041}, {'end': 716.134, 'text': "I don't know in the future what percentage of all developers will be AI developers.", 'start': 711.132, 'duration': 5.002}, {'end': 726.544, 'text': 'I could easily see it being north of 50%, because so many AI developers broadly construed, not just people doing the machine learning modeling,', 'start': 716.995, 'duration': 9.549}, {'end': 732.869, 'text': 'but the people building infrastructure, data pipelines, all the softwares surrounding the core machine learning model.', 'start': 726.544, 'duration': 6.325}, {'end': 734.792, 'text': "Maybe it's even bigger.", 'start': 733.85, 'duration': 0.942}, {'end': 740.178, 'text': 'I feel like today, almost every software engineer has some understanding of the cloud.', 'start': 734.812, 'duration': 5.366}], 'summary': 'Ai developers could potentially make up over 50% of all developers in the future, with many involved in infrastructure and data pipelines.', 'duration': 31.367, 'max_score': 708.811, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig708811.jpg'}, {'end': 824.197, 'src': 'embed', 'start': 793.61, 'weight': 2, 'content': [{'end': 799.315, 'text': "So like the, not just, cause you've mentioned a larger percentage of developers become machine learning people.", 'start': 793.61, 'duration': 5.705}, {'end': 807.021, 'text': 'It seems like more and more the kinds of people who are becoming developers is also growing significantly.', 'start': 800.356, 'duration': 6.665}, {'end': 813.687, 'text': 'I think once upon a time, only a small part of humanity was literate, could read and write.', 'start': 808.142, 'duration': 5.545}, {'end': 817.631, 'text': 'And maybe you thought, maybe not everyone needs to learn to read and write.', 'start': 813.927, 'duration': 3.704}, {'end': 824.197, 'text': 'You just go listen to a few monks read to you, and maybe that was enough.', 'start': 817.671, 'duration': 6.526}], 'summary': 'Rising percentage of developers transitioning to machine learning; growing diversity in developer demographics.', 'duration': 30.587, 'max_score': 793.61, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig793610.jpg'}, {'end': 943.041, 'src': 'embed', 'start': 909.364, 'weight': 1, 'content': [{'end': 910.785, 'text': 'We could give them some reasons.', 'start': 909.364, 'duration': 1.421}, {'end': 919.51, 'text': 'But what I found with the rise of machine learning and data science is that I think the number of people with a concrete use for data science in their daily lives,', 'start': 911.305, 'duration': 8.205}, {'end': 924.853, 'text': 'in their jobs, may be even larger than the number of people with a concrete use for software engineering.', 'start': 919.51, 'duration': 5.343}, {'end': 932.056, 'text': 'For example, if you run a small mom and pop store, I think if you can analyze the data about your sales, your customers,', 'start': 925.473, 'duration': 6.583}, {'end': 936.698, 'text': "I think there's actually real value there, maybe even more than traditional software engineering.", 'start': 932.056, 'duration': 4.642}, {'end': 943.041, 'text': 'So I find that for a lot of my friends in various professions, be it recruiters or accountants,', 'start': 937.358, 'duration': 5.683}], 'summary': 'Rise of machine learning & data science may benefit more people than software engineering, even for small businesses.', 'duration': 33.677, 'max_score': 909.364, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig909364.jpg'}, {'end': 1003.916, 'src': 'embed', 'start': 982.115, 'weight': 3, 'content': [{'end': 991.405, 'text': 'So let me ask, why do you like using a marker and whiteboard, even on the biggest of stages? I think it depends on the concepts you want to explain.', 'start': 982.115, 'duration': 9.29}, {'end': 994.088, 'text': 'For mathematical concepts.', 'start': 992.446, 'duration': 1.642}, {'end': 1003.916, 'text': "it's nice to build up the equation one piece at a time, and the whiteboard marker or the pen and stylus is a very easy way to build up the equation,", 'start': 994.088, 'duration': 9.828}], 'summary': 'Using marker and whiteboard helps to explain mathematical concepts by building up equations one piece at a time.', 'duration': 21.801, 'max_score': 982.115, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig982115.jpg'}, {'end': 1274.738, 'src': 'embed', 'start': 1248.041, 'weight': 5, 'content': [{'end': 1254.885, 'text': "And I'm reminded when I was doing this work at Stanford around that time there was a lot of reinforcement,", 'start': 1248.041, 'duration': 6.844}, {'end': 1258.968, 'text': 'learning theoretical papers but not a lot of practical applications.', 'start': 1254.885, 'duration': 4.083}, {'end': 1268.074, 'text': 'So the autonomous helicopter work for flying helicopters was one of the few practical applications of reinforcement learning at the time,', 'start': 1259.708, 'duration': 8.366}, {'end': 1270.876, 'text': 'which caused it to become pretty well known.', 'start': 1268.074, 'duration': 2.802}, {'end': 1274.738, 'text': 'I feel like we might have almost come full circle with today.', 'start': 1271.996, 'duration': 2.742}], 'summary': 'Autonomous helicopter work at stanford was a notable practical application of reinforcement learning, becoming well known at the time.', 'duration': 26.697, 'max_score': 1248.041, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig1248041.jpg'}, {'end': 1340.569, 'src': 'embed', 'start': 1313.358, 'weight': 6, 'content': [{'end': 1320.881, 'text': "You know, I like theory, but when I work on theory myself and this is personal taste I'm not saying anyone else should do what I do,", 'start': 1313.358, 'duration': 7.523}, {'end': 1330.624, 'text': 'but when I work on theory, I personally enjoy it more if I feel that the work I do will influence people, have positive impact or help someone.', 'start': 1320.881, 'duration': 9.743}, {'end': 1340.569, 'text': 'I remember when many years ago, I was speaking with a mathematics professor and he kind of just said hey, why do you do what you do?', 'start': 1332.444, 'duration': 8.125}], 'summary': 'Theory work is more enjoyable when it can positively influence or help people.', 'duration': 27.211, 'max_score': 1313.358, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig1313358.jpg'}], 'start': 627.677, 'title': 'Machine learning and education', 'summary': 'Explores the impact of machine learning on education and the workforce, emphasizing the growing significance of ai developers, the potential for machine learning to become a widespread skill, and the role of data science in various professions. it also covers the use of marker and whiteboard for teaching mathematical concepts, challenges in developing practical applications of reinforcement learning, and motivation for applied research in education.', 'chapters': [{'end': 964.11, 'start': 627.677, 'title': 'Impact of machine learning on education and workforce', 'summary': 'Discusses the impact of machine learning on education and the workforce, highlighting the growing importance of ai developers and the potential for machine learning to become a widespread skill similar to literacy, as well as the significant role of data science in various professions.', 'duration': 336.433, 'highlights': ["Machine learning's potential impact on the workforce and education The potential for machine learning to become a widespread skill similar to literacy, impacting various professions and enhancing human-to-computer communications.", "Data science's significance in different professions The potential value of data science and machine learning in various professions, surpassing traditional software engineering in terms of concrete use in daily work.", 'The growing importance of AI developers The prediction that a significant percentage, possibly over 50%, of all developers in the future will be AI developers, encompassing those involved in machine learning modeling and related software development.', 'Challenges in implementing features in online education The example of a feature for group watching in online education, which despite being considered brilliant, was not utilized by users who preferred individual video viewing and control.']}, {'end': 1379.443, 'start': 964.49, 'title': 'Marker and whiteboard in education', 'summary': 'Discusses the use of a marker and whiteboard for teaching mathematical concepts, the challenges faced in developing a practical application of reinforcement learning, and the motivation to work on applied research in the face of uncertainty and setbacks.', 'duration': 414.953, 'highlights': ['The use of a marker and whiteboard for teaching mathematical concepts is discussed, emphasizing the simplicity and understandability it brings to complex equations. The simplicity and understandability brought by using a marker and whiteboard for teaching mathematical concepts are highlighted, contributing to enhanced education.', 'The challenges faced in developing a practical application of reinforcement learning for flying helicopters are described, including the difficulties with localization and the iterative process of experimentation. The difficulties with localization and the iterative process of experimentation in developing a practical application of reinforcement learning for flying helicopters are discussed, highlighting the complexity and persistence required in research and development.', 'The motivation to work on applied research in the face of uncertainty and setbacks is explored, emphasizing the preference for practical impact and positive influence on people. The preference for practical impact and positive influence on people as a motivation for working on applied research in the face of uncertainty and setbacks is discussed, highlighting the personal drive and values in pursuing impactful work.']}], 'duration': 751.766, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig627677.jpg', 'highlights': ['The growing importance of AI developers: Prediction of over 50% of all future developers being AI developers.', "Data science's significance in different professions: Potential value surpassing traditional software engineering.", "Machine learning's potential impact on the workforce and education: Potential to become a widespread skill similar to literacy.", 'The use of a marker and whiteboard for teaching mathematical concepts: Emphasizing simplicity and understandability.', 'Challenges in implementing features in online education: Example of group watching feature not being utilized by users.', 'The challenges faced in developing a practical application of reinforcement learning for flying helicopters: Difficulties with localization and iterative experimentation.', 'The motivation to work on applied research in the face of uncertainty and setbacks: Emphasizing preference for practical impact and positive influence on people.']}, {'end': 2057.717, 'segs': [{'end': 1409.713, 'src': 'embed', 'start': 1379.463, 'weight': 3, 'content': [{'end': 1382.304, 'text': "I don't think everyone should do things the same way as I do.", 'start': 1379.463, 'duration': 2.841}, {'end': 1390.147, 'text': "But when I delve into either theory or practice, if I personally have conviction that here's a pathway to help people,", 'start': 1382.564, 'duration': 7.583}, {'end': 1395.209, 'text': 'I find that more satisfying to have that conviction.', 'start': 1390.147, 'duration': 5.062}, {'end': 1396.749, 'text': "That's your path.", 'start': 1395.909, 'duration': 0.84}, {'end': 1402.271, 'text': 'You were a proponent of deep learning before it gained widespread acceptance.', 'start': 1397.69, 'duration': 4.581}, {'end': 1405.932, 'text': 'What did you see in this field that gave you confidence?', 'start': 1403.491, 'duration': 2.441}, {'end': 1409.713, 'text': 'What was your thinking process like in that first decade of the?', 'start': 1406.312, 'duration': 3.401}], 'summary': 'Believes in individual paths, found satisfaction in helping others, early proponent of deep learning', 'duration': 30.25, 'max_score': 1379.463, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig1379463.jpg'}, {'end': 1456.667, 'src': 'embed', 'start': 1430.443, 'weight': 4, 'content': [{'end': 1438.431, 'text': 'And there was this argument, actually, I think it was around 2005 after NeurIPS, at that time called NIPS, but now NeurIPS had ended.', 'start': 1430.443, 'duration': 7.988}, {'end': 1443.376, 'text': 'And Geoff Hinton and I were sitting in the cafeteria outside the conference.', 'start': 1439.132, 'duration': 4.244}, {'end': 1444.458, 'text': 'We had lunch, we were just chatting.', 'start': 1443.397, 'duration': 1.061}, {'end': 1448.621, 'text': 'And Jeff pulled up this napkin, he started sketching this argument on the napkin.', 'start': 1445.018, 'duration': 3.603}, {'end': 1450.682, 'text': "It was very compelling, I'll repeat it.", 'start': 1448.881, 'duration': 1.801}, {'end': 1456.667, 'text': "Human brain has about 100 trillion, so that's 10 to the 14 synaptic connections.", 'start': 1451.943, 'duration': 4.724}], 'summary': "In 2005, at neurips, geoff hinton sketched a compelling argument about the human brain's 10^14 synaptic connections.", 'duration': 26.224, 'max_score': 1430.443, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig1430443.jpg'}, {'end': 1504.264, 'src': 'embed', 'start': 1475.057, 'weight': 2, 'content': [{'end': 1481.098, 'text': "that's 10 to the 14 bits you need to learn in up to 10 to the 9 seconds of your life.", 'start': 1475.057, 'duration': 6.041}, {'end': 1489.18, 'text': "So via this simple argument, which is a lot of problems, it's very simplified, that's 10 to the 5 bits per second you need to learn in your life.", 'start': 1481.958, 'duration': 7.222}, {'end': 1491.561, 'text': 'And I have a one-year-old daughter.', 'start': 1489.96, 'duration': 1.601}, {'end': 1498.042, 'text': 'I am not pointing out 10 to 5 bits per second of labels to her.', 'start': 1491.581, 'duration': 6.461}, {'end': 1504.264, 'text': "And I think I'm a very loving parent, but I'm just not going to do that.", 'start': 1499.223, 'duration': 5.041}], 'summary': "To learn 10^14 bits in 10^9 seconds, one needs to learn 10^5 bits per second, which isn't practical for parenting.", 'duration': 29.207, 'max_score': 1475.057, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig1475057.jpg'}, {'end': 1551.347, 'src': 'embed', 'start': 1522.871, 'weight': 5, 'content': [{'end': 1527.955, 'text': "argument we should go into really convinced me that there's a lot of power to unsupervised learning.", 'start': 1522.871, 'duration': 5.084}, {'end': 1532.499, 'text': 'So that was the part that we actually maybe got wrong.', 'start': 1529.616, 'duration': 2.883}, {'end': 1540.865, 'text': 'I still think unsupervised learning is really important, but in the early days, 10, 15 years ago, a lot of us thought that was the path forward.', 'start': 1532.779, 'duration': 8.086}, {'end': 1546.189, 'text': "Oh, so you're saying that that perhaps was the wrong intuition for the time? For the time.", 'start': 1541.386, 'duration': 4.803}, {'end': 1547.691, 'text': 'That was the part we got wrong.', 'start': 1546.25, 'duration': 1.441}, {'end': 1551.347, 'text': 'The part we got right was the importance of scale.', 'start': 1548.686, 'duration': 2.661}], 'summary': 'Unsupervised learning is powerful, but scale is more important.', 'duration': 28.476, 'max_score': 1522.871, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig1522871.jpg'}, {'end': 1628.523, 'src': 'embed', 'start': 1605.849, 'weight': 1, 'content': [{'end': 1614.852, 'text': 'And there, the intuition was scale will bring performance for the system, so we should chase a larger and larger scale.', 'start': 1605.849, 'duration': 9.003}, {'end': 1620.877, 'text': "And I think people don't realize how groundbreaking it's simple,", 'start': 1615.532, 'duration': 5.345}, {'end': 1625.701, 'text': "but it's a groundbreaking idea that bigger data sets will result in better performance.", 'start': 1620.877, 'duration': 4.824}, {'end': 1628.523, 'text': 'It was controversial at the time.', 'start': 1626.241, 'duration': 2.282}], 'summary': 'Bigger data sets lead to better performance, a groundbreaking idea at the time.', 'duration': 22.674, 'max_score': 1605.849, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig1605849.jpg'}, {'end': 1786.306, 'src': 'embed', 'start': 1755.698, 'weight': 0, 'content': [{'end': 1760.584, 'text': 'it was a combination of novel architecture, but also scale had a lot to do with it.', 'start': 1755.698, 'duration': 4.886}, {'end': 1765.61, 'text': 'If we look at what happened with GP2 and BERT, I think scale was a large part of the story.', 'start': 1760.644, 'duration': 4.966}, {'end': 1768.373, 'text': "yeah, that's that's not often talked about.", 'start': 1766.371, 'duration': 2.002}, {'end': 1774.998, 'text': "is the the scale of the data set it was trained on and the quality of the data set, because there's some.", 'start': 1768.373, 'duration': 6.625}, {'end': 1778.4, 'text': 'uh, so it was like reddit threads that had.', 'start': 1774.998, 'duration': 3.402}, {'end': 1780.021, 'text': 'they were operated highly.', 'start': 1778.4, 'duration': 1.621}, {'end': 1786.306, 'text': "so there's already some weak supervision on a very large data set that people don't often talk about.", 'start': 1780.021, 'duration': 6.285}], 'summary': "Novel architecture and scale, including large data sets, were crucial for gp2 and bert's success.", 'duration': 30.608, 'max_score': 1755.698, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig1755698.jpg'}], 'start': 1379.463, 'title': "Deep learning pioneer's path and importance of scale in ai", 'summary': "Explores the early days of deep learning, emphasizing the significance of conviction in one's pathway and the importance of scale in training learning algorithms. it discusses the need for unsupervised learning and the groundbreaking idea that bigger datasets result in better performance, highlighting recent breakthroughs using transformer networks for language models.", 'chapters': [{'end': 1450.682, 'start': 1379.463, 'title': "Deep learning pioneer's path", 'summary': "Delves into the early days of deep learning and highlights the importance of conviction in one's pathway and the misstep in prioritizing unsupervised learning over supervised learning, with a notable encounter with geoff hinton in 2005.", 'duration': 71.219, 'highlights': ['The early importance of unsupervised learning was a significant misstep in the early days of deep learning, as highlighted by an encounter with Geoff Hinton in 2005 after NeurIPS.', "Having personal conviction in one's pathway is emphasized as more satisfying and impactful when delving into theory or practice.", 'Encounter with Geoff Hinton in 2005, where he sketched a compelling argument on a napkin, showcasing the early insights and discussions in the field of deep learning.']}, {'end': 2057.717, 'start': 1451.943, 'title': 'Importance of scale and unsupervised learning in ai', 'summary': 'Discusses the significance of scale in training learning algorithms and the need for unsupervised learning, emphasizing the requirement of 10^5 bits per second to learn in a lifetime, the groundbreaking idea that bigger datasets result in better performance, and the importance of both novel architecture and scale in recent breakthroughs using transformer networks for language models.', 'duration': 605.774, 'highlights': ['The importance of 10^5 bits per second required to learn in a lifetime due to the 10^14 synaptic connections in the human brain and the need for unsupervised learning.', 'The groundbreaking idea that bigger datasets result in better performance, as evidenced by the graph showing improved accuracy with increased training scale, leading to the inception of the Google Brain project.', 'The combination of novel architecture and scale playing a vital role in recent breakthroughs using transformer networks for language models, such as GP2 and BERT.']}], 'duration': 678.254, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig1379463.jpg', 'highlights': ['The combination of novel architecture and scale playing a vital role in recent breakthroughs using transformer networks for language models, such as GP2 and BERT.', 'The groundbreaking idea that bigger datasets result in better performance, as evidenced by the graph showing improved accuracy with increased training scale, leading to the inception of the Google Brain project.', 'The importance of 10^5 bits per second required to learn in a lifetime due to the 10^14 synaptic connections in the human brain and the need for unsupervised learning.', "Having personal conviction in one's pathway is emphasized as more satisfying and impactful when delving into theory or practice.", 'Encounter with Geoff Hinton in 2005, where he sketched a compelling argument on a napkin, showcasing the early insights and discussions in the field of deep learning.', 'The early importance of unsupervised learning was a significant misstep in the early days of deep learning, as highlighted by an encounter with Geoff Hinton in 2005 after NeurIPS.']}, {'end': 2739.485, 'segs': [{'end': 2100.177, 'src': 'embed', 'start': 2074.525, 'weight': 0, 'content': [{'end': 2080.148, 'text': 'So yeah, so how does one get started in deep learning and where does deeplearning.ai fit into that?', 'start': 2074.525, 'duration': 5.623}, {'end': 2089.733, 'text': "So the deep learning specialization offered by deeplearning.ai is, I think it was Coursera's top specialization.", 'start': 2080.748, 'duration': 8.985}, {'end': 2090.853, 'text': 'It might still be.', 'start': 2089.753, 'duration': 1.1}, {'end': 2100.177, 'text': "So it's a very popular way for people to take that specialization, to learn about everything, from neural networks to how to tune a neural network,", 'start': 2090.933, 'duration': 9.244}], 'summary': "The deep learning specialization by deeplearning.ai is coursera's top specialization, offering a popular way for people to learn about neural networks and tuning them.", 'duration': 25.652, 'max_score': 2074.525, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig2074525.jpg'}, {'end': 2142.691, 'src': 'embed', 'start': 2116.563, 'weight': 1, 'content': [{'end': 2125.166, 'text': 'So what would you say are the prerequisites for somebody to take the deep learning specialization in terms of maybe math or programming background?', 'start': 2116.563, 'duration': 8.603}, {'end': 2130.188, 'text': 'Yeah, need to understand basic programming, since there are programming exercises in Python.', 'start': 2125.686, 'duration': 4.502}, {'end': 2135.829, 'text': 'And the math prereq is quite basic, so no calculus is needed.', 'start': 2131.468, 'duration': 4.361}, {'end': 2142.691, 'text': 'If you know calculus is great, you get better intuitions, but deliberately try to teach that specialization without requiring calculus.', 'start': 2136.05, 'duration': 6.641}], 'summary': 'Prerequisites for deep learning specialization: basic programming (python) and basic math (no calculus required).', 'duration': 26.128, 'max_score': 2116.563, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig2116563.jpg'}, {'end': 2188.825, 'src': 'embed', 'start': 2160.2, 'weight': 2, 'content': [{'end': 2165.165, 'text': 'I think that people that have done the machine learning course will find the deep learning specialization a bit easier,', 'start': 2160.2, 'duration': 4.965}, {'end': 2168.468, 'text': "but it's also possible to jump into the deep learning specialization directly,", 'start': 2165.165, 'duration': 3.303}, {'end': 2177.557, 'text': "but it'll be a little bit harder since we tend to go over faster concepts like how does gradient descent work and what is the objective function,", 'start': 2168.468, 'duration': 9.089}, {'end': 2180.019, 'text': 'which is covered more slowly in the machine learning course?', 'start': 2177.557, 'duration': 2.462}, {'end': 2185.184, 'text': 'Could you briefly mention some of the key concepts in deep learning that students should learn,', 'start': 2180.322, 'duration': 4.862}, {'end': 2188.825, 'text': 'that you envision them learning in the first few months, in the first year or so?', 'start': 2185.184, 'duration': 3.641}], 'summary': 'Deep learning specialization may be easier for machine learning course graduates, but possible to jump directly, covering faster concepts like gradient descent and objective function.', 'duration': 28.625, 'max_score': 2160.2, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig2160200.jpg'}, {'end': 2380.44, 'src': 'embed', 'start': 2353.417, 'weight': 3, 'content': [{'end': 2356.659, 'text': 'use a debugger trace through the code in the traditional software engineering.', 'start': 2353.417, 'duration': 3.242}, {'end': 2364.926, 'text': "It's an evolving discipline, but I find that the people that are really good at debugging machine learning algorithms are easily 10x,", 'start': 2357.3, 'duration': 7.626}, {'end': 2367.088, 'text': 'maybe 100x faster at getting something to work.', 'start': 2364.926, 'duration': 2.162}, {'end': 2372.733, 'text': 'And the basic process of debugging is so the bug in this case?', 'start': 2368.249, 'duration': 4.484}, {'end': 2380.44, 'text': "why isn't this thing learning, improving, sort of going into the questions of overfitting and all those kinds of things?", 'start': 2372.733, 'duration': 7.707}], 'summary': 'Debugging machine learning algorithms can make developers 10x-100x faster at getting something to work.', 'duration': 27.023, 'max_score': 2353.417, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig2353417.jpg'}, {'end': 2440.957, 'src': 'embed', 'start': 2416.696, 'weight': 4, 'content': [{'end': 2422.579, 'text': 'or sort of is the biggest challenge for them once they get over that hill?', 'start': 2416.696, 'duration': 5.883}, {'end': 2426.381, 'text': 'It hooks them and it inspires them, and they really get it.', 'start': 2423.339, 'duration': 3.042}, {'end': 2435.35, 'text': 'Similar to learning mathematics, I think one of the challenges of deep learning is that there are a lot of concepts that build on top of each other.', 'start': 2428.183, 'duration': 7.167}, {'end': 2440.957, 'text': "If you ask me what's hard about mathematics, I have a hard time pinpointing one thing.", 'start': 2436.972, 'duration': 3.985}], 'summary': 'Deep learning presents challenges, inspiring breakthroughs in its complexity.', 'duration': 24.261, 'max_score': 2416.696, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig2416696.jpg'}, {'end': 2486.642, 'src': 'embed', 'start': 2458.17, 'weight': 5, 'content': [{'end': 2467.056, 'text': 'So in the deep learning specialization, try to break down the concepts to maximize the odds of each component being understandable.', 'start': 2458.17, 'duration': 8.886}, {'end': 2469.317, 'text': 'So when you move on, to the more advanced thing.', 'start': 2467.076, 'duration': 2.241}, {'end': 2470.738, 'text': 'We learn, you know, confidence.', 'start': 2469.377, 'duration': 1.361}, {'end': 2478.58, 'text': 'Hopefully you have enough intuitions from the earlier sections to then understand why we structure confidence in a certain way.', 'start': 2470.958, 'duration': 7.622}, {'end': 2486.642, 'text': 'And then eventually why we built, you know, RNNs and LSTMs or attention models in a certain way, building on top of the earlier concepts.', 'start': 2478.82, 'duration': 7.822}], 'summary': 'Deep learning specialization breaks down concepts for better understanding and progression to advanced topics.', 'duration': 28.472, 'max_score': 2458.17, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig2458170.jpg'}, {'end': 2644.527, 'src': 'embed', 'start': 2621.825, 'weight': 6, 'content': [{'end': 2629.316, 'text': "what's your best example of an actual deployed reinforcement learning application among senior machine learning researchers?", 'start': 2621.825, 'duration': 7.491}, {'end': 2634.624, 'text': 'Again, there are some emerging ones, but there are not that many great examples.', 'start': 2629.737, 'duration': 4.887}, {'end': 2637.645, 'text': "I think you're absolutely right.", 'start': 2635.384, 'duration': 2.261}, {'end': 2644.527, 'text': "The sad thing is there hasn't been a big application, impactful real world application of reinforcement learning.", 'start': 2638.305, 'duration': 6.222}], 'summary': 'Limited impactful real-world applications of reinforcement learning among senior researchers.', 'duration': 22.702, 'max_score': 2621.825, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig2621825.jpg'}, {'end': 2725.778, 'src': 'embed', 'start': 2701.426, 'weight': 7, 'content': [{'end': 2708.469, 'text': "Even within machine learning, I feel like deep learning is so exciting, but the AI team shouldn't just use deep learning.", 'start': 2701.426, 'duration': 7.043}, {'end': 2710.85, 'text': 'I find that my teams use a portfolio of tools.', 'start': 2708.529, 'duration': 2.321}, {'end': 2719.974, 'text': "And maybe that's not the exciting thing to say, but some days we use a neural net, some days we use a PCA.", 'start': 2711.85, 'duration': 8.124}, {'end': 2722.876, 'text': 'Actually, the other day I was sitting down with my team looking at PCA residuals,', 'start': 2720.175, 'duration': 2.701}, {'end': 2725.778, 'text': "trying to figure out what's going on with PCA applied to a manufacturing problem.", 'start': 2722.876, 'duration': 2.902}], 'summary': 'Teams use a portfolio of tools, including neural nets and pca, for various tasks.', 'duration': 24.352, 'max_score': 2701.426, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig2701426.jpg'}], 'start': 2057.717, 'title': 'Deep learning specialization and teaching', 'summary': 'Covers insights into the deep learning specialization by deeplearning.ai, including its popularity, prerequisites, key concepts, and practical know-how. additionally, it discusses the challenges of teaching deep learning and reinforcement learning, emphasizing the need for breaking down concepts and the limited real-world impact of reinforcement learning applications.', 'chapters': [{'end': 2456.929, 'start': 2057.717, 'title': 'Deep learning specialization insights', 'summary': 'Discusses the popularity and prerequisites of the deep learning specialization offered by deeplearning.ai, the key concepts in deep learning, and the practical know-how provided to efficiently build and debug neural networks.', 'duration': 399.212, 'highlights': ["The deep learning specialization offered by deeplearning.ai is highly popular, being Coursera's top specialization, providing practical know-how for building and debugging neural networks.", 'The prerequisites for the deep learning specialization include basic programming skills and a basic understanding of math, with high school math being sufficient and a little basic linear algebra being beneficial.', 'The deep learning specialization covers foundational concepts such as neural networks, training techniques, differences between optimization algorithms, and practical decision-making processes, like when to collect more data and when not to.', 'Analogous to learning to code, the systematic frameworks for building practical machine learning and debugging algorithms are emphasized, aiming to make programmers efficient in constructing and debugging machine learning models.', 'One of the challenges of deep learning is the interconnected nature of its concepts, similar to learning mathematics, where missing a prerequisite concept can hinder understanding of subsequent topics.']}, {'end': 2739.485, 'start': 2458.17, 'title': 'Teaching deep learning and reinforcement learning', 'summary': 'Discusses the challenges of teaching deep learning and reinforcement learning, emphasizing the importance of breaking down concepts for better understanding and the limited real-world impact of reinforcement learning applications.', 'duration': 281.315, 'highlights': ['The challenge of teaching deep learning and reinforcement learning lies in breaking down concepts for better understanding. The speaker emphasizes the importance of breaking down concepts in the deep learning specialization to maximize understanding, particularly in advanced topics such as confidence, RNNs, LSTMs, and attention models.', 'Reinforcement learning has limited real-world impact, mostly observed in toy and game domains. The speaker notes the lack of impactful real-world applications of reinforcement learning, highlighting its biggest impact in the toy and game domain and its limited deployed applications.', 'The speaker advocates for using a portfolio of tools beyond deep learning for practical applications. The speaker emphasizes the need to use a portfolio of tools beyond deep learning, such as PCA, graphical models, and knowledge graphs, for practical applications, despite the excitement around deep learning.']}], 'duration': 681.768, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig2057717.jpg', 'highlights': ["The deep learning specialization by deeplearning.ai is Coursera's top specialization, providing practical know-how for building and debugging neural networks.", 'The prerequisites for the deep learning specialization include basic programming skills and a basic understanding of math, with high school math being sufficient and a little basic linear algebra being beneficial.', 'The deep learning specialization covers foundational concepts such as neural networks, training techniques, differences between optimization algorithms, and practical decision-making processes.', 'The systematic frameworks for building practical machine learning and debugging algorithms are emphasized, aiming to make programmers efficient in constructing and debugging machine learning models.', 'The interconnected nature of deep learning concepts poses a challenge, similar to learning mathematics, where missing a prerequisite concept can hinder understanding of subsequent topics.', 'The challenge of teaching deep learning and reinforcement learning lies in breaking down concepts for better understanding, particularly in advanced topics such as confidence, RNNs, LSTMs, and attention models.', 'Reinforcement learning has limited real-world impact, mostly observed in toy and game domains, with its biggest impact in the toy and game domain and limited deployed applications.', 'The need to use a portfolio of tools beyond deep learning, such as PCA, graphical models, and knowledge graphs, for practical applications is emphasized.']}, {'end': 3776.785, 'segs': [{'end': 2768.9, 'src': 'embed', 'start': 2739.805, 'weight': 2, 'content': [{'end': 2742.649, 'text': 'So I think reinforcement learning should be in that portfolio.', 'start': 2739.805, 'duration': 2.844}, {'end': 2745.213, 'text': "And then it's about balancing how much we teach all of these things.", 'start': 2742.709, 'duration': 2.504}, {'end': 2747.936, 'text': 'And the world should have diverse skills.', 'start': 2745.433, 'duration': 2.503}, {'end': 2751.381, 'text': "It'd be sad if everyone just learned one narrow thing.", 'start': 2747.996, 'duration': 3.385}, {'end': 2754.385, 'text': 'Yeah, the diverse skill help you discover the right tool for the job.', 'start': 2751.641, 'duration': 2.744}, {'end': 2760.348, 'text': 'What is the most beautiful, surprising or inspiring idea in deep learning to you?', 'start': 2755.481, 'duration': 4.867}, {'end': 2764.394, 'text': 'Something that captivated your imagination?', 'start': 2760.889, 'duration': 3.505}, {'end': 2768.9, 'text': 'Is it the scale that could be the performance that could be achieved with scale?', 'start': 2764.774, 'duration': 4.126}], 'summary': 'Balancing diverse skills in learning is crucial for discovering the right tools for the job.', 'duration': 29.095, 'max_score': 2739.805, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig2739805.jpg'}, {'end': 2815.694, 'src': 'embed', 'start': 2787.619, 'weight': 0, 'content': [{'end': 2790.04, 'text': 'I still think unsupervised learning is a beautiful idea.', 'start': 2787.619, 'duration': 2.421}, {'end': 2799.365, 'text': 'At both this past, NeurIPS and ICML I was attending workshops or listening to various talks about self-supervised learning,', 'start': 2790.06, 'duration': 9.305}, {'end': 2804.227, 'text': "which is one vertical segment, maybe of sort of unsupervised learning that I'm excited about.", 'start': 2799.365, 'duration': 4.862}, {'end': 2808.449, 'text': 'Maybe just to summarize the idea, I guess you know the idea described briefly.', 'start': 2805.348, 'duration': 3.101}, {'end': 2809.11, 'text': 'No, please.', 'start': 2808.649, 'duration': 0.461}, {'end': 2811.451, 'text': "So here's the example of self-supervised learning.", 'start': 2809.29, 'duration': 2.161}, {'end': 2815.694, 'text': "Let's say we grab a lot of unlabeled images off the internet.", 'start': 2812.211, 'duration': 3.483}], 'summary': 'Excitement about self-supervised learning at neurips and icml conferences.', 'duration': 28.075, 'max_score': 2787.619, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig2787619.jpg'}, {'end': 3029.507, 'src': 'embed', 'start': 3003.235, 'weight': 3, 'content': [{'end': 3008.117, 'text': 'there are people that finished it in less than a month by working more intensely and studying more intensely.', 'start': 3003.235, 'duration': 4.882}, {'end': 3010.078, 'text': 'So it really depends on the individual.', 'start': 3008.157, 'duration': 1.921}, {'end': 3017.622, 'text': 'When we created the Deep Learning Specialization, we wanted to make it very accessible and very affordable.', 'start': 3011.119, 'duration': 6.503}, {'end': 3021.764, 'text': "And with Coursera and Deep Learning DIY's education mission.", 'start': 3017.642, 'duration': 4.122}, {'end': 3029.507, 'text': "one of the things that's really important to me is that if there's someone for whom paying anything is a financial hardship,", 'start': 3021.764, 'duration': 7.743}], 'summary': 'Deep learning specialization designed for accessibility and affordability. completion time varies by individual.', 'duration': 26.272, 'max_score': 3003.235, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig3003235.jpg'}, {'end': 3071.233, 'src': 'embed', 'start': 3047.102, 'weight': 4, 'content': [{'end': 3054.306, 'text': 'How do they go about day-to-day sort of specific advice about learning, about their journey in the world of deep learning, machine learning?', 'start': 3047.102, 'duration': 7.204}, {'end': 3061.018, 'text': 'I think getting the habit of learning is key, and that means regularity.', 'start': 3054.969, 'duration': 6.049}, {'end': 3069.67, 'text': "For example, we send out our weekly newsletter, The Batch, every Wednesday, so people know it's coming Wednesday.", 'start': 3061.038, 'duration': 8.632}, {'end': 3071.233, 'text': 'you can spend a little bit of time on Wednesday.', 'start': 3069.67, 'duration': 1.563}], 'summary': 'Regular learning habits are key; for example, the batch is sent out every wednesday.', 'duration': 24.131, 'max_score': 3047.102, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig3047102.jpg'}, {'end': 3259.21, 'src': 'embed', 'start': 3233.002, 'weight': 5, 'content': [{'end': 3239.106, 'text': 'We know that that act of taking notes, preferably handwritten notes, increases retention.', 'start': 3233.002, 'duration': 6.104}, {'end': 3247.361, 'text': "So as you're sort of watching the video, just kind of pausing maybe and then taking the basic insights down on paper.", 'start': 3240.396, 'duration': 6.965}, {'end': 3250.083, 'text': 'Yeah So there have been a few studies.', 'start': 3247.962, 'duration': 2.121}, {'end': 3259.21, 'text': "If you search online, you find some of these studies that taking handwritten notes because handwriting is slower, as we're saying just now,", 'start': 3250.163, 'duration': 9.047}], 'summary': 'Taking handwritten notes increases retention, supported by studies.', 'duration': 26.208, 'max_score': 3233.002, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig3233002.jpg'}, {'end': 3410.115, 'src': 'embed', 'start': 3365.598, 'weight': 6, 'content': [{'end': 3368.039, 'text': 'one minute spent has a ripple effect, right?', 'start': 3365.598, 'duration': 2.441}, {'end': 3371.519, 'text': 'Through years of time, which is fascinating to think about.', 'start': 3368.439, 'duration': 3.08}, {'end': 3375.96, 'text': 'How does one make a career out of an interest in deep learning?', 'start': 3372.78, 'duration': 3.18}, {'end': 3378.661, 'text': 'Do you have advice for people?', 'start': 3375.98, 'duration': 2.681}, {'end': 3381.502, 'text': 'We just talked about sort of the beginning, early steps.', 'start': 3378.681, 'duration': 2.821}, {'end': 3388.043, 'text': "but if you want to make it an entire life's journey, or at least a journey of a decade or two, how do you do it??", 'start': 3381.502, 'duration': 6.541}, {'end': 3390.644, 'text': 'So most important thing is to get started.', 'start': 3388.863, 'duration': 1.781}, {'end': 3403.131, 'text': 'And I think in the early parts of a career, coursework, like the deep learning specialization, is a very efficient way to master this material.', 'start': 3391.084, 'duration': 12.047}, {'end': 3410.115, 'text': 'Because instructors be it me or someone else, or Lawrence Moroney,', 'start': 3404.932, 'duration': 5.183}], 'summary': 'Efficiently master deep learning through coursework and get started early in career.', 'duration': 44.517, 'max_score': 3365.598, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig3365598.jpg'}, {'end': 3481.783, 'src': 'embed', 'start': 3457.909, 'weight': 7, 'content': [{'end': 3470.396, 'text': 'then most people need to go on to either ideally work on projects and then maybe also continue their learning by reading blog posts and research papers and things like that.', 'start': 3457.909, 'duration': 12.487}, {'end': 3472.398, 'text': 'Doing projects is really important.', 'start': 3471.197, 'duration': 1.201}, {'end': 3477.881, 'text': "And again, I think it's important to start small and just do something.", 'start': 3473.178, 'duration': 4.703}, {'end': 3481.783, 'text': 'Today, you read about deep learning, it feels like, oh, all these people are doing such exciting things.', 'start': 3478.401, 'duration': 3.382}], 'summary': 'Most people need to work on projects and continue learning by reading blog posts and research papers.', 'duration': 23.874, 'max_score': 3457.909, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig3457909.jpg'}, {'end': 3599.871, 'src': 'embed', 'start': 3566.043, 'weight': 9, 'content': [{'end': 3570.404, 'text': "If someone's aspiration is to be a professor at the top academic university, you just need a PhD to do that.", 'start': 3566.043, 'duration': 4.361}, {'end': 3577.727, 'text': 'But if it goes to start a company, build a company, do great technical work, I think a PhD is a good experience.', 'start': 3571.185, 'duration': 6.542}, {'end': 3581.348, 'text': 'But I would look at the different options available to someone.', 'start': 3577.767, 'duration': 3.581}, {'end': 3583.049, 'text': 'where are the places where you can get a job?', 'start': 3581.348, 'duration': 1.701}, {'end': 3586.91, 'text': 'where are the places you can get in a PhD program and weigh the pros and cons of those?', 'start': 3583.049, 'duration': 3.861}, {'end': 3590.146, 'text': 'So, just to linger on that for a little bit longer,', 'start': 3587.745, 'duration': 2.401}, {'end': 3599.871, 'text': 'what final dreams and goals do you think people should have? So what options should they explore? So you can work in industry?', 'start': 3590.146, 'duration': 9.725}], 'summary': 'A phd is beneficial for aspiring professors and those pursuing technical work in a company, but other options should be considered for career goals.', 'duration': 33.828, 'max_score': 3566.043, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig3566043.jpg'}], 'start': 2739.805, 'title': 'Deep learning specialization', 'summary': 'Delves into the significance of diverse skills in deep learning, the emergence of self-supervised learning, and the potential impact in computer vision and video. it also highlights efficient learning strategies, including the flexibility of a 16-week course, the value of regular study, and career advice to start with coursework. additionally, it provides insights into career advice in machine learning, stressing the importance of starting small with projects, gaining skills through small steps, and considering the impact of peers and environment, while discussing options such as pursuing a phd, working in industry, or academia.', 'chapters': [{'end': 2979.607, 'start': 2739.805, 'title': 'Unsupervised learning portfolio', 'summary': 'Discusses the importance of diverse skills in the world of deep learning and highlights the growing traction of self-supervised learning as a piece of unsupervised learning that has the potential to unlock a significant real-world impact, particularly in computer vision and video.', 'duration': 239.802, 'highlights': ['Self-supervised learning, such as creating tasks like predicting image rotations or word embeddings, has the potential to unlock power in machine learning systems.', 'The concept of self-supervised learning is gaining traction and is close to being useful, particularly in computer vision and video applications.', 'Other unsupervised learning techniques like SMAS coding and ICA slow feature analysis are also exciting ideas that could lead to better algorithms in deep learning.', 'The speaker emphasizes the importance of diverse skills in the world and the need for a portfolio of techniques for generating made-up tasks in unsupervised learning.']}, {'end': 3457.909, 'start': 2980.388, 'title': 'Efficient learning in deep learning', 'summary': 'Discusses the deep learning specialization by deeplearning.ai, emphasizing the flexibility of the 16-week course, the importance of regularity in studying, the effectiveness of handwritten note-taking for long-term retention, and the career advice to start with coursework for efficient learning.', 'duration': 477.521, 'highlights': ["The official length of the deep learning specialization is 16 weeks, but it's go at your own pace, with some individuals finishing it in less than a month by working more intensely and studying more. The deep learning specialization is flexible, allowing individuals to complete it in less than a month by working more intensely.", 'The chapter emphasizes the importance of regularity in studying, recommending a daily schedule to cultivate the habit of learning, making it easier and more consistent over time. Regular studying habits, such as weekly learning sessions and daily reading or studying, are crucial for efficient learning and skill development.', 'Handwritten note-taking during learning, especially in deep learning courses, is highlighted as an effective method to increase retention through recoding knowledge and deeper processing of the material. Taking handwritten notes promotes long-term retention by requiring deeper processing of the material, as opposed to typing, leading to better knowledge retention.', 'Starting with coursework, like the deep learning specialization, is an efficient way for individuals to master the material in the early stages of their career in deep learning. Coursework, such as the deep learning specialization, is recommended for efficiently learning new concepts in the early stages of a career in deep learning.']}, {'end': 3776.785, 'start': 3457.909, 'title': 'Career advice in machine learning', 'summary': 'Emphasizes the importance of starting small with projects, gaining skills through small steps, and considering the impact of peers and environment when pursuing a career in machine learning, while discussing the options of pursuing a phd, working in industry, or academia.', 'duration': 318.876, 'highlights': ['The chapter emphasizes the importance of starting small with projects and gaining skills through small steps. Doing projects is important, starting small and doing something, gaining skills to do bigger projects.', 'The chapter discusses the impact of peers and environment when pursuing a career in machine learning. Emphasizes the influence of the people you interact with daily, advising to consider the team and manager when joining a company.', 'The chapter discusses the options of pursuing a PhD, working in industry, or academia. Discusses the different career paths including pursuing a PhD, working in industry for large companies or research groups, academia, or building a startup.']}], 'duration': 1036.98, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig2739805.jpg', 'highlights': ['Self-supervised learning has the potential to unlock power in machine learning systems.', 'The concept of self-supervised learning is gaining traction, particularly in computer vision and video applications.', 'The importance of diverse skills and the need for a portfolio of techniques for generating tasks in unsupervised learning is emphasized.', 'The deep learning specialization is flexible, allowing individuals to complete it in less than a month by working more intensely.', 'Regular studying habits, such as weekly learning sessions and daily reading, are crucial for efficient learning and skill development.', 'Handwritten note-taking during learning is highlighted as an effective method to increase retention.', 'Starting with coursework, like the deep learning specialization, is an efficient way for individuals to master the material in the early stages of their career in deep learning.', 'The importance of starting small with projects and gaining skills through small steps is emphasized.', 'The influence of peers and environment when pursuing a career in machine learning is discussed.', 'The different career paths including pursuing a PhD, working in industry, academia, or building a startup are discussed.']}, {'end': 4272.659, 'segs': [{'end': 3882.03, 'src': 'embed', 'start': 3856.392, 'weight': 1, 'content': [{'end': 3864.738, 'text': 'So as you build a startup, you have to constantly ask the question, will the customer give a thumbs up on this? I think so.', 'start': 3856.392, 'duration': 8.346}, {'end': 3868.341, 'text': 'I think startups that are very customer-focused, customer-obsessed,', 'start': 3864.838, 'duration': 3.503}, {'end': 3875.846, 'text': 'deeply understand the customer and are oriented to serve the customer are more likely to succeed.', 'start': 3868.341, 'duration': 7.505}, {'end': 3882.03, 'text': 'With the provisional that I think all of us should only do things that we think create social good and moves the world forward.', 'start': 3876.567, 'duration': 5.463}], 'summary': 'Customer-focused startups more likely to succeed. aim for social good.', 'duration': 25.638, 'max_score': 3856.392, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig3856392.jpg'}, {'end': 3976.464, 'src': 'embed', 'start': 3947.058, 'weight': 0, 'content': [{'end': 3952.481, 'text': 'That came out of my group and I found that to be actually the most fun part of my job.', 'start': 3947.058, 'duration': 5.423}, {'end': 3961.7, 'text': 'So what I wanted to do was to build AI Fund as a startup studio to systematically create new startups from scratch.', 'start': 3953.563, 'duration': 8.137}, {'end': 3965.013, 'text': 'With all the things we can now do with AI.', 'start': 3962.791, 'duration': 2.222}, {'end': 3976.464, 'text': 'I think the ability to build new teams to go after this rich space of opportunities is a very important mechanism to get these projects done that I think will move the world forward.', 'start': 3965.013, 'duration': 11.451}], 'summary': 'Ai fund aims to create new startups using ai, leveraging its potential for innovation and progress.', 'duration': 29.406, 'max_score': 3947.058, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig3947058.jpg'}, {'end': 4060.775, 'src': 'embed', 'start': 4033.918, 'weight': 2, 'content': [{'end': 4041.463, 'text': "it's actually a place for us to build startups from scratch, so we often bring in founders and work with them,", 'start': 4033.918, 'duration': 7.545}, {'end': 4051.129, 'text': 'or maybe even have existing ideas that we match founders with, and then this launches, you know, hopefully into successful companies.', 'start': 4041.463, 'duration': 9.666}, {'end': 4060.175, 'text': 'so how close are you to figuring out a way to automate the process of starting from scratch and building a successful ai startup?', 'start': 4051.129, 'duration': 9.046}, {'end': 4060.775, 'text': 'Yeah,', 'start': 4060.575, 'duration': 0.2}], 'summary': 'Building startups from scratch, matching founders with ideas, aiming for successful companies. progress on automating the process?', 'duration': 26.857, 'max_score': 4033.918, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig4033918.jpg'}], 'start': 3777.415, 'title': 'Building successful ai startups', 'summary': 'Discusses the importance of being customer-focused, building meaningful startups, and the role of a startup studio in systematically creating successful ai startups, emphasizing the need for social good and meaningful impact.', 'chapters': [{'end': 4272.659, 'start': 3777.415, 'title': 'Building successful ai startups', 'summary': 'Discusses the importance of being customer-focused, building meaningful startups, and the role of a startup studio in systematically creating successful ai startups, emphasizing the need for social good and meaningful impact.', 'duration': 495.244, 'highlights': ['The AI Fund aims to systematically create new startups from scratch using AI capabilities, with a focus on serving the customer and creating meaningful impact. The AI Fund aims to systematically create new startups from scratch using AI capabilities, with a focus on serving the customer and creating meaningful impact.', 'The chapter emphasizes the importance of being customer-focused and outcome-driven in building startups, with a focus on understanding and serving the customer to increase the likelihood of success. The chapter emphasizes the importance of being customer-focused and outcome-driven in building startups, with a focus on understanding and serving the customer to increase the likelihood of success.', 'The discussion revolves around the role of a startup studio in developing a blueprint for successful AI startups, providing support structures to reduce the loneliness of entrepreneurship and make key decisions, and the need to build companies that move the world forward. The discussion revolves around the role of a startup studio in developing a blueprint for successful AI startups, providing support structures to reduce the loneliness of entrepreneurship and make key decisions, and the need to build companies that move the world forward.']}], 'duration': 495.244, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig3777415.jpg', 'highlights': ['The AI Fund aims to systematically create new startups from scratch using AI capabilities, with a focus on serving the customer and creating meaningful impact.', 'The chapter emphasizes the importance of being customer-focused and outcome-driven in building startups, with a focus on understanding and serving the customer to increase the likelihood of success.', 'The discussion revolves around the role of a startup studio in developing a blueprint for successful AI startups, providing support structures to reduce the loneliness of entrepreneurship and make key decisions, and the need to build companies that move the world forward.']}, {'end': 5340.765, 'segs': [{'end': 4388.449, 'src': 'embed', 'start': 4318.02, 'weight': 0, 'content': [{'end': 4322.743, 'text': 'So I think the next wave for AI is for us to also transform all of those other industries.', 'start': 4318.02, 'duration': 4.723}, {'end': 4328.605, 'text': 'There was a McKinsey study estimating $13 trillion of global economic growth.', 'start': 4323.443, 'duration': 5.162}, {'end': 4333.327, 'text': 'US GDP is $19 trillion, so 13 trillion is a big number.', 'start': 4329.806, 'duration': 3.521}, {'end': 4337.829, 'text': 'Or PwC estimates $16 trillion, so whatever number is large.', 'start': 4333.367, 'duration': 4.462}, {'end': 4343.172, 'text': 'But the interesting thing to me was a lot of that impact would be outside the software internet sector.', 'start': 4338.43, 'duration': 4.742}, {'end': 4349.754, 'text': 'So we need more teams to work with these companies to help them adopt AI.', 'start': 4343.832, 'duration': 5.922}, {'end': 4355.836, 'text': 'And I think this is one of the things that will help drive global economic growth and make humanity more powerful.', 'start': 4349.834, 'duration': 6.002}, {'end': 4357.817, 'text': 'And like you said, the impact is there.', 'start': 4356.016, 'duration': 1.801}, {'end': 4363.759, 'text': 'So what are the best industries, the biggest industries where AI can help, perhaps outside the software tech sector?', 'start': 4357.957, 'duration': 5.802}, {'end': 4365.983, 'text': "Frankly, I think it's all of them.", 'start': 4364.562, 'duration': 1.421}, {'end': 4373.545, 'text': "Some of the ones I'm spending a lot of time on are manufacturing, agriculture, looking into healthcare.", 'start': 4368.103, 'duration': 5.442}, {'end': 4378.766, 'text': 'For example, in manufacturing we do a lot of work in visual inspection,', 'start': 4374.645, 'duration': 4.121}, {'end': 4388.449, 'text': 'where today there are people standing around using the human eye to check if this plastic part or the smartphone or this thing has a scratch or a dent or something in it.', 'start': 4378.766, 'duration': 9.683}], 'summary': "Ai's next wave will impact various industries, with estimates of $13-16 trillion global economic growth, driving the need for ai adoption and impact across sectors like manufacturing, agriculture, and healthcare.", 'duration': 70.429, 'max_score': 4318.02, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig4318020.jpg'}, {'end': 4503.501, 'src': 'embed', 'start': 4477.224, 'weight': 3, 'content': [{'end': 4483.848, 'text': "that's online and taught briefly in the AI for Everyone course on Coursera about the long-term journey that companies should take.", 'start': 4477.224, 'duration': 6.624}, {'end': 4486.59, 'text': 'But the first step is actually to start small.', 'start': 4484.289, 'duration': 2.301}, {'end': 4491.854, 'text': "I've seen a lot more companies fail by starting too big than by starting too small.", 'start': 4487.151, 'duration': 4.703}, {'end': 4494.536, 'text': 'Take even Google.', 'start': 4492.855, 'duration': 1.681}, {'end': 4499.52, 'text': "Most people don't realize how hard it was and how controversial it was in the early days.", 'start': 4494.796, 'duration': 4.724}, {'end': 4503.501, 'text': 'So when I started Google Brain, it was controversial.', 'start': 4500.18, 'duration': 3.321}], 'summary': 'Starting small is crucial for long-term success, as even google faced challenges in its early days.', 'duration': 26.277, 'max_score': 4477.224, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig4477224.jpg'}, {'end': 4802.84, 'src': 'embed', 'start': 4780.111, 'weight': 4, 'content': [{'end': 4787.935, 'text': "what we've become good at is working with our partners to think through all the things beyond just the machine learning model,", 'start': 4780.111, 'duration': 7.824}, {'end': 4796.038, 'text': 'running the Jupyter Notebook, build the entire system, manage the change process and figure out how to deploy this in a way that has an actual impact.', 'start': 4787.935, 'duration': 8.103}, {'end': 4802.84, 'text': "The processes that the large software tech companies use for deploying don't work for a lot of other scenarios.", 'start': 4796.998, 'duration': 5.842}], 'summary': 'We excel in deploying machine learning models with impact beyond just the technology, adapting processes to various scenarios.', 'duration': 22.729, 'max_score': 4780.111, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig4780111.jpg'}, {'end': 4896.438, 'src': 'embed', 'start': 4866.182, 'weight': 6, 'content': [{'end': 4871.067, 'text': 'So much of your work and our discussion today has been on applied AI.', 'start': 4866.182, 'duration': 4.885}, {'end': 4878.991, 'text': 'maybe you can even call narrow AI, where the goal is to create systems that automate some specific process that adds a lot of value to the world.', 'start': 4872.168, 'duration': 6.823}, {'end': 4887.234, 'text': "But there's another branch of AI starting with Alan Turing that kind of dreams of creating human level or superhuman level intelligence.", 'start': 4879.871, 'duration': 7.363}, {'end': 4890.375, 'text': 'Is this something you dream of as well?', 'start': 4888.575, 'duration': 1.8}, {'end': 4896.438, 'text': 'Do you think we human beings will ever build a human level intelligence or superhuman level intelligence system?', 'start': 4890.516, 'duration': 5.922}], 'summary': 'Discussion on applied ai and the pursuit of human level intelligence.', 'duration': 30.256, 'max_score': 4866.182, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig4866182.jpg'}, {'end': 5115.831, 'src': 'embed', 'start': 5087.121, 'weight': 5, 'content': [{'end': 5090.361, 'text': 'There may be even more that we need to do than education.', 'start': 5087.121, 'duration': 3.24}, {'end': 5094.342, 'text': 'I think bias is a serious issue.', 'start': 5092.222, 'duration': 2.12}, {'end': 5100.023, 'text': 'There are adverse uses of AI like deepfakes being used for various nefarious purposes.', 'start': 5095.082, 'duration': 4.941}, {'end': 5115.831, 'text': 'So I worry about some teams maybe accidentally and I hope not deliberately making a lot of noise about problems in the distant future rather than focusing on some of the much harder problems.', 'start': 5100.663, 'duration': 15.168}], 'summary': 'Ai bias and misuse concerns overshadow education efforts.', 'duration': 28.71, 'max_score': 5087.121, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig5087121.jpg'}], 'start': 4274.195, 'title': "Ai's impact on non-tech industries", 'summary': 'Discusses the $13 trillion estimated global economic growth from ai adoption, emphasizing the potential impact on non-tech industries such as manufacturing, agriculture, and healthcare. it also addresses the need for more teams to collaborate with companies outside the software internet sector.', 'chapters': [{'end': 4436.315, 'start': 4274.195, 'title': "Ai's impact on non-tech industries", 'summary': 'Discusses the potential impact of ai on non-tech industries, highlighting the $13 trillion estimated global economic growth from ai adoption and the need for more teams to work with companies outside the software internet sector. key industries for ai implementation include manufacturing, agriculture, and healthcare.', 'duration': 162.12, 'highlights': ['AI has the potential to drive global economic growth, with estimates of $13 trillion or $16 trillion impact, largely outside the software internet sector.', 'There is a need for more teams to work with companies outside the software internet sector to help them adopt AI and drive global economic growth.', 'Key industries for AI implementation include manufacturing, agriculture, and healthcare, with examples of visual inspection in manufacturing using AI to improve yield and quality.']}, {'end': 4845.545, 'start': 4436.335, 'title': 'Ai transformation playbook', 'summary': "Discusses the importance of starting small in ai projects, with examples from google's early days, highlighting the challenges in building and deploying machine learning systems and the need for robustness, generalization, and good software engineering work.", 'duration': 409.21, 'highlights': ["Starting small in AI projects is crucial, as demonstrated by Google's early successes with speech recognition and Google Maps, leading to a ripple effect within the company, and helping teams gain faith and learn about new technologies.", 'Challenges in building and deploying machine learning systems include the gulf between developing on a laptop and running in a production deployment setting, and the need for robustness, generalization, and good software engineering work.', 'The chapter emphasizes the importance of redesigning tasks and managing change when automating processes with machine learning, as well as the need to work with partners to build the entire system, manage the change process, and deploy in a way that has an actual impact.', "In deploying machine learning systems, it's essential to consider maintenance, dev ops, and other aspects, which may require new systematic terminology and concepts, as these are still evolving in the industry."]}, {'end': 5340.765, 'start': 4845.545, 'title': 'The future of ai and humanity', 'summary': 'Explores the future of ai, discussing the potential for human-level or superhuman-level intelligence, concerns about the long-term fate of humanity, and the need to align ai systems with human values, while highlighting the current challenges in ai such as bias, wealth inequality, and adverse uses like deepfakes.', 'duration': 495.22, 'highlights': ['The chapter explores the future of AI, discussing the potential for human-level or superhuman-level intelligence, concerns about the long-term fate of humanity, and the need to align AI systems with human values. The discussion delves into the dream of achieving human-level or superhuman-level intelligence through AI, along with concerns about the long-term fate of humanity and the importance of aligning AI systems with human values.', 'The current challenges in AI are highlighted, including bias, wealth inequality, and adverse uses like deepfakes. The chapter emphasizes the existing challenges in AI, such as bias, wealth inequality, and the adverse uses of AI, such as deepfakes, which are impacting society.', 'Andrew Ng expresses concerns about the impact of AI and the need to address the harder problems in the field rather than being distracted by distant future issues. Andrew Ng expresses concerns about the impact of AI and emphasizes the need to address the more pressing and challenging problems in the field, rather than being distracted by distant future issues.', 'Andrew Ng reflects on moments of pride and happiness, including helping others achieve their dreams and spending time with his daughter. Andrew Ng reflects on moments of pride and happiness, citing helping others achieve their dreams and spending time with his daughter as sources of fulfillment in his life.']}], 'duration': 1066.57, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/0jspaMLxBig/pics/0jspaMLxBig4274195.jpg', 'highlights': ['AI has the potential to drive global economic growth, with estimates of $13 trillion or $16 trillion impact, largely outside the software internet sector.', 'Key industries for AI implementation include manufacturing, agriculture, and healthcare, with examples of visual inspection in manufacturing using AI to improve yield and quality.', 'There is a need for more teams to work with companies outside the software internet sector to help them adopt AI and drive global economic growth.', "Starting small in AI projects is crucial, as demonstrated by Google's early successes with speech recognition and Google Maps, leading to a ripple effect within the company, and helping teams gain faith and learn about new technologies.", 'The chapter emphasizes the importance of redesigning tasks and managing change when automating processes with machine learning, as well as the need to work with partners to build the entire system, manage the change process, and deploy in a way that has an actual impact.', 'The current challenges in AI are highlighted, including bias, wealth inequality, and adverse uses like deepfakes. The chapter emphasizes the existing challenges in AI, such as bias, wealth inequality, and the adverse uses of AI, such as deepfakes, which are impacting society.', 'The chapter explores the future of AI, discussing the potential for human-level or superhuman-level intelligence, concerns about the long-term fate of humanity, and the need to align AI systems with human values. The discussion delves into the dream of achieving human-level or superhuman-level intelligence through AI, along with concerns about the long-term fate of humanity and the importance of aligning AI systems with human values.']}], 'highlights': ["Andrew Ng's significant contributions to AI and technology, including co-founding Coursera and Google Brain, and launching Deep Learning AI, Lending AI, and the AI Fund.", 'The global impact of MOOC movement, focusing on reaching a broad and global audience interested in machine learning and AI, with millions of people from around the world demonstrating substantial interest in the field.', 'The growing importance of AI developers: Prediction of over 50% of all future developers being AI developers.', 'The combination of novel architecture and scale playing a vital role in recent breakthroughs using transformer networks for language models, such as GP2 and BERT.', "The deep learning specialization by deeplearning.ai is Coursera's top specialization, providing practical know-how for building and debugging neural networks.", 'AI has the potential to drive global economic growth, with estimates of $13 trillion or $16 trillion impact, largely outside the software internet sector.', 'The current challenges in AI are highlighted, including bias, wealth inequality, and adverse uses like deepfakes.', 'The discussion delves into the dream of achieving human-level or superhuman-level intelligence through AI, along with concerns about the long-term fate of humanity and the importance of aligning AI systems with human values.']}