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Andrew Ng: Deep Learning, Education, and Real-World AI | Lex Fridman Podcast #73
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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
Segments Timeline
Meet Andrew Ng: AI Pioneer
In this introduction, Lex Fridman presents Andrew Ng, a leading figure in artificial intelligence and education. Ng's impressive background includes co-founding Coursera and Google Brain, and serving as Chief Scientist at Baidu. This segment sets the stage for a deep dive into Ng's contributions to AI and education, highlighting his impact on millions of learners worldwide.
"the following is a conversation with Andrew and one of the most impactful educators researchers innovators and leaders in artificial intelligence and technology space in general he co-founded Coursera..."
The Spark of Interest in AI
Andrew Ng shares his early experiences that ignited his passion for computer science and machine learning. From coding at a young age in Hong Kong to being inspired by his father's readings on expert systems, Ng reflects on pivotal moments that shaped his career. This segment illustrates the formative experiences that led him to become a leader in AI education.
"Andrew Eng the courses you taught on machine learning in Stanford and later on Coursera the co-founded have educated and inspired millions of people so let me ask you what people are ideas inspired yo..."
The Birth of MOOCs
Ng discusses the challenges and motivations behind launching the first MOOCs (Massive Open Online Courses) at Stanford and later on Coursera. He emphasizes the importance of automating education to reach more students and shares insights on the pressures of creating content for a large audience. This segment highlights Ng's innovative approach to education and his commitment to making learning accessible.
"favorite memories from your early days at Stanford teaching thousands of people in person and then millions of people online you know teaching online what not many people know was that a lot of those ..."
Lessons from Early Online Teaching
Reflecting on his early days of teaching online, Ng shares the realities of filming educational videos late at night under pressure. He emphasizes the importance of focusing on what benefits learners the most, which guided his approach to creating engaging content. This segment captures the dedication and thoughtfulness that Ng brings to online education.
"that had an interest in machine learning to break into fields and and I think sometimes eventually people ask me hey why you spend so much time explaining gradient descent and then and my answer was i..."
The Growing Interest in AI
Ng discusses the expanding interest in AI and machine learning, revealing that the audience for these fields is much larger than previously thought. He reflects on how teaching has helped uncover this vast community of learners, including developers from diverse backgrounds. This segment highlights the democratization of AI education and its global reach.
"many that allows us to hone in to the set of features and it sounds like a brilliant feature so I guess the lesson to take from that is you there's something that looks amazing on paper and then nobod..."
The Future of Programming and AI
In this segment, Ng envisions a future where programming and machine learning skills become as fundamental as literacy. He discusses the potential for a broader range of professionals, including those outside traditional tech roles, to engage with data science and machine learning. This forward-looking perspective emphasizes the importance of making these skills accessible to everyone.
"I send you an email you send me an email I think in computing we're still in that phase where so few people know how the codes that the code is mostly have to code for relatively large audiences but i..."
The Power of Whiteboard Teaching
Ng explains his preference for using a whiteboard in teaching, highlighting its effectiveness in breaking down complex concepts. He discusses the balance between using slides and a whiteboard, emphasizing the clarity that comes from writing equations step by step. This segment showcases Ng's educational philosophy and his commitment to making learning engaging and understandable.
"they use a whiteboard or a stylus the slowness of a whiteboard is also it's upside is it forces you to reduce everything to the basics some of some of your talks and involve the whiteboard I mean ther..."
Conviction in the Face of Uncertainty
Andrew Ng shares his motivation for pursuing applied research in reinforcement learning despite the uncertainties and challenges. He emphasizes the importance of having conviction in one's work and the desire to create a positive impact, which drives him to tackle difficult problems in the field.
"techniques so didn't actually mean to helicopter fly and you know I'm reminded when when was doing um this work at Stanford around that time there was a lot of reinforcement learning theoretical paper..."
The Importance of Scale in Deep Learning
Ng discusses the significance of scale in deep learning, recounting how early experiments demonstrated that larger datasets lead to better performance. He reflects on the initial skepticism he faced from peers and the groundbreaking nature of this insight, which has become a foundational principle in AI development.
"work yeah in the face of fear uncertainty is sort of the setbacks the you mentioned for localization I like stuff that works III know physical world so like it's this back to the shredder and you know..."
Lessons from the Early Days of Google Brain
In this segment, Andrew Ng shares lessons learned from the early days of Google Brain, including the misjudgment regarding unsupervised learning. He contrasts this with the realization of the importance of scale, which ultimately shaped the direction of their research and the development of deep learning technologies.
"as I do but when I delve into either theory or practice if I personally have conviction you know that here's a pathway to help people I find that more satisfying to have that conviction that that's yo..."
The Role of Data in AI Breakthroughs
Ng elaborates on the relationship between data scale and AI breakthroughs, particularly in the context of recent advancements in language models. He discusses how both innovative architectures and large datasets contribute to performance improvements, emphasizing the need for a balanced approach in AI research.
"out 10 to 5 bits per second of labels to her so and and I think I'm a very loving parent but I'm just not gonna do that so from this you know very crude definitely problematic argument there's just no..."
Navigating Data Management Challenges
Andrew Ng addresses the complexities of data management in AI, particularly in non-consumer internet settings. He shares experiences from working with manufacturing companies, highlighting the challenges of inconsistent labeling and the importance of developing robust data management processes.
"that gave me the conviction to go of Sebastian's to pitch you know starting starting a project at Google which became the CooCoo brain crunch brain you know filing Google brain and there the intuition..."
Encouraging Practical Projects in Education
Ng discusses his approach to teaching at Stanford, encouraging students to engage in practical projects rather than relying on pre-existing datasets. He believes that defining their own problems and datasets fosters deeper learning and prepares students for real-world challenges in AI.
"of learning you want to make better learning mechanisms and I personally believe that bigger data sets will still with the same learning methods we have now result in better performance what's your in..."
Building the Future of AI with Landing AI
In this segment, Andrew Ng outlines his current initiatives, including the AI Fund and Landing AI. He explains how these efforts aim to create new companies and help established organizations integrate AI, emphasizing the transformative potential of AI across various industries.
"you know but then we had was that CVS subversion get maybe something else in the future we're very immature in terms of Susa managing data and think about how the creator and how the soft I'm very hot..."
Getting Started in Deep Learning
Andrew Ng provides guidance on how individuals interested in deep learning can begin their journey. He discusses the popularity of his machine learning course on Coursera and its impact on aspiring data scientists. Ng emphasizes the importance of foundational knowledge and practical skills, encouraging learners to engage with the material actively.
"so let's perhaps talk about each of these areas first deep learning that AI how the basic question how does a person interested in deep learning get started in the field the Atlanta AI is working to c..."
Prerequisites for Deep Learning Specialization
In this segment, Ng outlines the prerequisites for taking the deep learning specialization, emphasizing that basic programming skills and high school-level math are sufficient. He reassures potential learners that calculus is not a requirement, making the course accessible to a broader audience. Ng highlights the importance of understanding fundamental concepts to succeed in deep learning.
"for that I'm sure I speak for a lot of people say big thank you no yeah thank you you know I was once reading a news article I think it was tech review and I'm gonna mess up the statistic but I rememb..."
Key Concepts in Deep Learning
Andrew Ng discusses essential concepts that students should grasp in their early months of studying deep learning. He emphasizes the importance of understanding neural networks, optimization algorithms, and practical know-how. Ng shares insights on how to avoid common pitfalls, such as overfitting, and the significance of efficient debugging in machine learning projects.
"is it confident to what is a RNA nor sequence model or what is an attention model and so the design specialization um steps everyone's through those algorithms so you deeply understand it and can impl..."
Debugging Machine Learning Models
In this segment, Ng compares debugging in machine learning to traditional software engineering. He explains the unique challenges of debugging machine learning algorithms and the importance of systematic thinking in troubleshooting. Ng shares strategies for efficiently identifying and resolving issues in machine learning projects, highlighting the need for a diverse skill set.
"tend to you know go over faster concepts like how does gradient descent work and what is an objective function which which is covered mostly in the machine learning course could you briefly mention so..."
Overcoming Challenges in Deep Learning Education
Andrew Ng reflects on the challenges students face when learning deep learning concepts. He discusses the cumulative nature of knowledge in the field and the importance of breaking down complex ideas into manageable components. Ng aims to build students' confidence and understanding as they progress through the deep learning specialization.
"build is net so dive right in to play with the network to train it to do the inference on a particular data set to build an intuition about it without without building it up too big to where you spend..."
The Role of Reinforcement Learning in Education
Ng shares his perspective on the educational value of reinforcement learning (RL) in teaching neural networks. He discusses how RL can inspire students and illustrate the capabilities of neural networks. Ng acknowledges the current limitations of RL in real-world applications but emphasizes its potential for engaging learners in the field of AI.
"think so we learned how the debug and I think in machine learning the way you debug the machine learning program is very different than the way you you know like do binary search or whatever use the d..."
Balancing Fun and Impact in AI Education
In this segment, Ng discusses the balance between engaging students with exciting topics like reinforcement learning and ensuring they acquire practical skills. He emphasizes the importance of teaching foundational concepts in supervised learning while also allowing room for exploration and creativity in AI education.
"months doing this what concepts and deep learning do you think students struggle the most with or sort of this is the biggest challenge for them was to get over that hill it's it hooks them and it ins..."
The Beauty of Unsupervised Learning
Andrew Ng expresses his fascination with unsupervised learning and its potential for future research. He shares examples of self-supervised learning techniques and their ability to generate labeled datasets from unlabeled data. Ng highlights the significance of these methods in advancing AI and their applications in various domains.
"of the earlier concepts I'm curious you you you do a lot of teaching as well do you have a do you have a favorite this is the hard concept moment in your teaching well I don't think anyone's ever turn..."
Innovative Techniques in Self-Supervised Learning
Ng delves into specific self-supervised learning techniques, such as rotating images and jigsaw puzzles, to create labeled datasets from unlabeled data. He discusses the implications of these methods for training neural networks and their effectiveness in transferring knowledge to different tasks. Ng emphasizes the ongoing research in this area and its potential impact on the future of AI.
"which is counterintuitive I find like a lot of the inspired sort of fire and people's passion people's eyes comes from the RL world do you find I mean first of all learning and to be a useful part of ..."
The Beauty of Unsupervised Learning
Andrew Ng shares his fascination with unsupervised learning, emphasizing its potential to generate infinite labeled data from unlabeled images. He discusses techniques like self-supervised learning, where neural networks predict original orientations of rotated images, and the jigsaw method, which involves predicting the arrangement of image segments. Ng believes these methods could unlock significant advancements in machine learning.
"the right tool for the job what is the most beautiful surprising or inspiring idea in deep learning to you something that captivated your imagination at the scale that could be a the performance I giv..."
The Future of Self-Supervised Learning
In this segment, Andrew Ng discusses the growing traction of self-supervised learning and its implications for real-world applications in computer vision and video. He reflects on the importance of returning to foundational ideas in representation learning and expresses excitement about the potential of unsupervised learning techniques to enhance machine learning systems.
"different toss very powerfully um learning word embeddings when we take a sentence to leave the word predict the missing word which is how we learn you know one of the ways we learn where the embeddin..."
Deep Learning Specialization Insights
Andrew Ng provides insights into the deep learning specialization course on Coursera, explaining its structure and flexibility. He emphasizes the importance of accessibility and affordability in education, encouraging those facing financial hardships to apply for financial aid to access the course for free.
"this concept and then I think there'll be other concepts around it you know other unsupervised learning things that I worked on I've been excited about I was really excited about sparse coding and I s..."
Building a Learning Habit
Ng discusses the significance of establishing a consistent learning habit for mastering deep learning. He shares his personal routine of dedicating time each weekend to study and encourages others to create similar habits, likening it to brushing teeth—an automatic part of daily life that leads to long-term improvement.
"individual who created the divine specialization we wanted to make it very accessible and very affordable and with you know Coursera and Devon dyers education mission one thing that's really important..."
The Power of Handwritten Notes
In this segment, Andrew Ng highlights the benefits of taking handwritten notes while studying. He explains how the slower process of writing by hand promotes better retention and understanding of material compared to typing, emphasizing the importance of summarizing information in one's own words for deeper learning.
"easier so yeah it's kind of amazing in my own life like I play guitar every day for life forced myself to at least for five minutes play guitar it's just it's a ridiculously short period of time but b..."
Efficient Learning in AI
Ng shares his philosophy on creating efficient learning experiences, stressing the importance of maximizing the value of each minute spent on education. He discusses the impact of his teaching methods and the ripple effect they have on learners, aiming to make every moment count in the learning process.
"less long-term retention I don't know what the psychological effect there is but so true there's something fundamentally different about in handwriting I wonder what that is I wonder if it is as simpl..."
Starting a Career in Deep Learning
Andrew Ng offers advice for those looking to build a career in deep learning. He emphasizes the importance of starting with coursework to master foundational concepts and encourages practical experience through projects. Ng advocates for taking small steps and gradually building skills to tackle larger challenges in the field.
"fascinating talk about how does one make a career out of an interest in deep learning give advice for people we just talked about sort of the beginning early steps but if you want to make it a entire ..."
Should You Pursue a PhD?
Ng discusses the value of pursuing a PhD in machine learning, noting that while it can be beneficial, many impactful roles in the field do not require one. He advises individuals to weigh their options carefully, considering both academic and industry paths based on their career aspirations.
"bigger projects I find this to be true at the individual level and also at the organizational level for company to become good at machine learning sometimes the right thing to do is not to tackle the ..."
Choosing the Right Environment
In this segment, Ng emphasizes the importance of the people you work with in shaping your career experience. He advises job seekers to consider the team dynamics and the quality of mentorship over the prestige of the organization, highlighting that great colleagues can significantly enhance learning and growth.
"Google Facebook buy do all these large companies already have huge teams of machine learning engineers you can also do with an industry sort of more research groups that kind of like Google research G..."
Choosing the Right Team
In this segment, Andrew Ng discusses the critical nature of team dynamics in both academic and corporate settings. He warns against accepting positions where the team structure is unclear, suggesting that a lack of transparency may indicate a poor working environment. Ng stresses the importance of connecting with colleagues and recognizing red flags during the job search process.
"profound advice that we kind of sometimes sweep we don't consider to rigorously or carefully the people around you are really often this especially when you accomplish great things it seems the great ..."
Building Startups with the AI Fund
Andrew Ng introduces the AI Fund, a startup studio designed to help new AI ventures succeed. He shares insights on the challenges of startup failures, emphasizing the need for a customer-focused approach. Ng believes that understanding customer needs and creating socially beneficial products are key to building successful startups in the AI space.
"and that's yeah I am in my standard cause cs2 30s was an ACN talk I think I gave like a hour long talk on career advice including on the job search process and then some of these those are yours if yo..."
The Startup Studio Concept
In this segment, Ng elaborates on the startup studio model, explaining how it systematically creates new companies. He discusses the importance of building teams and leveraging AI capabilities to explore new business opportunities. Ng reflects on his experiences at Baidu and how they inspired him to create the AI Fund as a mechanism for fostering innovation.
"for words I'm sorry I personally don't want to build addictive digital products just so long as you know the things that that could be lucrative but I won't do but if we can find ways to serve people ..."
Automating Startup Success
Andrew Ng discusses the ongoing efforts to automate the startup creation process within the AI Fund. He highlights the importance of iterating on processes and learning from customer interactions to improve success rates. Ng emphasizes that while the startup journey is challenging, systematic approaches can enhance the likelihood of building successful AI companies.
"start-up studio is a relatively new concept there there are maybe dozens of startup studios you're right now but I feel like all of us many teams are still trying to figure out how do you systematical..."
Support Structures for Entrepreneurs
Ng explains how startup studios provide essential support for entrepreneurs, making the journey less isolating. He discusses the importance of having a network to help navigate key decisions and challenges. Ng believes that fostering collaboration and sharing knowledge can significantly improve the chances of startup success.
"building successful AI startup yeah I think we've we've been constantly improving and iterating on our processes but how we do that so things like you know how many customer calls do we need to make a..."
Ethics in AI Entrepreneurship
In this segment, Ng reflects on the ethical considerations of building AI companies. He shares his personal stance against creating addictive products that do not contribute positively to society. Ng emphasizes the responsibility of entrepreneurs to ensure their innovations serve meaningful purposes and contribute to the greater good.
"also um when facing with these key decisions like trying to hire your first the VP of Engineering what's a good selection criteria do you sauce should I hire this person or not but helping by having b..."
AI's Transformative Potential
Andrew Ng discusses the transformative potential of AI across various industries beyond software and tech. He highlights sectors like manufacturing, agriculture, and healthcare as ripe for AI integration. Ng references studies estimating significant economic growth driven by AI adoption, underscoring the need for more teams to assist companies in leveraging AI technologies.
"people so what the building companies or work of enterprises or doing personal projects I think it's up to each of us to figure out what's the difference we want to make in the world with learning AI ..."
Practical AI Implementation Challenges
Ng addresses the practical challenges companies face when implementing AI solutions. He explains the gap between theoretical models and real-world applications, emphasizing the importance of robust software engineering. Ng shares insights on common pitfalls and stresses the need for companies to understand the complexities of deploying machine learning systems effectively.
"more powerful and like you said the impact is there so what are the best industries the biggest industries where AI can perhaps outside the software tech sector um frankly I think is all of them some ..."
Starting Small with AI Projects
In this segment, Ng advises companies to start small when integrating AI technologies. He shares examples from his experience at Google, illustrating how initial small-scale projects can build confidence and demonstrate value. Ng emphasizes that these early successes can lead to broader adoption of AI across organizations.
"such a fascinating space you're absolutely right but what is the first step that a company should take it's just scary leap into this new world of going from the human eye inspecting to digitizing tha..."
Bridging the Gap in AI Development
Andrew Ng discusses the critical gap between developing AI models and deploying them in real-world settings. He highlights the challenges of ensuring that machine learning algorithms perform well outside of controlled environments. Ng stresses the importance of addressing these issues to ensure successful AI implementations in various industries.
"for us I think the early small-scale projects it helps the teams gain faith but also hosts the team's learn what these technologies do I still remember when our first GPU server it was a server under ..."
Challenges of AI Maintenance and Deployment
Ng addresses the complexities of maintaining machine learning systems in industrial settings, contrasting them with the resources available in tech companies. He emphasizes the need for systematic approaches to DevOps and maintenance, which are often overlooked in traditional AI deployment discussions.
"people when he so happens I think what Lani AI has become good at and I think we learned by making mistakes and you know painful experiences for my ring what would become good at is working with our p..."
The Future of AGI and Ethical Considerations
Andrew Ng shares his thoughts on the pursuit of artificial general intelligence (AGI) and the ethical implications it carries. He expresses concerns about the long-term impact of AGI on humanity and the importance of aligning AI systems with human values to prevent potential existential threats.
"not inconsistent no they're all together I'm only half joking because you're probably interested a little bit in both but let me ask a romanticized question so much of the work your work and our discu..."
Addressing Immediate AI Challenges
In this segment, Ng discusses pressing issues in AI today, such as bias, wealth inequality, and the need for responsible AI development. He argues that focusing on these immediate challenges is crucial for ensuring that AI benefits society as a whole, rather than exacerbating existing problems.
"short term or the long term I do worry about the long term fate of humanity um I do wonder as well I do worry about overpopulation on the planet Mars just not today I think there will be a day when ma..."
The Importance of Practical AI Solutions
Ng emphasizes the significance of solving practical problems in AI, such as ensuring reliable performance in real-world scenarios. He critiques the tendency to focus on theoretical concerns while neglecting the tangible challenges that affect industries and communities today.
"and you teach this so you know how many times when you're driving your car did you face this moral dilemma as it would I food I crash into you so I think itself Giancarlo runs that problem roughly as ..."
Reflections on Life and Helping Others
Andrew Ng reflects on his journey through teaching, research, and entrepreneurship. He shares personal insights about his regrets and proud moments, emphasizing the fulfillment he finds in helping others achieve their dreams and the broader impact of his work on society.
"teams maybe accidentally and I hope not deliberately making a lot of noise about things that problems in the distant future rather than focusing on senses much harder problems yeah the overshadow the ..."
Words of Wisdom from Andrew Ng
In closing, Ng offers a powerful message about the importance of ensuring that one's work contributes positively to others. He encourages listeners to seek out endeavors that not only fulfill personal ambitions but also significantly help others, underscoring the essence of living up to one's potential.
"potential thank you for listening and hope to see you next time you"