20VC: Andrew NG on The Biggest Bottlenecks in AI | How LLMs Can Be Used as a Geopolitical Weapon | Do Margins Matter in a World of AI? | Is Defensibility Dead in a World of AI? | Will AI Deliver Masa Son's Predictions of 5% GDP Growth?
Dr. Andrew Ng is a globally recognized leader in AI. He is Founder of DeepLearning.AI, Executive Chairman of LandingAI, General Partner at AI Fund, Chairman and Co-Founder of Coursera. As a pioneer in machine learning Andrew has authored or co-authored over 200 research papers in machine learning, robotics and related fields. In 2023, he was named to the Time100 AI list of the most influential AI persons in the world.
Agenda:
03:19 What are the Biggest Bottlenecks in AI Today?
08:51 How LLMs Can Be Used as a Geopolitical Weapon
15:48 Should AI Talent Really Be Paid Billions?
29:07 Why is the Application Layer the Most Exciting Layer?
36:22 Do Margins Matter in a World of AI?
38:02 Is Defensibility Dead in a World of AI?
45:29 Will AI Deliver Masa Son's Predictions of 5% GDP Growth?
49:39 Are We in an AI Bubble?
57:31 Will Human Labour Budgets Shift to AI Spend?
How Agentic AI is Transforming The Startup Landscape with Andrew Ng
Andrew Ng has always been at the bleeding edge of fast-evolving AI technologies, founding companies and projects like Google Brain, AI Fund, and DeepLearning.AI. So he knows better than anyone that founders who operate the same way in 2025 as they did in 2022 are doing it wrong. Sarah Guo and Elad Gil sit down with Andrew Ng, the godfather of the AI revolution, to discuss the rise of agentic AI, and how the technology has changed everything from what makes a successful founder to the value of small teams. They talk about where future capability growth may come from, the potential for models to bootstrap themselves, and why Andrew doesn’t like the term “vibe coding.” Also, Andrew makes the case for why everybody in an organization—not just the engineers—should learn to code.
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Chapters:
00:00 – Andrew Ng Introduction
00:32 – The Next Frontier for Capability Growth
01:29 – Andrew’s Definition of Agentic AI
02:44 – Obstacles to Building True Agents
06:09 – The Bleeding Edge of Agentic AI
08:12 – Will Models Bootstrap Themselves?
09:05 – Vibe Coding vs. AI Assisted Coding
09:56 – Is Vibe Coding Changing the Nature of Startups?
11:35 – Speeding Up Project Management
12:55 – The Evolution of the Successful Founder Profile
19:23 – Finding Great Product People
21:14 – Building for One User Profile vs. Many
22:47 – Requisites for Leaders and Teams in the AI Age
28:21 – The Value of Keeping Teams Small
32:13 – The Next Industry Transformations
34:04 – Future of Automation in Investing Firms and Incubators
37:39 – Technical People as First Time Founders
41:08– Broad Impact of AI Over the Next 5 Years
41:49 – Conclusion
841: Andrew Ng on AI Vision, Agents and Business Value
In this special episode recorded live at ScaleUp:AI in New York, Jon Krohn speaks to Andrew Ng in response to his conference talk on smart agentic AI workflows. Jon follows up with Andrew about smart agentic workflows and when to use them, how businesses should direct their efforts in investing in AI, and the new ways that AI tools can process visual and unstructured data.
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn:
(06:13) How to weigh up cost and effectiveness in new AI workflows
(12:08) The crucial elements for building effective vision AI applications
(15:34) How large vision models might transform global industries
(18:40) How to mitigate risk in people not verifying accuracy in answers generated by agents
Additional materials: www.superdatascience.com/841
The Implications of AI on the Global Balance of Power with Alex Wang, Andrew Ng, Jack Clark and Cory Booker
Tune in to today's special episode airing a recent panel with the founders of Scale AI, Anthropic, and AI Fund who gathered in Washington DC to discuss China as an adversary. They argue that the papers out of Tsinghua University are just as impressive as those coming out of American universities. China is just as creative, but maybe even more motivated. While discussions of regulations have encompassed certain restraints, Alex Wang, Andrew Ng, and Jack Clark argue that we’re not moving fast enough (moderated by US senator Cory Booker).
This session was recorded live at The Hill & Valley Forum in 2024, a private bipartisan community of lawmakers and innovators committed to harnessing the power of technology to address America's most pressing national security challenges. The Hill & Valley podcast is part of the Turpentine podcast network. Learn more: www.turpentine.co
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CHAPTERS:
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(04:45) Predictions for AGI
(08:21) Navigating AI innovation amidst regulation
(16:15) Global AI competition and the urgency of Innovation
(24:34) Empowering future generations
When AI and Genomics Collide
Today’s episode continues our coverage from a16z’s recent AI Revolution event. You’ll hear a16z Bio & Health GP Vijay Pande speak with Daphne Koller about the fascinating convergence of machine learning and genomics – two industries that have benefitted decades of investment and progress – which are now colliding head on.
Daphne is a prominent innovator at this intersection, as a long-time professor in computer science at Stanford and co-founder of Coursera, who has decided to step back into the arena with her company Insitro. In fact, Insitro is a blend of in silico and in virto!
If you’d like to access all the talks from AI Revolution in full, visit a16z.com/airevolution.
Resources:
Find Daphne on Twitter: https://twitter.com/DaphneKoller
Find Vijay on Twitter: https://twitter.com/vijaypande
Find Insitro on Twitter: https://twitter.com/insitro
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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#131 Andrew Ng: Exploring Artificial Intelligence's Potential & Threats
Welcome to episode #131 of the Eye on AI podcast with Andrew Ng. Get ready to challenge your perspectives as we sit down with Andrew Ng. We navigate the widely disputed topic of AI as a potential existential threat, with Andrew assuring us that, with time and global cooperation, safety measures can be built to prevent disaster. He offers insight into the debates surrounding the harm AI might cause, including the notions of AI as a bio-weapon and the notorious 'paper clip argument'. Listen as Andrew debunks these theories, delivering an interesting argument for why he believes the associated risks are minimal.Onwards, we venture into the intriguing realm of AI's capability to understand the world, setting the stage for a conversation on how we can objectively assess their comprehension. We explore the safety measures of AI, drawing parallels with the rigour of the aviation industry, and contemplate on the consensus within the research community regarding the danger posed by AI. (00:00) Preview (01:08) Introduction (02:15) Existential risk of artificial intelligence (05:50) Aviation analogy with artificial intelligence (10:00) The threat of AI & deep learning (13:15) Lack of consensus in AI dangers (18:00) How AI can solve climate change (24:00) Landing AI and Andrew Ng (27:30) Visual prompting for images Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
Our sponsor for this episode is Masterworks, an art investing platform. They buy the art outright, from contemporary masters like Picasso and Banksy, then qualify it with the SEC, and offer it as an investment. Net proceeds from its sale are distributed to its investors. Since their inception, they have sold over $45 million dollars worth of artwork And so far, each of Masterworks' exits have returned positive net returns to their investors.
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Purchase shares in great masterpieces from artists like Pablo Picasso, Banksy, Andy Warhol, and more. See important Masterworks disclosures: https://www.masterworks.com/cd "Net Return" refers to the annualized internal rate of return net of all fees and costs, calculated from the offering closing date to the date the sale is consummated. IRR may not be indicative of Masterworks paintings not yet sold and past performance is not indicative of future results. Returns shown are 4 examples of midrange returns selected to demonstrate Masterworks performance history. Returns may be higher or lower. Investing involves risk, including loss of principal.
How AI can make drug discovery fail less, with Daphne Koller from Insitro
Life-saving therapeutics continue to grow more costly to discover. At the same time, recent advances in using machine learning for the life sciences and medicine are extraordinary. Are we on the verge of a paradigm shift in biotech?
This week on the podcast, a pioneer in AI, Daphne Koller, joins Sarah Guo and Elad Gil on the podcast to help us explore that question. Daphne is the CEO and founder of Insitro — a company that applies machine learning to pharma discovery and development, specifically by leveraging “induced pluripotent stem cells.” We explain Insitro’s approach, why they’re focused on generating their own data, why you can’t cure schizophrenia in mice, and how to design a culture that supports both research and engineering. Daphne was previously a computer science professor at Stanford, and co-founder and co-CEO of edutech company Coursera.
Show Links:
Insitro - About
Video: AWS re:Invent 2019 – Daphne Koller of insitro Talks About Using AWS to Transform Drug Development
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Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @DaphneKoller
Show Notes:
[1:49] - How Daphne combined her biology and tech interests and ran a bifurcated lab at Stanford
[4:34] - Why Daphne resigned an endowed chair at Stanford to build Coursera
[14:14] - How insitro approaches target identification problems and training data
[18:33] - What are pluripotent stem cells and how insitro identifies individual neurons
[24:08 ] - How insitro operates as an engine for drug discovery and partners to create the drugs themselves
[26:48] - Role of regulations, clinical trials and disease progression in drug delivery
[33:19] - Building a team and workplace culture that can bridge both bio and computer sciences
[39:50] - What Daphne is paying attention to in the so-called golden age of machine learning
[43:12] - Advice for leading a startup in edtech and healthtech
How AI could empower any business | Andrew Ng
Expensive to build and often needing highly skilled engineers to maintain, artificial intelligence systems generally only pay off for large tech companies with vast amounts of data. But what if your local pizza shop could use AI to predict which flavor would sell best each day of the week? Andrew Ng shares a vision for democratizing access to AI, empowering any business to make decisions that will increase their profit and productivity. Learn how we could build a richer society – all with just a few self-provided data points.
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Andrew Ng
Andrew Ng, founder of Google Brain, Coursera and Landing AI, talks about his vision of data-centric AI, MLOps and the future of supervised vs unsupervised learning. The Eye on AI podcast is sponsored by ClearML.
Daphne Koller — Digital Biology and the Next Epoch of Science
From teaching at Stanford to co-founding Coursera, insitro, and Engageli, Daphne Koller reflects on the importance of education, giving back, and cross-functional research.
Daphne Koller is the founder and CEO of insitro, a company using machine learning to rethink drug discovery and development. She is a MacArthur Fellowship recipient, member of the National Academy of Engineering, member of the American Academy of Arts and Science, and has been a Professor in the Department of Computer Science at Stanford University. In 2012, Daphne co-founded Coursera, one of the world's largest online education platforms. She is also a co-founder of Engageli, a digital platform designed to optimize student success.
https://www.insitro.com/
https://www.insitro.com/jobs
https://www.engageli.com/
https://www.coursera.org/
Follow Daphne on Twitter: https://twitter.com/DaphneKoller
https://www.linkedin.com/in/daphne-koller-4053a820/
Topics covered:
0:00 Giving back and intro
2:10 insitro's mission statement and Eroom's Law
3:21 The drug discovery process and how ML helps
10:05 Protein folding
15:48 From 2004 to now, what's changed?
22:09 On the availability of biology and vision datasets
26:17 Cross-functional collaboration at insitro
28:18 On teaching and founding Coursera
31:56 The origins of Engageli
36:38 Probabilistic graphic models
39:33 Most underrated topic in ML
43:43 Biggest day-to-day challenges
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E1089 The Next Unicorns E11: insitro CEO Daphne Koller is revolutionizing drug discovery via machine learning & data, shares insights on remote education from time at Coursera & more
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Check out insitro: https://insitro.com/
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#93 – Daphne Koller: Biomedicine and Machine Learning
Daphne Koller is a professor of computer science at Stanford University, a co-founder of Coursera with Andrew Ng and Founder and CEO of insitro, a company at the intersection of machine learning and biomedicine.
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EPISODE LINKS:
Daphne’s Twitter: https://twitter.com/daphnekoller
Daphne’s Website: https://ai.stanford.edu/users/koller/index.html
Insitro: http://insitro.com
This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon.
Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.
OUTLINE:
00:00 – Introduction
02:22 – Will we one day cure all disease?
06:31 – Longevity
10:16 – Role of machine learning in treating diseases
13:05 – A personal journey to medicine
16:25 – Insitro and disease-in-a-dish models
33:25 – What diseases can be helped with disease-in-a-dish approaches?
36:43 – Coursera and education
49:04 – Advice to people interested in AI
50:52 – Beautiful idea in deep learning
55:10 – Uncertainty in AI
58:29 – AGI and AI safety
1:06:52 – Are most people good?
1:09:04 – Meaning of life
#73 – Andrew Ng: Deep Learning, Education, and Real-World AI
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.
EPISODE LINKS:
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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/
This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon.
This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”.
This episode is also supported by the Techmeme Ride Home podcast. Get it on Apple Podcasts, on its website, or find it by searching “Ride Home” in your podcast app.
Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time.
OUTLINE:
00:00 – Introduction
02:23 – First few steps in AI
05:05 – 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
Machine Learning: A New Approach to Drug Discovery with Daphne Koller - #332
Today we’re joined by Daphne Koller, co-Founder and former co-CEO of Coursera and Founder and CEO of Insitro. In our conversation, discuss the current landscape of pharmaceutical drugs and drug discovery, including the current pricing of drugs, and an overview of Insitro’s goal of using ML as a “compass” in drug discovery. We also explore how Insitro functions as a company, their focus on the biology of drug discovery and the landscape of ML techniques being used, Daphne’s thoughts on AutoML, and
Episode 29 - Daphne Koller
Daphne Koller, formerly at Stanford University and cofounder of the online education company, Coursera, talks this week about using machine-learning to develop new drugs. Her approach is to use machine learning to accuratley identify cellular or genetic targets for treatment. The field is just getting started but promises to speed the development of new and better therapies to treat disease.
Live from TWIMLcon! Overcoming the Barriers to Deep Learning in Production with Andrew Ng - #304
Earlier today, Andrew Ng joined us onstage at TWIMLcon - as the Founder and CEO of Landing AI and founding lead of Google Brain, Andrew is no stranger to knowing what it takes for AI and machine learning to be successful. Hear about the work that Landing AI is doing to help organizations adopt modern AI, his experience in overcoming challenges for large companies, how enterprises can get the most value for their ML investment as well as addressing the ‘essential complexity’ of software engineering.
a16z Podcast: Breaking Into Bio
with Atul Butte (@atulbutte), Daphne Koller (@daphnekoller), and Vijay Pande (@vijaypande)
Whether you’re an academic seeking to move out of research and into industry, or simply interested in working at a bio startup, this episode of the a16z Podcast is for you. It covers everything from how to build a brand in the space when you don’t have one to how the bio and how the healthcare startup ecosystem is different from traditional tech (or traditional pharma), to how to choose the right co-founder -- or even identify what problems to solve and build a company around.
The discussion (which is based on a recent event at Andreessen Horowitz) features Atul Butte, Distinguished Professor and Director of the Institute for Computational Health Sciences at UCSF; and Daphne Koller, founder and CEO of insitro (former professor at Stanford, co-founder of Coursera); in conversation with a16z bio team general partner Vijay Pande. Together, they provide practical how-to's -- for those coming from machine and deep learning backgrounds, but also for anyone, really -- for how to break into the bio space.
The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.
This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments and certain publicly traded cryptocurrencies/ digital assets for which the issuer has not provided permission for a16z to disclose publicly) is available at https://a16z.com/investments/.
Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.
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Ep. 32: Deep Learning Pioneer Andrew Ng on AI as the New Electricity
Purple shirts, haircuts, and cats. How are these three all related? According to deep learning pioneer Andrew Ng, they all played a part in AI’s growing presence in our lives. Ng, formerly of Google and Baidu, and the founder of his new company, Deeplearning.ai, joined this week’s episode of the AI Podcast to share his thoughts on AI being the new electricity.
Recode Decode: Daphne Koller, president, Coursera
Coursera president and co-founder Daphne Koller talks with Recode's Kara Swisher about how she helped build the popular online learning platform after a successful early experiment at Stanford University. Koller says the future of higher education is a mixture of online and offline learning, with people continually going back to school in some form throughout their lives, rather than stopping in their 20s. She discusses whether universities themselves are at risk of going extinct and whether technologies like artificial intelligence and virtual reality could replace a college professor.
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