Acerca de

Season 1 Episode 20

Fei-Fei Li

              On Ep.20 of The Robot Brains Podcast, Pieter Abbeel is joined by Fei-Fei Li. Her legendary status in the field of AI precedes her on our podcast because she's been discussed frequently by many of our previous guests - many of whom are her former students.

She is the Sequoia Capital Professor of Computer Science at Stanford University, Co-Director of the Stanford Institute for Human-Centered Artificial Intelligence (Stanford HAI). She was also the leading scientist and instigator of ImageNet, arguably the most momentous episode in the history of AI which allowed vision systems and neural nets to break out of academia and into real industries all over the world.

On the show we talk to Fei-Fei about her illustrious career in academia, her involvement in the ImageNet and AlexNet breakthroughs, and her new, deeply personal reasons for focusing her latest work on transforming healthcare with AI. | SUBSCRIBE TO THE ROBOT BRAINS PODCAST TODAY |

Host: Pieter Abbeel | Executive Producers: Ricardo Reyes & Henry Tobias Jones | Audio Production: Kieron Matthew Banerji | Title Music: Alejandro Del Pozo

spotify-podcast-badge-blk-grn-330x80.png
badge.png

Subscribe to
The Robot Brains Podcast

listen+on+google+podcast.png
overcast-logo.png
pocketcasts_large_dark@2x.png
stitcher-logo-e1528167200985.png
Castbox.png
logo-deezer-png-5-Transparent-Images-Free.png
acast (1).png
podcast-addict-badge.png
413-4138881_podcast-tunein-keep-calm-and-listen.png
listenOnAmazonMusicBlack.0688fc5c.png

Links

pngkit_www-icon-png_2423644.png
twitter-logo-2429_edited.png
Season 2 Ep. 6 Cathy Wu of MIT on the future of our roads
37:27

Season 2 Ep. 6 Cathy Wu of MIT on the future of our roads

Previous guests on our podcasts - from Tesla, Aurora, to Waymo - are building the brains of the cars and trucks of our future. This episode's guest, Professor Cathy Wu, is helping build the roadways of our future with machine-learning to predict the ideal infrastructure for the world's future mobility, the cost of building this infrastructure, and the age-old question, "How do we eliminate traffic jams?" Currently at MIT's Institute for Data, Systems, and Society (IDSS), Professor Cathy Wu (and previous student of Pieter Abbeel's) gives listeners an overview of the type of potential scenarios being modeled with machine-learning such as scenarios in which the road is filled with mixed-autonomy vehicles. What emergent behaviors might happen? As our mode for transportation and delivery evolve, what are the infrastructure or software solutions that can help ensure smooth travel and safe roadways? What are the policy considerations? Throughout the talk, Wu cites building reinforcement learning for her work and why it's the right fit her research, "Reinforcement learning is essentially this paradigm at the intersection of machine learning and also control, and it is essentially about how agents learn from experience and in particular through trial and error." What's in this episode: 00:00:00 - Introduction 00:02:09 - Her undergrad path to where she is now 00:06:30 - Why studying next-generation transportation models is important 00:10:03 - What does autonomy mean for traffic jams? 00:18:30 - Her motivation for her work 00:23:00 - Why use reinforcement learning? 00:29:27 - The future of our world's highways 00:34:21 - Advice for students Links: MIT's IDSS: https://idss.mit.edu/ Website: http://wucathy.com/ Recent interview: https://news.mit.edu/2021/qa-cathy-wu-developing-algorithms-safely-integrate-robots-our-world-1216 TEDxMIT talk: https://www.youtube.com/watch?v=mrk8I-9iLs4 SUBSCRIBE TODAY: Apple: https://apple.co/3vRqBlV Spotify: https://spoti.fi/3d0PEwf Amazon: https://amzn.to/2SWdZfP Google: https://bit.ly/3d52Uju Acast: https://bit.ly/3A0uqIO Host: Pieter Abbeel Executive Producers: Alice Patel & Henry Tobias Jones Production: Fresh Air Production
Season 2 Ep. 5 Is machine learning the future of blood diagnostics?
55:02

Season 2 Ep. 5 Is machine learning the future of blood diagnostics?

Analyzing a person’s blood (and the cells within it) is often used to diagnose many health conditions and illnesses, from infections to leukemia and bone marrow disorders. Generally it's a long and expensive process. You have to go to the doctor, have a sample taken, wait for a couple of days for a trained professional to analyze the blood, and finally get your diagnosis. Athelas is using machine learning to dramatically improve the speed and efficiency of testing blood cells. From a simple finger prick’s worth of blood, Athelas devices can monitor and help healthcare professionals to remotely care for patients. To date over 40,000 people have used Athelas devices to monitor a range of conditions including hypertension and diabetes. With a recent valuation of $1.5B, the company is poised for major impact. What's in this episode: 00:00:00 - Introduction 00:7:03 - Athelas' founding story 00:18:30 - Genetic differences among populations 00:21:14 - How does Athelas differ from Theranos? 00:27:07 - Real life use cases in action including Leukemia and Schizophrenia 00:32:25 - Patient stories related to detection and chronic care 00:34:10 - The story of Tanay founding his first company at 15 years old 00:37:59 - How the Athelas cofounders met, from science fair competitor to co-founder 00:39:16 - Tanay’s decision to quit Stanford to start his company 00:41:20 - YCombinator at 19 years old 00:44:00 - Advice for other founders 00:50:58 - Where is Athelas headed next? Links: Athelas website: https://www.athelas.com/ Bloomberg coverage of Athelas funding: https://www.bloomberg.com/news/videos/2022-02-01/health-startup-athelas-hits-1-5b-valuation-video Subscribe and listen to our podcast today: Apple: https://apple.co/3vRqBlV Spotify: https://spoti.fi/3d0PEwf Amazon: https://amzn.to/2SWdZfP Google: https://bit.ly/3d52Uju Acast: https://bit.ly/3A0uqIO Host: Pieter Abbeel Executive Producers: Alice Patel & Henry Tobias Jones Audio Production: Kieron Matthew Banerji. Video Production: Bo Obradovic.
Season 2 Ep. 4 What matters in tech according to Benedict Evans
56:28

Season 2 Ep. 4 What matters in tech according to Benedict Evans

*Warning* Explicit language used in the episode. Benedict Evans, long-time technology analyst and occasional VC at firms such as Andreessen Horowitz, is well known for his analysis of mobile, media and technology trends. He writes a popular weekly newsletter on the most important happenings in tech and he is also famous for his annual presentations that analyze macro and strategic trends in the tech industry. He’s a voice of reason trying to sort out the technology issues of the day. In this episode of The Robot Brains, he sits down with Pieter to discuss his opinion on the label of "AI", areas of business that ML is adding real value, and his predictions for the future. What's in this episode: 00:00:00 - Introduction 00:09:38 - The great unbundling 00:12:57 - How does AI play a role in this movement? 00:16:40 - The stage of AI becoming a product or a company 00:17:40 - Benedict’s time at Andreessen Horowitz 00:21:22 - Can scaling up current technologies lead to AGI? 00:31:25 - The vertical view of AI, logistics and e-commerce 00:36:40 - How important is efficiency for logistics? 00:40:04 - China's role as an AI powerhouse 00:46:46 - Government regulation of tech 00:51:50 - Benedict's view on AVs and transportation tech Links: Benedict's Twitter: https://twitter.com/benedictevans Benedict's newsletter: https://www.ben-evans.com/newsletter Benedict's annual reports: https://www.ben-evans.com/presentations Subscribe and listen to our podcast today: Apple: https://apple.co/3vRqBlV Spotify: https://spoti.fi/3d0PEwf Amazon: https://amzn.to/2SWdZfP Google: https://bit.ly/3d52Uju Acast: https://bit.ly/3A0uqIO Host: Pieter Abbeel Executive Producers: Alice Patel & Henry Tobias Jones Audio Production: Kieron Matthew Banerji. Video Production: Bo Obradovic.