Building the factories of the future with Covariant CEO Peter Chen
Building adaptive AI models that can learn and complete tasks in the physical world requires precision but these AI robots could completely change manufacturing and logistics processes. Peter Chen, the co-founder and CEO of Covariant, leads the team that is building robots that will increase manufacturing efficiency, safety, and create warehouses of the future.
Today on No Priors, Peter joins Sarah to talk about how the Covariant team is developing multimodal models that have precise grounding and understanding so they can adapt to solve problems in the physical world. They also discuss how they plan their roadmap at Covariant, what could be next for the company, and what use case will bring us to the Chat-GPT moment for AI robots.
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Show Notes:
(0:00) Peter Chen Background
(0:58) How robotics AI will drive AI forward
(3:00) Moving from research to a commercial company
(5:46) The argument for building incrementally
(8:13) Manufacturing robotics today
(12:21) Put wall use case
(15:45) What’s next for Covariant Brain
(18:42) Covariant’s customers
(19:50) Grounding concepts in Ai
(25:47) How scaling laws apply to Covariant
(29:21) Covariant’s driving thesis
(32:54) the Chat-GPT moment for robotics
(35:12) Manufacturing center of the future
(37:02) Safety in AI robotics
#159 Peter Chen: Building the AI-Driven Future of Robotics
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In episode #159 of Eye on AI, Craig Smith sits down with Peter Chen, the co-founder and CEO of Covariant, in a deep dive into the world of AI-driven robotics.
Peter shares his journey from his early days in China to his pivotal role in shaping the future of AI at Covariant. He discusses the philosophies that guided his work at OpenAI and how these have influenced Covariant's mission in robotics.
This episode unveils how Covariant is harnessing AI to build foundational models for robotics, discussing the intersection of reinforcement learning, generative models, and the broader implications for the field. Peter elaborates on the challenges and breakthroughs in developing AI agents that can operate in dynamic, real-world environments, providing insights into the future of robotics and AI integration.
Join us for this insightful conversation, where Peter Chen maps out the evolving landscape of AI in robotics, shedding light on how Covariant is pushing the boundaries of what's possible.
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(00:00) Preview and Introduction
(03:10) Peter Chen Journey in AI
(09:53) The Evolution of Generative AI and Transformer Models
(12:21) The Concept of World Models in AI
(14:03) Building Robust Role Models in AI
(20:48) Training AI: From Video Analysis to Real-World Interaction
(23:10) The Three Pillars of Building a Robotic Foundation Model
(27:36) Architectural Insights of Covariant's Foundation Model
(33:20) Adapting AI Models to Diverse Hardware
(35:01) The Future of Robotics: Progress and Potential
(38:55) Real-World Application and Future of AI-Controlled Robots
(42:11) Envisioning the Future of Automated Warehouses
(45:51) The Evolution of Robotics: Current Trends and Future Prospects
Next Unicorns: Empowering robots to think for themselves via AI with Covariant’s Peter Chen | E1796
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Today’s show:
Covariant CEO Peter Chen joins Jason to discuss the future of AI in robotics (1:33), the key concepts of reinforcement learning (13:50), and much more!
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Time stamps:
(0:00) Covariant CEO Peter Chen joins Jason
(1:33) AI’s role in robotics and its value in e-commerce warehouses
(7:38) Lemon.io - Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist
(8:59) Reinforcement learning today and the AlphaGo moment
(13:50) The 2 key concepts of reinforcement learning
(17:35) Approaches to accessing data for AI in robotics
(20:35) Robotics hardware
(22:50) Vanta - Get $1000 off your SOC 2 at https://vanta.com/twist
(23:57) Covariant's hardware and software in use
(27:32) The importance of adaptability
(32:40) LinkedIn Marketing - Get a $100 LinkedIn ad credit at https://linkedin.com/nextunicorn
(34:08) The Tesla Optimus and humanoid robots
(39:58) Overcoming hardware constraints
(44:38) Boomerang investors and customers
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Follow Peter: https://twitter.com/peterxichen
Check out Covariant : https://covariant.ai/
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Rocky Duan: from OpenAI to Covariant and building foundation models for robotic automation
Rocky Duan, CTO of Covariant joins joins Host Pieter Abbeel to talk about his time at OpenAI to founding Covariant to build foundation models for robotic automation.
Subscribe to the Robot Brains Podcast today | Visit therobotbrains.ai and follow us on YouTube at TheRobotBrainsPodcast and Twitter @therobotbrains.
Hosted on Acast. See acast.com/privacy for more information.
Pieter Abbeel — Robotics, Startups, and Robotics Startups
Pieter is the Chief Scientist and Co-founder at Covariant, where his team is building universal AI for robotic manipulation. Pieter also hosts The Robot Brains Podcast, in which he explores how far humanity has come in its mission to create conscious computers, mindful machines, and rational robots.
Lukas and Pieter explore the state of affairs of robotics in 2021, the challenges of achieving consistency and reliability, and what it'll take to make robotics more ubiquitous. Pieter also shares some perspective on entrepreneurship, from how he knew it was time to commercialize Gradescope to what he looks for in co-founders to why he started Covariant.
Show notes: http://wandb.me/gd-pieter-abbeel
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Connect with Pieter:
📍 Twitter: https://twitter.com/pabbeel
📍 Website: https://people.eecs.berkeley.edu/~pabbeel/
📍 The Robot Brains Podcast: https://www.therobotbrains.ai/
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Timestamps:
0:00 Intro
1:15 The challenges of robotics
8:10 Progress in robotics
13:34 Imitation learning and reinforcement learning
21:37 Simulated data, real data, and reliability
27:53 The increasing capabilities of robotics
36:23 Entrepreneurship and co-founding Gradescope
44:35 The story behind Covariant
47:50 Pieter's communication tips
52:13 What Pieter's currently excited about
55:08 Focusing on good UI and high reliability
57:01 Outro
503: Deep Reinforcement Learning for Robotics
Pieter Abbeel joins us to discuss his work as an academic and entrepreneur in the field of AI robotics and what the future of the industry holds.
In this episode you will learn:
How does Pieter do it all? [5:45]
Pieter’s exciting areas of research [12:30]
Research application at Covariant [32:27]
Getting into AI robotics [42:18]
Traits of good AI robotics apprentices [49:38]
Valuable skills [56:40]
What Pieter hopes to look back on [1:04:30]
LinkedIn Q&A [1:06:51]
Additional materials: www.superdatascience.com/503
Peter Chen on building brains for robots in the real world
In episode seven of The Robot Brains Podcast, our guest is Covariant CEO and co-founder Peter Chen. Peter is one of Pieter Abbeel's closest collaborators for the past five years, with Peter having studied for his PhD in Pieter's lab in Berkley before then working together at OpenAI. Now they are co-founders of Covariant, which they started back in 2017 with Peter as the CEO. On this episode we explore the future of AI-powered robotics, looking at what happens when you teach industrial robots to "think" and "learn" from their environment. Host: Pieter Abbeel | Executive Producers: Ricardo Reyes & Henry Tobias Jones | Audio Production: Kieron Matthew Banerji | Title Music: Alejandro Del Pozo Hosted on Acast. See acast.com/privacy for more information.
Reinforcement Learning for Industrial AI with Pieter Abbeel - #476
Today we’re joined by Pieter Abbeel, a Professor at UC Berkeley, co-Director of the Berkeley AI Research Lab (BAIR), as well as Co-founder and Chief Scientist at Covariant.
In our conversation with Pieter, we cover a ton of ground, starting with the specific goals and tasks of his work at Covariant, the shift in needs for industrial AI application and robots, if his experience solving real-world problems has changed his opinion on end to end deep learning, and the scope for the three problem domains of the models he’s building.
We also explore his recent work at the intersection of unsupervised and reinforcement learning, goal-directed RL, his recent paper “Pretrained Transformers as Universal Computation Engines” and where that research thread is headed, and of course, his new podcast Robot Brains, which you can find on all streaming platforms today!
The complete show notes for this episode can be found at twimlai.com/go/476.
Episode 13 - Pieter Abbeel
Thinking robots: that's how much of the world envisions artificial intelligence and if there is one person on the planet who understands the limitations and promise of intelligence in robots, it's Pieter Abbeel, one of the world's foremost experts on robotic learning systems. In this episode, Pieter talks about robot memories and the prospect of robots with personalities eventually assisting in the home. Listen and learn about your future.
UC Berkeley’s Pieter Abbeel on How Deep Learning Will Help Robots Learn - Ep. 82
Robots can do amazing things. Compare even the most advanced robots to a three-year old, however, and they can come up short. UC Berkeley Professor Pieter Abbeel has pioneered the idea that deep learning could be the key to bridging that gap: creating robots that can learn how move through the world more fluidly and naturally. We caught up with Abbeel, who is director of the Berkeley Robot Learning Lab and cofounder of Covariant AI, a Bay Area company developing AI software that makes it easy to teach robots new and complex skills, at GTC 2019.
Pieter Abbeel: Deep Reinforcement Learning
Pieter Abbeel is a professor at UC Berkeley, director of the Berkeley Robot Learning Lab, and is one of the top researchers in the world working on how to make robots understand and interact with the world around them, especially through imitation and deep reinforcement learning. Video version is available on YouTube. 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, or YouTube where you can watch the video versions of these conversations.
Reinforcement Learning Deep Dive with Pieter Abbeel - TWiML Talk #28
This week our guest is Pieter Abbeel, Assistant Professor at UC Berkeley, Research Scientist at OpenAI, and Cofounder of Gradescope. Pieter has an extensive background in AI research, going way back to his days as Andrew Ng’s first PhD student at Stanford. His research today is focused on deep learning for robotics. During this conversation, Pieter and I really dig into reinforcement learning, a technique for allowing robots (or AIs) to learn through their own trial and error. Nerd alert!! This conversation explores cutting edge research with one of the leading researchers in the field and, as a result, it gets pretty technical at times. I try to uplevel it when I can keep up myself, so hang in there. I promise that you’ll learn a ton if you keep with it. The notes for this show can be found at twimlai.com/talk/28
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