Podcasts about covariant

这次依旧是硬核话题，我们跟学术大牛深度聊聊2024年上半年美国创投圈最火的的话题之一，具身智能。 没错，智能机器人之火终于从国内来到美国了。在去年下半年的时候，美国创投界还是在关注大模型和应用、infra等等，虽然Deepmind RT-2 等工作彼时已经崭露头角，更喜欢软件的美国VC似乎还在犹豫机器人这个太硬的赛道。但是从今年上半年开始，事情似乎有了变化。 Hello World, who is OnBoard!? 除了Figure AI 这样的人形机器人公司获得了英伟达、微软等一系列战投的加持，硅谷的老牌基金们也疯狂涌入了所谓的机器人大模型公司，比如学术大牛创立的 Physical intelligence, Skild, 还有 Cruise 前CEO 创立的Bot company, 等等。 这次的嘉宾也是大名鼎鼎，UCSD 计算机科学副教授，苏昊老师，关注具身智能和3D视觉领域的同学应该都不陌生。他参与的一系列AI数据集和软件工作，从ImageNet到ShapeNet、PointNet、SAPIEN，以及最近的ManiSkill等等，都是三维视觉、机器人操作等领域穿越几个时代的标志性作品。 苏昊老师现在还是智能机器人创业公司Hillbot 的联合创始人，我们深度探讨了： 过去一年，我们从学术界、工业界讨论的种种话题，又有了哪些新的进展？ 大模型的发展如何影响具身智能的不同技术路径？ 大模型带来的泛化能力，跟硬件、控制系统等，又会怎样相互作用？ 机器人模型里的数据问题，有哪些解决方案？ 具身智能这个看似很纷繁的话题，苏昊老师总是能抽丝剥茧，相信你们也能从我们两个多小时的交流中，受益匪浅。Enjoy! 对了！今年年初，Onboard 就发布过一期关于具身智能的讨论，嘉宾包括了 Deepmind Robotics，高仙机器人和UCSD 的不同视角的重磅嘉宾。那一期讨论也非常精彩，建议大家回去复习哈！ 嘉宾介绍 苏昊 (Twitter @HaoSuLabUCSD)，UC San Diego Associate Professor，Hillbot智能机器人初创公司创始人、CTO。Stanford PhD, UCSD 具身智能实验室主任，数据科学研究所创始成员，以及视觉计算中心和情境机器人研究所成员。他的研究工作集中在开发算法来模拟、理解并与物理世界互动。 OnBoard! 主持：Monica, 美元VC投资人，前 AWS 硅谷团队+ AI 创业公司打工人，公众号M小姐研习录 (ID: MissMStudy) 主理人 | 即刻：莫妮卡同学 我们都聊了什么 03:04 苏昊的学术历程，为什么最近觉得有关证明的研究进展对机器人领域很有启发？ 10:05 从智能演化的角度，理解“具身智能”这个“老概念” 15:01 为什么从语言而不是视觉上最先看到了接近人类的智能？ 21:31 实现具身智能有哪些主流的路线？如何理解不同路径不同切入点背后的逻辑？ 32:10 可以通过大模型的能力实现运动控制吗？有泛化性的控制数据要怎么采集？ 38:26 演示学习 (learning from demonstration) 有哪些不同路径？ALOHA这类遥操作有什么利弊？ 47:00 规划和执行需要一起做训练吗？做一个端到端的系统核心难点在哪里？ 51:15 划重点：好的算法的本质就是降低对数据的需求 52:23 针对机器人的大模型会跟LLM架构有什么异同？ 59:31 人形机器人可以解决数据和能力泛化的问题吗？ 66:16 模拟器能解决训练数据的问题吗？近年来模拟器相关技术有什么关键进展？ 78:31 AI生成3D，Sora 等新技术进展对实现 sim2real 路径有什么影响？ 95:26 苏昊老师现在的创业项目 Hillbot 100:32 快问快答：推荐的书，影响最大的人，具身智能被高估和低估的话题，如何解压！ 重点词汇和公司 Boston Dynamics PI (Physical Intelligence) ⁠OpenAI DALL-E 3⁠ ⁠SAPIEN: A SimulAted Part-based Interactive ENvironment⁠ ⁠ManiSkill⁠: a powerful unified framework for robot simulation and training powered by SAPIEN. ⁠Google Deepmind RT-1⁠: Robotics Transformer for real-world control at scale ⁠Google Deepmind RT-2⁠: New model translates vision and language into action, ⁠Paper⁠ ⁠Google Deepmind Open X-Embodiment⁠: Robotic Learning Datasets and RT-X Models, ⁠Paper⁠ ⁠ALOHA⁠: A Low-cost Open-source Hardware System for Bimanual Teleoperation ⁠Mobile ALOHA⁠: a low-cost and whole-body teleoperation system for data collection. Behavior Colony：行为克隆 Learning from Demonstration：示范学习 ⁠Meta AI Habitat⁠: A Platform for Embodied AI Research ⁠AI2⁠: The Allen Institute for Artificial Intelligence ⁠Segment Anything Model (SAM)⁠: a new AI model from Meta AI that can "cut out" any object, in any image, with a single click ⁠robot-VILA⁠: Look Before You Leap: Unveiling the Power of GPT-4V in Robotic Vision-Language Planning ⁠CoPa⁠: General Robotic Manipulation through Spatial Constraints of Parts with Foundational Model ⁠ImageNet: image database organized according to the WordNet hierarchy⁠ ⁠EP 44.【AI年终特辑3】具身智能深度对话：从学术到产业，机器人的ChatGPT时刻来了吗？ - OnBoard! | 小宇宙⁠ ⁠Debate: Is Scaling Enough to Deploy General Purpose Robots @CoRL2023⁠ ⁠解密机器人大模型RFM-1：Covariant创始人陈曦专访⁠ ⁠对话高阳：具身大模型框架ViLa+CoPa⁠ 参考文章欢迎关注M小姐的微信公众号，了解更多中美软件、AI与创业投资的干货内容！ M小姐研习录 (ID: MissMStudy) 欢迎在评论区留下你的思考，与听友们互动。如果你用 Apple Podcasts 收听，也请给我们一个五星好评，这对我们非常重要。 最后！快来加入Onboard！听友群，结识到高质量的听友们，我们还会组织线下主题聚会，开放实时旁听播客录制，嘉宾互动等新的尝试。添加任意一位小助手微信，onboard666, 或者 Nine_tunes,小助手会拉你进群。期待你来！

Google entered a $2.7 billion agreement with AI startup Character.AI to rehire Noam Shazeer, an expert in AI chatbots. In August, Google signed the agreement to obtain a license for Character.AI's technology. Shazeer, who left Google in 2021, contributed significantly to conversational AI during his tenure. He founded Character.AI and secured over $150 million in funding, achieving a valuation of $1 billion by March. Under the recent agreement, Shazeer returns to Google as part of the DeepMind research team, earning hundreds of millions in the process. This move aligns with a trend among tech companies, as demonstrated by Amazon's licensing deals with AI robotics startup Covariant.Learn more on this news visit us at: https://greyjournal.net/ Hosted on Acast. See acast.com/privacy for more information.

Our 182nd episode with a summary and discussion of last week's big AI news! With hosts Andrey Kurenkov and Jeremie Harris. Read out our text newsletter and comment on the podcast at https://lastweekin.ai/. If you would like to become a sponsor for the newsletter, podcast, or both, please fill out this form. Email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai Sponsors: - Agent.ai is the global marketplace and network for AI builders and fans. Hire AI agents to run routine tasks, discover new insights, and drive better results. Don't just keep up with the competition—outsmart them. And leave the boring stuff to the robots

Cohosts Steve Crowe and Mike Oitzman discuss the latest robotics news from the last week, including a review of the July funding report, which topped $1.3B. 1X also unveiled the NEO Beta humanoid model and prepares for pilot deployments into test home environments. The recent news of the Covariant AI acquisition or acqui-hire by Amazon is an interesting strategic move by the retailing giant. Both companies declined to comment on the details of the acquisition, so we asked ex-Amazon robotics leader and current CEO and founder of Collaborative Robotics, Brad Porter, to join us on the show to share his insights into the state of AI development and why this is an exciting move by Amazon. To learn more about Collaborative Robotics, goto: https://www.co.bot/

Craig Schwartz is the Head of Legal at Covariant, an AI and robotics company out of Berkeley. He is a veteran tech lawyer with 20 years of experience at the intersection of emerging technology and regulated markets. Craig previously worked for Palantir Technologies, where he led the USG Partnerships team and served as Lead Counsel for the Intelligence Community business. Now at Covariant, Craig is part of a team building foundational models for the physical world, focusing on automation and AI integration in industrial settings. In this episode… Europe's aging workforce is fueling a growing demand for automated labor solutions, with US-based AI robotics companies stepping in to fill the gap. But this trend isn't just about technological innovation. For US-based companies entering the European market, success in this landscape requires a deep understanding of product capabilities and the global regulatory environment. To stay ahead, companies must make informed decisions on ethical AI use and on how to handle data — from collection to storage to use — without stepping on any global regulatory toes.  With emerging regulations like the EU AI Act and Internet of Things (IoT) legislation, it's now more important than ever for companies to integrate privacy considerations into product design from the start. By adopting privacy-by-design principles early on, companies like Covariant can meet anticipated global compliance requirements and create operational efficiencies, demonstrating their proactive approach to these regulatory challenges. In this week's episode of She Said Privacy/He Said Security, Jodi and Justin Daniels chat with Craig Schwartz, the Head of Legal at Covariant, who shares invaluable insights on navigating the complex intersection of AI, robotics, and international privacy regulations. Craig explains the steps Covariant takes to stay ahead of global privacy regulations. He also discusses the critical need for legal professionals in tech to immerse themselves in technical product knowledge, the challenges of applying existing global privacy laws, such as GDPR, to cutting-edge technologies, and the potential impact of antitrust policies on innovation in the AI space.

LLMs are democratizing digital intelligence, but we're all waiting for AI agents to take this to the next level by planning tasks and executing actions to actually transform the way we work and live our lives.  Yet despite incredible hype around AI agents, we're still far from that “tipping point” with best in class models today. As one measure: coding agents are now scoring in the high-teens % on the SWE-bench benchmark for resolving GitHub issues, which far exceeds the previous unassisted baseline of 2% and the assisted baseline of 5%, but we've still got a long way to go. Why is that? What do we need to truly unlock agentic capability for LLMs? What can we learn from researchers who have built both the most powerful agents in the world, like AlphaGo, and the most powerful LLMs in the world?  To find out, we're talking to Misha Laskin, former research scientist at DeepMind. Misha is embarking on his vision to build the best agent models by bringing the search capabilities of RL together with LLMs at his new company, Reflection AI. He and his cofounder Ioannis Antonoglou, co-creator of AlphaGo and AlphaZero and RLHF lead for Gemini, are leveraging their unique insights to train the most reliable models for developers building agentic workflows. Hosted by: Stephanie Zhan and Sonya Huang, Sequoia Capital  00:00 Introduction 01:11 Leaving Russia, discovering science 10:01 Getting into AI with Ioannis Antonoglou 15:54 Reflection AI and agents 25:41 The current state of Ai agents 29:17 AlphaGo, AlphaZero and Gemini 32:58 LLMs don't have a ground truth reward 37:53 The importance of post-training 44:12 Task categories for agents 45:54 Attracting talent 50:52 How far away are capable agents? 56:01 Lightning round Mentioned:  The Feynman Lectures on Physics: The classic text that got Misha interested in science. Mastering the game of Go with deep neural networks and tree search: The original 2016 AlphaGo paper. Mastering the game of Go without human knowledge: 2017 AlphaGo Zero paper Scaling Laws for Reward Model Overoptimization: OpenAI paper on how reward models can be gamed at all scales for all algorithms. Mapping the Mind of a Large Language Model: Article about Anthropic mechanistic interpretability paper that identifies how millions of concepts are represented inside Claude Sonnet Pieter Abeel: Berkeley professor and founder of Covariant who Misha studied with A2C and A3C: Advantage Actor Critic and Asynchronous Advantage Actor Critic, the two algorithms developed by Misha's manager at DeepMind, Volodymyr Mnih, that defined reinforcement learning and deep reinforcement learning

Ian Rust, founder and CEO of Revoy, discusses their innovative approach to hybridizing the propulsion system of commercial vehicles. Revoy's solution involves adding a third electric vehicle to the traditional tractor-trailer setup, allowing for significant cost savings and decarbonization. Links Show notes: http://brandonbartneck.com/futureofmobility/ianrust Edison Manufacturing Exchange: https://brandonbartneck.substack.com/publish/home https://www.linkedin.com/in/ian-rust-85a41b43/ https://www.revoy.com/ Takeaways: Revoy's innovative approach to hybridizing the propulsion system of commercial vehicles involves adding a third electric vehicle to the traditional tractor-trailer setup. The main challenge in electrifying the commercial vehicle space is the high cost and limited lifespan of current electric vehicle technology. Revoy addresses this challenge by using lithium iron phosphate batteries, which have a longer cycle life and can go over 10,000 cycles. Revoy also offers a battery swapping technology that integrates with the existing trailer-to-truck interface, allowing for quick and efficient swaps during long-haul trips. The hybrid solution provided by Revoy improves efficiency, performance, and safety for commercial vehicles. Revoi coordinates the electric powertrain with the pedal to make the transition to electric trucks seamless for drivers. The commercial model charges based on the unit of energy, similar to diesel, and there is no need for modifications to fill up the tank with a pre-charged battery pack. Chapters Hybrid Vehicles and Propulsion Systems Electrifying Commercial Vehicles: The Modular Approach Operational Considerations and Safety in Electric Vehicle Deployment Strategic Viability and Cost Competitiveness Building a Strong Team: Trust, Empowerment, and Passion Cultural Focus: Safety, Minimum Viable Product, and What Not to Do Early Adoption of Electrification in Fleets Rethinking the Tractor-Trailer Setup Advancements in Technology Conclusion Ian Rust Bio: Ian Rust is an innovator, founder and roboticist with over 14 years of experience of automation and robotics in the clean transportation and the sustainability industry, with the goal of moving trucking into a more sustainable future. Ian has been passionate about technology and how it is impacted by and impacts people and historical trends.Ian founded Revoy (formerly SixWheel), a company backed by Y Combinator, in 2021, creating an autonomous vehicle technology to address climate change. Prior to founding Revoy, Ian led robotics projects at Amazon Lab126 and Google X, later moving into starting notable robotics companies as the founding engineer of Cruise Automation and serving on the early team at Covariant and Petra. Rust holds a B.S. and M.S. in mechanical engineering from the Massachusetts Institute of Technology where he focused on robotics. About Revoy: Revoy, a simple and truly viable alternative solution to decarbonize the trucking industry, is democratizing electric trucking and providing a clear pathway for existing trucking fleets to completely eliminate emissions. Revoy's charging infrastructure and innovative Revoy swapping network aims to be the backbone of the future of electric road freight, allowing fleets to lower carbon emissions and costs, while increasing MPG by over 150%. This technology is made in the USA, FMVSS compliant and compliant with all length and weight (bridge and GVW) regulations. Future of Mobility: The Future of Mobility podcast is focused on the development and implementation of safe, sustainable, effective, and accessible mobility solutions, with a spotlight on the people and technology advancing these fields. Edison Manufacturing and Engineering: Edison is your low volume contract manufacturing partner, focused on assembly of complex mobility and energy products that don't neatly fit within traditional high-volume production methods. linkedin.com/in/brandonbartneck/ brandonbartneck.com/futureofmobility/

Mike Volpi is a longtime venture capitalist who joined Index Ventures in 2009 to establish the firm's San Francisco office and North American operations. Prior, he was Chief Strategy Officer at Cisco, overseeing a run of acquisitions still studied today as a model for technology merger strategy. Mike invests primarily in artificial intelligence, infrastructure, and open-source companies, and currently serves on the boards of multiple companies including Aurora, ClickHouse, Cockroach Labs, Cohere, Confluent, Covariant.ai, Kong, Scale, Sonos, and Wealthfront.     In this episode, Kevin and Mike discuss Mike's early childhood, how he got interested in the study of engineering, and his career experiences—including what led to Mike's long career at Cisco and his current Partner position at Index—including his board experiences with multiple companies.     Mike Volpi | Index Ventures  Kevin Scott    Behind the Tech with Kevin Scott    Discover and follow other Microsoft podcasts.    

非常久违的两位主播的研究对谈来了！在 ChatGPT 诞生近一年半的时间里，生成式 AI 领域几乎每天都在发生激动人心的变化。从大模型到应用，从软件到机器人，从文字到图片、视频、声音，从全新的商业模式到对现有业务的赋能。比起很久之前那一期对谈，不只是 AI，两位主播也都分别开始了新的征程，过去一年有了很多机会在中美一线市场频繁穿梭，终于有机会分享一些我们沉淀下来的观察与思考。 Hello world, who is OnBoard!? Monica 去年加入了另一家美元 VC，更聚焦地关注海外的早期投资机会。GN从美元机构离开，创立了 SaaS/AI 社区 Linkloud（公众号同名），帮助越来越多中国软件和科技公司走向全球。AI 无疑是这个时代里边最大的变量之一，近两个小时，过去一年在中美频繁奔波的我们，探讨了你关心的各种问题： AI应用落地真的不及预期吗？ 从应用到infra有哪些有意思的落地案例？ 如何看待国内AI的进展和弯道超车的机会？ 中美差异背后的原因是什么？ AI公司出海有什么最佳实践与建议？ 一些拙见，抛砖引玉，希望对大家有一些些启发~！Enjoy! 我们都聊了什么 03:11 两位主播的自我介绍，以及最近半年日常使用的AI产品。 15:54 一年以来，哪些AI产品或落地超预期或不及预期？ 20:24 为什么还在成长期的SaaS公司最容易将AI落地？ 23:11 AI在全球其他地区的渗透有什么不一样的地方？ 26:00 为什么在美国大模型和Infra层的进展会超预期？ 30:16 对苹果Siri的预期，以及可能面临的限制在那里？ 35:31 Soundhound是如何结合Voice AI来落地点餐场景，并完成商业化的？ 40:42 EvolutionIQ是如何在保险领域结合AI并促进业务增长的？ 49:08 Monica错过的一家初创公司是如何将AI融入销售人员工作流的？ 55:47 为什么AI代码生成领域在今年会百花齐放？ 65:38 国内AI的进展与美国有什么不同，为什么在C端会出现更多产品？ 76:07 中美资本市场的差异在哪里，以及创业者该如何在市场下行时树立长期愿景？ 81:58 为什么中美差异最大的是AI在B端的发展，以及机器人是否是个变量？ 92:55 为什么“单点极致”可能是中国AI公司出海最重要的方式？ 97:33 为什么出海第一步要走出国门，感受并融入开放的生态？ 100:55 作为投资人，如何看待面对大模型公司下创业公司的壁垒和竞争力？ 106:41 两位主播对今年AI的“大胆”预测和期待有哪些？ 119:02 最后，奉上我们这一年新种草的播客和Newsletter，希望对听众有帮助！ 提到的公司 Devin (by Cognition Lab): cognitionlab.com SWE-agent: swe-agent.com DBRX by Databricks: github.com Jamba: A Hybrid Transformer-Mamba Language Model Hume AI: www.hume.ai Monica.im: www.youtube.com Gemini Advanced: www.cnn.com Perplexity: www.perplexity.ai Kimi Chat: asianwiki.com Six助手（目前还在灰度测试，微信不接受新用户啦） Workstream: www.workstream.us Klarna: www.klarna.com Speak: https://www.speak.com/ Lepton.ai: www.lepton.ai Soundhound: www.soundhound.com EvolutionIQ: evolutioniq.com Siro: siro.ai Magic.dev: magic.dev Codium: www.roboleary.net Cursor: www.cursor.app Augment: www.augment.co Sweep: www.sweep.io Typeface: www.typeface.ai Sierra AI: www.siera.ai Physical intelligence: www.bloomberg.com Skild: www.skild.ai Covariant: covariant.ai Figure: www.figure.ai Cobot: www.tm-robot.com Deepmind RT-X: deepmind.google 推荐的播客和newsletter Latent Space | swyx & Alessio | Substack Bg2 Pod Interconnected | Where Tech, Investing, Geopolitics Come ... Elad Gil First Round Review What's

Covariant's RFM-1: Jon Krohn explores the future of AI-driven robotics with RFM-1, a groundbreaking robot arm designed by Covariant and discussed by A.I. roboticist Pieter Abbeel. Explore how this innovation aims to merge digital intelligence with the physical world, promising a new era of efficiency and autonomy. Additional materials: www.superdatascience.com/774 Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information.

Robotics startup Covariant is experimenting with a ChatGPT-style chatbot that can control a robotic arm, as a way to create machines that can be more helpful in the physical world. Thanks for listening to WIRED. Talk to you next time for more stories from WIRED.com and read this story here. Learn more about your ad choices. Visit megaphone.fm/adchoices

Covariant launched RFM-1 (Robotics Foundation Model 1) a “large language model (LLM), but for robot language.” Plus did the Princess of Wales, aka “Kate” photoshop a picture of herself with her three children? And why are tablet sized handheld gaming machines rising in popularity?Starring Tom Merritt, Shannon Morse, Roger Chang, Joe.Link to the Show Notes.

Covariant launched RFM-1 (Robotics Foundation Model 1) a “large language model (LLM), but for robot language.” Plus did the Princess of Wales, aka “Kate” photoshop a picture of herself with her three children? And why are tablet sized handheld gaming machines rising in popularity? Starring Tom Merritt, Shannon Morse, Roger Chang, Joe To read the show notes in a separate page click here! Support the show on Patreon by becoming a supporter!

Peter Chen is the co-founder and CEO of Covariant. Peter's problem is this: How do you take the AI breakthroughs of the past decade or so, and make them work in robots? Peter was one of the first employees at OpenAI, the maker of ChatGPT. On the show, he talks about how AI has evolved, and why it's so difficult to teach a robot to fold a towel.See omnystudio.com/listener for privacy information.

Our guest today is Ryan Shannon, AI Investor at Radical Ventures, a world-known venture capital firm investing exclusively in AI. Radical's portfolio includes hot startups like Cohere, Covariant, V7 and many more.  In our conversation, we talk about how to start an AI company & what makes a good founding team. Ryan also explains what he and Radical look for when investing and how they help their portfolio after the investment. We finally chat about some cool AI Startups like Twelve Labs and get Ryan's predictions on hot startups in 2024. If you enjoyed the episode, please leave a 5 star review and subscribe to the AI Stories Youtube channel.Link to Train in Data courses (use the code AISTORIES to get a 10% discount): https://www.trainindata.com/courses?affcode=1218302_5n7krabaFollow Ryan on LinkedIn: https://www.linkedin.com/in/ryan-shannon-1b3a7884/Follow Neil on LinkedIn: https://www.linkedin.com/in/leiserneil/  ---(0:00) - Intro(2:42) - Ryan's background and journey into AI investing(11:15) -  Radical Ventures(14:34) - How to keep up with AI breakthroughs? (22:42) - How Ryan finds and evaluates founders to invest in(32:54) - What makes a good founding team? (38:57) - Ryan's role at Radical (45:53) - How to start an AI company (50:22) - Twelve Labs(59:19) - Future of AI and hot startups in 2024(1:09:48) - Career advice

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. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @peterxichen 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

Today's episode is a deep dive into warehouse automation. We discuss the role humanoids are hoping to play in logistics, including how GXO is testing the Digit humanoid from Agility Robotics. We also discuss the state of mobile robots with John Santagate, the Vice President of Robotics at Körber Supply Chain. We also talk about artificial intelligence and the growth of picking robots with Peter Chen, Co-Founder and CEO of Covariant.

This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere. If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai   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.   Stay updated: Craig Smith's Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI (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  

This Week in Startups is brought to you by… Lemon.io - Hire pre-vetted remote developers, get 15% off your first 4 weeks of developer time at https://Lemon.io/twist Vanta. Compliance and security shouldn't be a deal-breaker for startups to win new business. Vanta makes it easy for companies to get a SOC 2 report fast. TWiST listeners can get $1,000 off for a limited time at vanta.com/twist LinkedIn Marketing. To redeem a $100 LinkedIn ad credit and launch your first campaign, go to LinkedIn.com/nextunicorn * 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! * Time stamps: (00:00) 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 * Follow Peter: https://twitter.com/peterxichen Check out Covariant : https://covariant.ai/ * Read LAUNCH Fund 4 Deal Memo: https://www.launch.co/four Apply for Funding: https://www.launch.co/apply Buy ANGEL: https://www.angelthebook.com Great recent interviews: Steve Huffman, Brian Chesky, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland, PrayingForExits, Jenny Lefcourt Check out Jason's suite of newsletters: https://substack.com/@calacanis * Follow Jason: Twitter: https://twitter.com/jason Instagram: https://www.instagram.com/jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis * Follow TWiST: Substack: https://twistartups.substack.com Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin * Subscribe to the Founder University Podcast: https://www.founder.university/podcast

Die Roboter kommen! Und zwar in die Logistikstandorte der Otto Group. Dort unterstützen sie die Kolleg*innen vor Ort, zum Beispiel bei sich wiederholenden Aufgaben oder um Auftragsspitzen abzufedern. Das Besondere: Diese Roboter können nicht nur eine bestimmte Tätigkeit automatisiert wiederholen, sie können „sehen, denken und handeln“ – dank künstlicher Intelligenz. Was es damit auf sich hat und welche Bedeutung das Teamwork von Mensch und smarter Technologie für die Zukunft der Logistik hat, haben wir mit unserem Gast Kay Schiebur, Konzern-Vorstand Services, besprochen. Darüber hinaus geht es um die aktuellen Herausforderungen der Branche, Kays Vision für die Handelslogistik von morgen und die Frage, ob Dark Warehouses wirklich die Zukunft sind. 0:32: Intro und Einleitung ins Thema 01:20: Hintergrundinformationen zur strategischen Partnerschaft mit Covariant 03:18 Interview mit Kay Schiebur, Konzern-Vorstand Services 11:43 Outro und Ausblick Bonusfolge mit KI-Forscher und Covariant-Mitgründer Peter Chen: https://soundcloud.com/ottogroup/was-macht-roboter-intelligent-peter-chen Wie die Otto Group mit Künstlicher Intelligenz die Logistik revolutioniert: https://www.ottogroup.com/de/stories/story/kuenstliche-intelligenz-sehende-roboter-und-die-logistik-von-morgen.php Otto Group auf LinkedIn: www.linkedin.com/company/ottogroup/ Otto Group auf Twitter: www.twitter.com/ottogroup_com Otto Group auf Instagram: www.instagram.com/ottogroupcom/ Impressum: www.ottogroup.com/de/impressum/

Peter Chen ist einer der weltweit führenden Experten auf dem Gebiet der Künstlichen Intelligenz und Mitbegründer von Covariant, einem Unternehmen, das sich auf die Entwicklung von KI-gesteuerten Robotern spezialisiert hat. Peter hat intensiv im Bereich der KI geforscht, unter anderem als Doktorand an der UC Berkeley, und sammelte weitere Erfahrungen bei OpenAI. Die Otto Group ist eine strategische Partnerschaft mit Covariant eingegangen, um ihr Logistiknetzwerk mit KI-Robotik zu versorgen – diese wunderbare Gelegenheit haben wir genutzt, um mit ihm über die Herausforderungen von Robotern zu sprechen, die "sehen, denken und handeln" können, was Lagerhäuser zu einer hochkomplexen Umgebung für einen Roboter macht und inwiefern die KI von Covariant von der gemeinsamen Zeit drei der Gründer bei OpenAI geprägt ist. „Künstliche Intelligenz: Sehende Roboter und die Logistik von morgen“ – die ganze Story könnt ihr hier lesen: https://www.ottogroup.com/de/stories/story/kuenstliche-intelligenz-sehende-roboter-und-die-logistik-von-morgen.php Otto Group auf LinkedIn: https://www.linkedin.com/company/ottogroup/ Otto Group auf Twitter: https://twitter.com/ottogroup_com Otto Group auf Instagram: https://www.instagram.com/ottogroupcom/ Impressum: https://www.ottogroup.com/de/impressum/

Rocky Duan, CTO of Covariant joins joins Host Pieter Abbeel.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.

Pre-IPO Stock Market Update - Apr 07, 2023 | Buys stocks on Twitter powered by eToro, Databrick's ChatGPT competitor, SpaceX's Starship to launch next week, Tyler Siconolfi research (OpenSea, Deel)00:31 | Twitter + eToro partner to bring stock trading to Twitter users- Twitter will allow users to view market charts on an expanded range of financial instruments and buy and sell stocks and other assets from eToro- Twitter cashtags will be expanded to cover far more instruments and asset classes- Twitter users will be able to click a button that says “view on eToro,” which takes you through to eToro's site, and then buy and sell assets on its platform- Musk wants to turn Twitter into a super app like China's WeChat- Musk changed the corporate name of Twitter to X Corp last week01:50 | Databricks releases ChatGPT competitor- Dolly 2.0 = first open-source, instruction-following LLM fine-tuned on a transparent and freely available dataset that is also open-sourced to use for commercial purposes- Dolly 2.0 is available for commercial applications without the need to pay for API access or share data with third parties like OpenAI requires- Databricks is open sourcing the dataset on which Dolly 2.0 was trained on, called databricks-dolly-15k02:59 | SpaceX new rocket Starship to launch next week- Starship is nearly 40 stories tall and has 5.5x more payload capability vs Falcon9; 22 tons vs 125 tons- Starship's first orbital launch to happen next week ... targeting Mon, 17 Apr- Starship is designed to be reusable but for this initial orbital test the focus is simply reaching orbit- The booster - Super Heavy - will splash down in the Gulf of Mexico- The spacecraft - Starship - will splash down near Hawaii- Musk said there is a 50% chance of success for the mission- A second Starship orbital flight is estimated for later this year04:09 | Tyler's Corner by Tyler Siconolfi ... OpenSea and Deel- OpenSea, the NFT exchange, announced it will be launching OpenSea Pro, a NFT marketplace aggregator that allows users to trade NFTs from different marketplaces all under one platform. This move has now put OpenSea in front of Blur, a rival NFT marketplace, as the most popular NFT marketplace based on daily active user.- Deel, the HR platform, has expanded its immigration service, making it significantly easier and less time consuming to hire and move people around the globe. The new expansion allows more than 25 different countries to use their platform and streamline the immigration process of global employees. Deel's 2022 revenue was up 418% but its stock price was down 45% in secondary market trading.05:21 | Large capital raises- BYJU'S | $700m Series L. $22.0b valuation- LayerZero | $120m Series B, $3.0b valuation- SJSemi | $340m Series C1, $2.0b valuation- Quantexa | $129m Series E, $1.8b valuation- Covariant | $75m Series C1, $625m valuation06:34 | Pre-IPO stock market performance- Pre-IPO stocks were down 2.25% for the week vs the S&P 500 down -0.02%. - YTD pre-IPO stocks still trail the S&P by about 19%.- OpenSea and Kraken have given up all their gains YTD. OpenSea is now up only 2% … Kraken is down 3%. Discord, Epic Games, Airtable, Flexport, and Chime are still all down over 20%.- A big week for the challenger banks. Chime and Revolut were both up big. 15% and 13% respectfully.- OpenSea was down 25% just last week alone. Kraken was down 12% last week. Not a great week for crypto related businesses.AG Dillon & Co venture capital funds...- AG Dillon SpaceX Pre-IPO Stock Fund = www.agdillon.com/spacex- AG Dillon Pre-IPO Equity Fund (top 15 pre-IPO stocks) = www.agdillon.com/top15

In this episode, we discuss the news of the shutdown of Argo AI and the state of autonomous driving, including the upcoming IAC race event. Mike interviews Covariant.AI CEO, Peter Chen, and they discuss the new CovariantOne RaaS solution, that's based on performance SLAs for the Covariant warehouse solution.

The Council of Supply Chain Management Professionals (CSCMP) and CSCMP's Supply Chain Quarterly  bring you a new podcast filled with deep industry discussions. We talk to today's top thought innovators, spanning topics across the entire supply chain. Supply Chain in the Fast Lane fast tracks topics you need to know from leaders you want to know.In this second season of eight episodes, we look at Supply Chain Digitalization.EPISODE 4: The convergence of AI and RoboticsWhile artificial intelligence (AI) has been around for a number of years, it's only been recently that we have been seeing the application of this technology in the intralogistics and logistics realm. In this interview, Anu Saha, head of product marketing for the AI robotics firm Covariant, talks about some exciting applications that are driving efficiencies in today's supply chains. Moderator: Susan Lacefield, executive editor, CSCMP's Supply Chain QuarterlySupply Chain in the Fast Lane is sponsored by DHLLinksLearn more about CSCMPJoin the CSCMP communityCSCMP's Supply Chain QuarterlySubscribe to CSCMP's Supply Chain Quarterly Sign up for our FREE newslettersListen to our sister podcast, Top 10 Supply Chain Threats Advertise with CSCMP's Supply Chain Quarterly

“We're building robots that swim like fish and move like turtles. Robots that brush your hair, robots that pack your groceries, and can reason that you shouldn't put milk on top of lettuce. Robots that can recycle, robotic pills that enable incision free surgeries. In each of these examples, we have to think about the body of the robot, we have to think about the brain of the robot, and what is the interaction between the robot and the users.” - Daniela RusHear about the latest advances in robotics from those working in the forefront of the field.Daniela Rus is a Professor of Electrical Engineering and Computer Science at MIT and Director of the Computer Science and Artificial Intelligence Laboratory. Her research spans across all of robotics, everything from soft surface robotics, to human robot interactions, to autonomous driving. Pieter Abeel is the Director of the Berkeley Robot Learning Lab and Co-director of the Berkeley AI Research Lab at the University of California. Pieter is also the co-founder of Covariant.ai, which looks to bring some of the research that he's been doing with his group at Berkeley to real world applications in fulfillment centers and beyond. He's also the host of the Robot Brains podcast.Daniela & Pieter are interviewed by Index's Bryan Offutt.“In academia, robotics is about emphasizing novelty. It's about going places we've never been before….. But for companies that bring robotics into the real world, the real challenge is about achieving really high reliability.” - Pieter Abeel 

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 --- Connect with Pieter:

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

On this episode, we discuss what it means for a technology to be transformational? Why Artificial Intelligence (AI) matters so much to us? What is AI? What are some good examples of AI? How AI works? Who are the key people & organizations to follow? The media narratives and how it distorts reality, our own personal experiences with AI, the limitations of AI and finally answer the question, "Will AI transform our lives?"Links to folks and organizations and other material mentioned in the episode People: Andrew Ng, Andrej Karpathy, Ben Lorica, Gary Marcus, Peter Diamandis, Sam Altman, Fei-Fei-Li, Pieter AbbeelCompanies/ organizations :  Singularity University, Google, Covariant.aiTweets and articles: GPT-3Uber/Lyft getting out of autonomous drivingAlpha-fold breakthroughBoston Dynamics robotsBlenderbot 2.0Show info:  Website, TwitterCo-hosts & Creators:  Kapil, Ravi 

In episode 14 of The Robot Brains Podcast we sit down and chat with Mike Volpi of Index Ventures. Index is one of the largest and best known VC firms in Silicon Valley. Mike joined Index Ventures in 2009, helping to establish the firm's San Francisco office which has become one of the largest parts of their business today. Mike invests primarily in infrastructure, open-source, and artificial intelligence companies and he's currently on the boards of Aurora, Cockroach Labs, Confluent, Elastic, Kong, Sonos, Starburst, Wealthfront, and Covariant. He has been involved in the funding of some of the biggest AI companies on the planet, so he knows more about the business of AI than practically anyone. In his chat with our host, Pieter Abbeel, Mike explains what a VC does, why VCs and investors should be so excited about AI in particular, and gives his advice for startups who want to get their big idea funded. Host: Pieter Abbeel | Executive Producers: Ricardo Reyes & Henry Tobias Jones | Audio Production: Kieron Matthew Banerji | Title Music: Alejandro Del Pozo See acast.com/privacy for privacy and opt-out information.

PHP Internals News: Episode 88: Pure Intersection Types London, UK Thursday, June 10th 2021, 09:16 BST In this episode of "PHP Internals News" I talk with George Peter Banyard (Website, Twitter, GitHub, GitLab) about the "Pure Intersection Types" RFC that he has proposed. The RSS feed for this podcast is https://derickrethans.nl/feed-phpinternalsnews.xml, you can download this episode's MP3 file, and it's available on Spotify and iTunes. There is a dedicated website: https://phpinternals.news Transcript Derick Rethans 0:14 Welcome to PHP internals news, a podcast dedicated to explaining the latest developments in the PHP language. This is Episode 88. Today I'm talking with George Peter Banyard about pure intersection types. George, could you please introduce yourself? George Peter Banyard 0:30 Hello, my name is George Peter Banyard. I work on PHP code development in my free time. And on the PHP Docs. Derick Rethans 0:36 This RFC is about intersection types. What are intersection types? George Peter Banyard 0:40 I think the easiest way to explain intersection types is to use something which we already have, which are union types. So union types tells you I want X or Y, whereas intersection types tell you that I want X and Y to be true at the same time. The easiest example I can come up with is a traversable that you want to be countable as well. So traversable and countable. Currently, you can do intersection types in very hacky ways. So you can either create a new interface which extends both traversable and countable, but then all the classes that you want to be using this fashion, you need to make them implement the interface, which might not be possible if you using a library or other things like that. The other very hacky way of doing it is using reference and typed properties. You assign two typed properties by reference, one being traversable, one being countable, and then your actual property, you type alias reference it, with both of these properties. And then my PHP will check: does the property respect type A those reference? If yes, move to the next one. It doesn't respect type B, which basically gives you intersection types. Derick Rethans 1:44 Yeah, I saw that in the RFC. And I was wondering like, well, people actually do that? George Peter Banyard 1:49 The only reason I know that is because of Nikita's slide. Derick Rethans 1:51 The thing is, if it is possible, people will do it, right. And that's how that works. George Peter Banyard 1:56 Yeah, most of the times. Derick Rethans 1:57 The RFC isn't actually called intersection types. It's called pure intersection types. What does the word pure do here? George Peter Banyard 2:05 So the word pure here is not very semantic. But it's more that you cannot mix union types and intersection types together. The reasons for it are mostly technical. One reason is how do you mix and match intersection types and union types? One way is to have like union types take precedence over intersection types, but some people don't like that and want to explicit it grouping all the time. So you need to do parentheses, A intersection B, close parentheses, pipe for the union, and then the other type. But I think the main reason is mostly the variance, like the variance checks for inheritance are already kind of complicated and kind of mind boggling. Derick Rethans 2:44 I'm sure we'll get into the variance rules in a moment. What is it actually what you're proposing to add here. What is the syntax, for example? George Peter Banyard 2:52 So the syntax is any class type with an ampersand, and any other class type gives you an intersection type, which is the usual way of doing and. Derick Rethans 3:01 When you say class types, do you also mean interfaces? George Peter Banyard 3:04 Yes, PHP has a concept of class types, which are mostly any class in any interface. There's also a weird exception where parent and self are considered class types, but those are not allowed. Derick Rethans 3:20 Okay, so it's just the classes that you've defined and the class that are part of the language but not a special keywords, self and parent and static, I suppose? George Peter Banyard 3:28 Yes, the reason for that is standard types are not allowed to be part of an intersection, because nothing can be an integer and a string at the same time. Now, there are some of the built in types, which can be kind of true. You could have a callable, which is a string, because callables can be arrays, or can be a closure. But that's like very weird and not very great. The other one is iterable. If when you expand that out, you get redundant types, which we can talk about later. And the final thing is parent, self, and static, just makes for some very weird design questions, in my opinion, like, if you ask for something to be an intersection with itself, you basically can only enforce conditions on subclasses. You have a class and you say: Oh, I want it to return self, but also be countable for some reason, but I'm not countable. So if you extend me, then you need to be countable, but I'm not. So it's very weird. parent has kind of the very same weird semantics where you can ask a parent, but it's like, if the base class doesn't support it, and you ask for a parent to be an intersection, then you basically need the child to implement the interface and then a child to return the first child. If you do that main question. Why? Because I don't see any good reasons to do it. And it just makes everything harder. Derick Rethans 4:40 You've only added for the sake of completeness instead of it being useful. Let's move on birds. You've mentioned which types are supported, which is class names and interface names. You already hinted a little bit at redundant types. What are redundant types? George Peter Banyard 4:56 Currently, PHP already does that with union types. If you repeat the type twice in a union, you'll get a compile error. This only affects compiled time known aliases. If you use a use statement, then PHP knows that you basically using the same type. However you use a runtime alias, then it can't detect that. Derick Rethans 5:13 A runtime alias, what's that? George Peter Banyard 5:15 So if you use the function class_alias. Derick Rethans 5:16 It's new to me! George Peter Banyard 5:18 it technically exists. It also doesn't guarantee basically that the type is minimal, because it can only see those was in its own file. For example, if you say I want A and B, but B is a child class of A, then the intersection basically resolves to only B. But you can only know that at runtime if classes are defined in different files. So the type isn't minimal. But if you do redundant types, basically, it's a easy way to check if you might be typing a bug. Derick Rethans 5:46 You try to do your best to warn people about that. But you never know for certain. George Peter Banyard 5:51 You never know for certain because PHP doesn't compile everything into like one big program like in check. Static analyser can help for that. Derick Rethans 5:59 Let's talk a little bit about technical aspects, because I recommend that implementing intersection types are quite different from implementing union types. What kind of hacks that you have to make in a parser and compiler for this? George Peter Banyard 6:11 Our parser has being very weird. The parsing syntax should be the same as union types. So I just copy pasted what Nikita did. I tried it. It worked for return types without an issue. It didn't work with argument types, because bison, which is the tool which generates our parser, was giving a shift reduce conflict, which basically tells: Oh, I got two possible states I can go in, and I don't know which branch I need to go, because the PHP parser only does one look ahead. Because it was conflicting, the ampersand, either for the intersection type or for to mark a reference. Normally, if the paster is more developed, or does more look ahead, it is not a conflict. And it shouldn't be. Ilia managed to came up with this ingenious idea, which is just redefine the ampersand token twice and have very complicated names, and just use them in different contexts. And bison just: now I have no issue. It is the same token, it is the same character. Now that you have two different tokens it manages to disambiguate, like it's shift produce. So that's a very weird. Derick Rethans 7:17 I'll have a look at what that actually does, because I'm curious now myself. Beyond the parser, I think the biggest and most complicated part of this is implementing the variance rules for these intersection types. Can you give a short summary of what a variance rules are, and potentially how you've actually implemented them? George Peter Banyard 7:38 Since PHP seven point four, return types and up covariant, and parameter types are contravariant. Covariant means you can like restrict, we can be more specific. And contravariance means you can be broader or like more generic. Union types already gives some interesting covariance implications. Usually, you would think, well, a union is always broader than a single type, you say: Oh, I want either a traversable or accountable, it seems that you're expanding the type sphere. However, a single type can have as a subtype, a union type. For example, you say,:Oh, my base type is a Class A, and I have two child classes, which are B and C. I can type covariantly that I want either B or C, because B or C is more specific than just A. That's what union types over there allows you to do. And the way how it's implemented. And how to check for that is you traverse the list of child types, and check that the child type is an instance of at least one of the parents types. An intersection by virtue of you adding constraints on the type itself will always be more specific than just a single type. If you say: Oh, I want a class A, then more specifically, so I want something of class A and I want it to be countable. So you're already restrict this, which gives some very interesting implications, meaning that a child type can have more types attached to itself than a parent type. That's mostly due how PHP implements its type system, to make the distinctions, basically, I've added the flag, which is either this is a union, meaning that you need to check it is part of one, or it's an intersection. The thing with intersection types is that you need to reverse the order in how you check the types. So you basically need to check that the parent is at least an instance of one of the child types, but not that none of the child types is a super type of the parent type. Let's say you have class C, which extends Class B and Class B extends Class A. If I say let's say my base type is B to any function, and I give something which is a intersection T, any interface, this would not be a valid subtyping relation to underneath B. Because if you looked it was a Venn diagram in some sense, you've got A which is this massive sphere, you've got B which is inside it, and C which is inside it. A intersection something intersects the whole of A with something else, which might also intersect with B in a subset, but it is wider than just B, which means like the whole variance is very complicated in how you check it because you can't really reuse the same loop. Derick Rethans 10:13 I can't imagine how much more complicated this gets when you have both intersection and union types in the same return type or parameter argument type. George Peter Banyard 10:22 One of the primary reasons why it's currently not in the RFC, because it is already mind boggling. And although I think it shouldn't be that hard to like, add support for it down the line, because I've already split it mostly up so it should be easy to check: Oh, is this an intersection? Is this a union? And then you need to branch. Derick Rethans 10:42 Luckily because standard types aren't included here, you also don't really have to think about coercive mode and strict mode for these types. Because that's simply not a thing. George Peter Banyard 10:50 That's very convenient. Derick Rethans 10:52 Is the future scope to this RFC? George Peter Banyard 10:54 The obvious future scope is what I call composite types, is you have unions and intersections available in the same type. The main issue is mostly variance, because it's already complicated, adding more scope to it, it's going to make the variance go even harder. I think with most programming languages, the variance code is always complicated to read. While I was researching some of it, I managed to hit a couple of failures, which where with I think was Julia and the research paper I was it was just like focusing on a specific subset. And like, basically proving that it is correct. It's not a very big field. Professors at Imperial, which I've talked to, have been kind of helpful with giving some pointers. They mostly work with basically proper languages or compiled languages, which have this whole other set of implications. Apparently, they have like a bunch of issues about how you normalize the types like in an economical form, to make it easier to check. Which is probably one of the problems that will need to be addressed, when you get like such a intersection and union type. First, you normalize it to some canonical form, and then you work with it. But then the second issue is like how do you want the composite types to actually be? Is it oh, you have got parentheses when you want to mix and match? Or can you use like union precedence? I've heard both opinions. Basically, some people are very dead against using Union as a precedent. Derick Rethans 12:14 My question is going to be, is this actually something people would use a lot? George Peter Banyard 12:21 I don't think it would be used a ton. The moment you want to use it, it is very useful. One example is with the PSRs, the HTTP interfaces. Or if you want the link interface. Combining these multiple things gets it convenient. One of the reasons why I personally wanted as well, it's for streams. So currently, streams don't have any interface, don't have any classes. PHP basically internally checks when you call like certain string methods. For example, if you try to seek and you provide a user stream, it basically checks if you implement a seek method, which should be an interface. But you can't currently do that. Ideally, you would want to stream maybe like a base class, instead of having like a seekable stream, and rewindabe stream, or things like that. You basically just have interfaces. And then like if somebody wants a specific type of stream, just like a stream, which is seekable, which is rewindable. And other things. We already have that in SPL because there's an iterator. And we have a seekable iterator interface, which basically just ask: Oh, this is there's a seek method. I think it depends how you program. So if you separate the many things into interfaces, then you'll probably use intersections types a lot. If you use a maybe a more traditional PHP code base, which uses union types a lot. Union types are like going to be easier. And you want to reduce that. Derick Rethans 13:32 Would you think that lots of people already use union types because it's pretty new as well. Isn't it? George Peter Banyard 13:38 Union types are being implemented in various different libraries. PSRs are updating the interfaces to use union types. One use case, I also have a special method, which was taken the date, it takes a union of like a DateTime interface, a string or an integer. Although intersections types are really new, you hear people when union types were being introduced, you heard people saying, I would promote bad cleaning habits, you shouldn't have one specific type. And if you're using a union, you have a design issue. And I had many people complaining to me why and intersection types of see? Why they haven't intersection types being introduced first, because intersection types are more useful. But then you see other people telling us like, I don't see the point in intersection types. Why would you use an intersection type, just use your concrete class, because that's what you're going to type anyway. Derick Rethans 14:21 I can give you a reason why union types have implemented first, over intersection types, I think, which is that it's easier to implement. George Peter Banyard 14:28 It's easier to implement. And it's more useful for PHP as a whole, because PHP functions accepts a union or return a union. Functions return false for error states instead of null. It makes sense why union types were introduced first, because they are mostly more useful within the scope of what PHP does. Derick Rethans 14:46 Do you think you have anything else to add about intersection types? At the moment, it's already up for voting, when is that supposed to end? George Peter Banyard 14:54 So the vote is meant to end on the 17th of June. Derick Rethans 14:57 At the moment I see there's 15 votes for and two against so it's looking good. What's been your most pushback on this? If there was any at all? George Peter Banyard 15:05 Mostly: I don't see the point in it. However, I do think proper reasons why you don't want it, compared to like some other features where it's more like have thoughts on what you think design wise. But it is undeniable that you you add complexity to the variance. And to the variance check. It is already kind of complicated. I have like a hard time reading it initially. There's the whole parser hackery thing, which is kind of not great. It's probably just because we use like a restricted parser because it's faster and more efficient. Derick Rethans 15:36 I think I spoke with Nikita about parsers some time ago and what the difference between them were. If I remember which episode it was all the to the show notes. George Peter Banyard 15:44 And I think the last reason against it is that it only accepts pure intersections. You could argue that, well, if you're adding intersections, you should add the whole feature set. It might impact the implementation of type aliases, because if you type alias T to be a union of A and B, and then you use type T in an intersection, you basically get a mixture of unions and intersections, that you need to be able to work with. The crux of this whole feature is the variance implementation. And being able to rationalize the variance implementation and been to extend it, I think it's the hardest bit. Derick Rethans 16:18 I guess the next thing still missing would be type aliases, right? Like names for types, which you can't define just yet, which I think you also mentioned in the RFC is future scope. George Peter Banyard 16:29 Yeah. Derick Rethans 16:30 Thank you, George, for taking the time today to talk to me about pure intersection types. George Peter Banyard 16:36 Thanks for having me on the show. Derick Rethans 16:41 Thank you for listening to this installment of PHP internals news, the podcast dedicated to demystifying the development of the PHP language. I maintain a Patreon account for supporters of this podcast as well as the Xdebug debugging tool. You can sign up for Patreon at https://drck.me/patreon. If you have comments or suggestions, feel free to email them to derick@phpinternals.news. Thank you for listening and I'll see you next time. Show Notes RFC: Pure Intersectio Types Episode #66: Namespace Token, and Parsing PHP GLR Parser LALR(1) Parser Iter Library Credits Music: Chipper Doodle v2 — Kevin MacLeod (incompetech.com) — Creative Commons: By Attribution 3.0

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 See acast.com/privacy for privacy and opt-out information.

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