22Astronauts

22Astronauts with Ilir Aliu
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The world was built by people not different from you. We interview founders, operators and engineers, to show you they're just like you. Hosted by Ilir Aliu.

  1. 5 天前

    Ep 103 | Why Robotics Hasn't Had Its ChatGPT Moment Yet (w/ Jiafei Duan)

    Dr. Jiafei Duan is a Presidential Young Professor at the ⁨National University of Singapore (NUS), Director of the MAGIC Lab (Manipulation and General Intelligence Control), and Research Scientist at A*STAR. Formerly a researcher at UW and the Allen Institute for AI (Ai2), Jiafei co-led the open-source "MolmoAct" and "MolmoAct2" robotics foundation models; action reasoning models designed to provide a transparent, fully reproducible alternative to proprietary "black box" physical AI systems. MAGIC Lab: https://magic-ailab.github.io/ RoboPapers Podcast: https://www.youtube.com/@RoboPapers Jiafei on X: https://x.com/DJiafei Ilir on X: https://x.com/IlirAliu_ Ilir on LinkedIn: https://www.linkedin.com/in/ilir-aliu/ Timestamps: 0:00 Why true robotics progress requires radically open science 1:45 The RoboPapers podcast: Asking the hard research questions 3:34 Building my first mobile manipulator from PVC pipes at 16 7:19 The Leap Motion epiphany: Controlling plywood with Arduino 10:15 Writing the survey that introduced "Embodied AI" to Singapore 14:55 Why Singapore is investing heavily in physical intelligence 21:36 Moving from cognitive science to robotics at UW with Dieter Fox 24:51 AR2-D2: Collecting robot manipulation data using AR & inpainting 28:41 The PhD shift: Learning how to think and communicate science 32:49 Why robotics isn't ready for industry to consolidate yet 39:11 Vision researchers are migrating to ICRA: The field is shifting 41:26 Running open VLA models on a $200 SO-100 hobbyist robot 46:38 Leaving Ai2: The philosophy behind fully open data and weights 50:52 Launching the MAGIC Lab at NUS: Finding efficient model architectures 54:36 Why robotics won't have its ChatGPT moment without open source

  2. 7月23日

    Ep 102 | Why Humanoids Won’t Be in Our Homes Anytime Soon (w/ Majid Khadiv)

    My conversation with Prof. Dr. Majid Khadiv, Head of the ATARI LAB (Applied and Theoretical Aspects of Robot Intelligence) and Assistant Professor at TUM (the Technical University of Munich). The ATARI Lab focuses on AI planning in dynamic environments, bridging optimal control with modern foundation models to make general-purpose humanoid robots safe, adaptable, and truly autonomous. ATARI Lab: https://ce.cit.tum.de/en/aipd/ Majid on LinkedIn: https://www.linkedin.com/in/majid-khadiv-a92a2a62/ Ilir on X: https://x.com/IlirAliu_ Ilir on LinkedIn: https://www.linkedin.com/in/ilir-aliu/ Timestamps: 0:00 Building national humanoids in Iran without resources 2:11 Why playing soccer beats being a tech kid 3:03 How my sister proved you can break through the entrance exam 5:10 Thinking deeply about a single math problem for five hours 7:02 Visualizing physics: Why Newtonian mechanics just clicked 8:38 Why traditional schooling fails curious minds 10:50 Should AI tutors replace the classroom experience? 18:48 Discovering the intersection of control and dynamics in robotics 20:30 Building the Surena III humanoid from scratch with PhD students 23:44 Honda's Asimo vs our 98kg robot: The engineering reality 26:01 How the 2015 DARPA Robotics Challenge humbled everyone 28:55 Why grades don't reflect true deep-thinking ability 34:01 How Ludovic Righetti transformed my research mindset at Max Planck 37:09 The price to pay for staying at the forefront of academia 52:19 Why general purpose humanoids are the holy grail 58:26 The hand is the pinnacle of human intelligence 62:03 Fusing language models with evolutionary search for physics planning 64:27 Why safety and OOD cases will keep humanoids out of homes for years 70:19 Advice to my younger self: Have confidence in your curiosity

    Ep 102 | Why Humanoids Won’t Be in Our Homes Anytime Soon (w/ Majid Khadiv)

  3. 7月15日

    Ep 101 | Investing $19M in Humanoids with Zero Robotics Experience (w/ Andrew Kang, RoboStrategy)

    Andrew Kang is the Co-Founder and CEO of ⁨RoboStrategy⁩ and Managing Partner of Mechanism Capital. RoboStrategy already holds concentrated positions in industry-defining companies including ⁨Figure AI, ⁨Apptronik, ⁨Standard Bots⁩, and Dyna Robotics. It is the first publicly listed vehicle purpose-built to give investors liquid exposure to private robotics and physical AI giants, applying the MicroStrategy capital-markets playbook to automation. RoboStrategy: https://www.robostrategy.ai Andrew on X: https://x.com/Rewkang Andrew on LinkedIn: https://www.linkedin.com/in/rewkang/ Ilir on X: https://x.com/IlirAliu_ Ilir on LinkedIn: https://www.linkedin.com/in/ilir-aliu/ Timestamps 0:00 Why we built a public fund for private robotics 0:35 Building the MicroStrategy for robotics 1:22 Escaping the tiger parent trap 2:11 Video games are elite training for game theory and critical thinking 6:30 Learning arbitrage in RuneScape and Neopets 7:59 Don't believe experts just because of their titles 10:24 Why investing is just a video game with real money 12:40 Harvard nutrition professors don't know what they're talking about 18:48 Recreating global finance from first principles 19:57 Why robotics is the early days of crypto all over again 21:50 Realizing humanoids are no longer sci-fi 22:58 Why I wrote a $19M check when every VC told me not to 27:24 How SPVs are democratizing venture investing 30:55 Bet on the founder and their execution speed, not the pitch deck 36:39 The math behind a $50 trillion physical labor market 41:44 Applying the MicroStrategy playbook to private markets 45:48 Humanoids are the GPUs of physical labor 47:48 Building a new SoftBank for the robotics era 50:51 Why robotics startups need engineers for attention 54:35 Don't be satisfied with surface level answers

  4. 2月18日

    Ep 100 | You Need To Be 10x Better (w/ Evan Beard)

    Evan Beard is the co-founder and CEO of Standard Bots, building AI-trained industrial robot arms designed to automate real factory work, not demos:In this episode, Evan shares a founder path that started in software startups and Y Combinator long before robotics. Seeing engineers at YC building giant robots convinced him this was a “cheat code on life” and he taught himself mechanical and electrical engineering to make it possible  We talk about the early years spent building prototypes in a small apartment, running more than one hundred calls with manufacturers, and discovering the same problem every time. Companies wanted automation, but robots were too expensive and too difficult to program  Evan explains why Standard Bots focuses on usable automation instead of chasing hype. The goal was not a slightly better robot but something ten times easier to deploy, trained through demonstration and physical AI rather than complex programming  We also discuss surviving the near-death phase, raising funding weeks before running out of money, rebuilding electronics during the chip shortage, and learning electrical engineering while debugging exploding circuit boards remotely  A conversation about persistence, customer obsession, and why the future of robotics will be decided by real ROI on factory floors, not humanoid spectacle.

  5. 2月12日

    Ep 99 | You Can’t Be What You Can’t See (w/ Grace Brown)

    Grace Brown is the founder and CEO of Andromeda, building social companion robots designed for aged care and healthcare environments: In this episode, Grace shares a founder journey that started long before a company existed. She had been building robots since her teenage years, but the real motivation appeared during COVID lockdowns. People in care facilities were physically supported, yet emotionally isolated. The goal became simple. Build a robot people actually want around them. We talk about learning outside the curriculum, reaching out to mentors early, and running long real-world pilots before the product was ready. Instead of waiting for perfection, Andromeda deployed unfinished systems into nursing homes to understand behavior, trust, and human reaction. Grace explains why the hardest problem in social robotics is not intelligence but comfort. A robot can function technically and still fail if people feel uneasy around it. Design, personality, and interaction determine adoption more than raw capability. We also discuss building a company as a young founder, hiring commercial leadership early, and how moving into the US startup ecosystem changed the pace of decisions and iteration. You don't want to miss this one!

  6. 2月4日

    Ep 98 | Discipline Is a Transferable Skill (w/ Camilla Mazzoleni)

    Camilla Mazzoleni is the co-founder and Chief Product Officer of FORGIS, a Zurich-based startup building an AI operating layer for industrial automation: In this episode, Camilla shares a founder journey shaped long before robotics. She grew up as a competitive alpine skier, leaving home early to train at elite level. Discipline, pressure, and repetition defined her daily life. Losing was normal. Learning how to reset and keep going became second nature. After an injury ended her professional sports career, that same intensity moved into engineering. Camilla talks about discovering robotics through building, not theory. Working on factory floors, programming robots across vendors, and seeing firsthand how slow and fragmented industrial automation really is. We talk about how Forgis came to life at ETH Zurich. Why hardware is not the bottleneck in factories. Why software fragmentation is. And how Forgis sits on top of existing systems as a hardware-agnostic, edge-based AI layer that upgrades how factories operate instead of tearing them apart. A great conversation about discipline, switching paths, and why Europe’s manufacturing future depends on intelligence, not replacement.

  7. 1月29日

    Ep 97 | Why Robotics Keeps Rebuilding the Same Infrastructure (w/ Stephen James)

    Stephen James is the founder and CEO of Neuracore, and Assistant Professor of Robot Learning at Imperial College London: In this episode, Stephen shares his path from growing up in Wales to spending a decade at Imperial, a postdoc at Berkeley, and eventually founding Neuracore. Not because he wanted to be a startup founder, but because he kept running into the same problem again and again: every robotics team rebuilding the same infrastructure from scratch. We talk about what actually slows robotics teams down, why data pipelines matter more than clever algorithms, and how Neuracore aims to become the infrastructure layer that lets teams focus on deployment instead of plumbing. Stephen also reflects on imposter syndrome, work ethic, moving between academia and industry, and why Europe can and should build its own robotics infrastructure instead of copying Silicon Valley playbooks. A very honest conversation about building foundations, not hype, and why scaling robotics is mostly about removing friction.

  8. 1月22日

    Ep 96 | Talent Didn’t Save Me, Consistency Did (w/ Steve Xie)

    Steve Xie is the founder and CEO of Lightwheel AI, building the simulation and synthetic data layer powering the next generation of embodied AI and humanoid robotics. In this episode, Steve shares a rare founder journey that starts far from robotics. From studying physics at Peking University, struggling to stand out, and rebuilding confidence through sheer consistency, to a PhD at Columbia and an early failed startup built out of love for his dog. A detour that taught him the cost of building without a business model. We talk about his path through Cruise, NVIDIA, and NIO, where he led large-scale simulation efforts for autonomous driving. Steve explains how those years shaped his conviction that simulation, data quality, and evaluation are the real bottlenecks in physical AI. He then breaks down how Lightwheel AI came to life. Why sim-ready assets matter more than solvers. How synthetic data actually closes the sim-to-real gap. And why robotics teams hit a ceiling without proper evaluation and scaling infrastructure. A deep conversation about resilience, delayed gratification, and why the hardest part of building is often unlearning what made you successful before.

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簡介

The world was built by people not different from you. We interview founders, operators and engineers, to show you they're just like you. Hosted by Ilir Aliu.

資訊

  • 創作者
    22Astronauts with Ilir Aliu
  • 活躍年代
    2024年 - 2026年
  • 集數
    103
  • 年齡分級
    兒少適宜
  • 版權
    © 22Astronauts with Ilir Aliu
  • 節目網站
    22Astronauts

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