Podcast
22Astronauts
Hosted by 22Astronauts with Ilir Aliu · EN
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.
14episodes
Episodes
Newest firstAll episodes
Ep 102 | Why Humanoids Won’t Be in Our Homes Anytime Soon (w/ Majid Khadiv)
6d ago01:11:31Tap to summarizeMy 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 resources2:11 Why playing soccer beats being a tech kid3:03 How my sister proved you can break through the entrance exam5:10 Thinking deeply about a single math problem for five hours7:02 Visualizing physics: Why Newtonian mechanics just clicked8:38 Why traditional schooling fails curious minds10:50 Should AI tutors replace the classroom experience?18:48 Discovering the intersection of control and dynamics in robotics20:30 Building the Surena III humanoid from scratch with PhD students23:44 Honda's Asimo vs our 98kg robot: The engineering reality26:01 How the 2015 DARPA Robotics Challenge humbled everyone28:55 Why grades don't reflect true deep-thinking ability34:01 How Ludovic Righetti transformed my research mindset at Max Planck37:09 The price to pay for staying at the forefront of academia52:19 Why general purpose humanoids are the holy grail58:26 The hand is the pinnacle of human intelligence62:03 Fusing language models with evolutionary search for physics planning64:27 Why safety and OOD cases will keep humanoids out of homes for years70:19 Advice to my younger self: Have confidence in your curiosity
Transcribe →Ep 101 | Investing $19M in Humanoids with Zero Robotics Experience (w/ Andrew Kang, RoboStrategy)
2w ago00:55:49Tap to summarizeAndrew 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.aiAndrew on X: https://x.com/RewkangAndrew 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/Timestamps0:00 Why we built a public fund for private robotics0:35 Building the MicroStrategy for robotics1:22 Escaping the tiger parent trap2:11 Video games are elite training for game theory and critical thinking6:30 Learning arbitrage in RuneScape and Neopets7:59 Don't believe experts just because of their titles10:24 Why investing is just a video game with real money12:40 Harvard nutrition professors don't know what they're talking about18:48 Recreating global finance from first principles19:57 Why robotics is the early days of crypto all over again21:50 Realizing humanoids are no longer sci-fi22:58 Why I wrote a $19M check when every VC told me not to27:24 How SPVs are democratizing venture investing30:55 Bet on the founder and their execution speed, not the pitch deck36:39 The math behind a $50 trillion physical labor market41:44 Applying the MicroStrategy playbook to private markets45:48 Humanoids are the GPUs of physical labor47:48 Building a new SoftBank for the robotics era50:51 Why robotics startups need engineers for attention54:35 Don't be satisfied with surface level answers
Transcribe →Ep 101 | Why I Bought a $25k Robot Arm for My New York Apartment (w/ Elliot Horowitz, Viam)
3w ago00:54:06Tap to summarizeEliot Horowitz is the Founder and CEO of Viam and Co-Founder of MongoDB. Viam is building the universal software platform to bridge the gap between AI and physical hardware, running everything from automated boat-sanding systems to AI sonar fleet operations. Viam: https://www.viam.comEliot on X: https://x.com/elliothorowitzIlir on X: https://x.com/IlirAliu_Ilir on LinkedIn: https://www.linkedin.com/in/ilir-aliu/Timestamps:0:00 The early days of 20 megabyte hard drives1:18 Writing video games on a Radio Shack computer at age five6:24 Rockets, airplanes, and why software is the hardest part of hardware9:03 The power of iteration velocity11:35 Becoming an entrepreneur by accident: MongoDB15:00 Product vs. utility: Why MongoDB won19:10 Stepping down and tinkering in the COVID era22:41 Why I bought a $25k industrial robot arm for my New York apartment28:28 Taking a big swing: Building a universal platform34:16 From an idea to 1,000 production robots41:00 Why trying to build both hardware and software is a trap43:53 Real world deployments: Tooling for operators vs technologists47:02 The power of dogfooding coffee and salad robots in the office49:16 How LLMs will actually code the future of robotics52:14 It’s not about the product, it’s about the outcome53:36 Why nobody spends enough time on education
Transcribe →Ep 100 | You Need To Be 10x Better (w/ Evan Beard)
Feb 1800:57:21Tap to summarizeEvan 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.
Transcribe →Ep 99 | You Can’t Be What You Can’t See (w/ Grace Brown)
Feb 1200:52:47Tap to summarizeGrace 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!
Transcribe →Ep 98 | Discipline Is a Transferable Skill (w/ Camilla Mazzoleni)
Feb 401:01:40Tap to summarizeCamilla 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.
Transcribe →Ep 97 | Why Robotics Keeps Rebuilding the Same Infrastructure (w/ Stephen James)
Jan 2900:56:35Tap to summarizeStephen 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.
Transcribe →Ep 96 | Talent Didn’t Save Me, Consistency Did (w/ Steve Xie)
Jan 2201:08:18Tap to summarizeSteve 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.
Transcribe →Ep 95 | The Hard Part Is Not Training Robots. It Is Making Them Generalize (w/ Animesh Garg)
Jan 1400:59:54Tap to summarizeI talk with Animesh Garg,Assistant Professor at Georgia Tech and one of the leading voices in robot learning today:We talk about growing up in India, building his first autonomous vehicle on a $280 budget after being rejected from a CMU program, and how that failure pushed him toward Berkeley, Stanford, and eventually NVIDIA Research. Animesh shares why he avoided computer science early on, what drew him to mechatronics, and how curiosity rather than planning shaped his entire career.ORBIT and Isaac Lab, why simulation is now the backbone of robot learning, and how world models, reinforcement learning, and foundation models are lowering the barrier for people outside robotics to build real systems. Animesh explains why he believes the most important robotics breakthroughs will come from people who are still in high school today.A deeply personal conversation about grit, risk, redefining success, and why chasing interesting problems beats chasing money.
Transcribe →Ep 94 | What Made Us Strong Is Now Holding Us Back (w/ Marco Huber)
Jan 800:54:10Tap to summarizeIn this episode, I talk with Prof. Dr. Marco Huber, Professor for Cognitive Production Systems at the University of Stuttgart and Scientific Director for AI at Fraunhofer IPA.Marco shares his journey from a middle-class upbringing with no academic role models to becoming a leading figure in applied AI for manufacturing. We talk about discovering computer science through a single physics teacher, why he almost went to vocational school, and how a mix of personal drive and mentors shaped his path.We spend some time on his years between academia and industry, what he learned working in high-pressure startups, and why real innovation happens when theory meets factory floors. Marco explains how Germany still leads in fundamental AI research but is at risk of losing the race when it comes to turning research into scalable industrial products.A conversation about explainable AI, robotics in production, and why Europe has only a small window left to turn Physical AI into a competitive advantage.
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