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. 2d ago

    Ep 110 | Your Factory Data Is Lying to You (w/ Silviu Homoceanu, CTO Almetra)

    Almetra is turning the perception stack from self-driving cars into factory intelligence. I sat down with Silviu Homoceanu, Co-Founder & CTO of Almetra, to talk about growing up with computers in post-communist Romania, eight years inside VW's self-driving programme, and why the data most factories run on doesn't describe what actually happens on the line. Silviu learned programming by translating English menus on his father's work PC, was selling self-built accounting software at 15, and came to Germany for a PhD in machine learning. He joined VW Group Research in 2014 and spent the next eight years on perception for autonomous driving, before a question from a manufacturing colleague sent him into factories for seven months. Today, Almetra (formerly Deltia) combines computer vision, sensors and machine data to show how production actually runs instead of how it was planned. The company raised a $19M Series A led by blisce/ in June 2026 and is opening an office in Boston. We cover why factory data is often wrong, what happens when the MES reports a reality that isn't real, the 100% defect detection problem, why so many robotics startups get stuck in pilot purgatory, what reliability really means on a running line, and Almetra's move from measuring manual work to automating parts of it. Silviu Homoceanu: https://www.linkedin.com/in/silviu-homoceanu-893b7a5 Almetra: https://www.almetra.ai/ 𝐒𝐏𝐎𝐍𝐒𝐎𝐑 - CoreWeave — The Essential Cloud for AI. CoreWeave sponsors this podcast. Join CoreWeave at #FullyConnected: https://coreweave.com/fully-connected-2026/agenda 👉 Free code: FCLR26 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 00:00 Meeting at the AI Campus in Berlin 00:47 Who Silviu is and what Almetra does 02:44 Romania after 1989 and his father's first PC 06:08 A 286 at home, MS-DOS, then Linux 08:04 Running a computer business at 15 10:21 High school nights in the computer lab 14:44 The mentor who said: study abroad 16:15 Flipping burgers to see the MIT campus 18:58 Romania vs Germany: theory against practice 20:23 First job: cluster computing for bridge simulations 26:20 Why computer networks stopped being enough 28:00 The exam answer that led to a PhD offer 30:47 Percentages or factors: how he picks problems 36:20 VW Research comes knocking in 2014 39:05 The meeting with manufacturing that changed everything 39:52 Seven months in factories: the data is wrong 40:30 Merantix, meeting Max, and founding the company 42:08 The Goal, bottlenecks, and life on a shop floor 43:31 The 100% defect detection problem 46:14 When the MES reports a reality that isn't real 48:09 Automating stations and the robotics angle 49:33 99.999% and why factories say no to startups 52:47 What is actually automatable today 55:07 The Series A, blisce/, and the move to Boston 59:21 Closing Follow 22Astronauts: Newsletter: 22astronauts.com LinkedIn: https://www.linkedin.com/company/22astronauts Instagram: https://www.instagram.com/_22astronauts_/

  2. Sep 16

    Ep 109 | Inside Almond: The $8,999 Physical AI Robot (w/ Saba Khalilnaji)

    Almond is building robots for the era of physical AI. I sat down with Saba Khalilnaji, Founder & CEO of Almond, inside the company's San Francisco factory to talk about building robots, scaling hardware, factory automation, and why Almond wants to become "America's robot factory." Saba started building robots as a kid, later spent nearly seven years at DoorDash, and eventually left to work on one of the hardest problems in automation: getting robots to operate reliably in factories where the environment and tasks constantly change. Today, Almond is building Axol, a dual-arm robot designed for physical AI, data collection, teleoperation and real-world deployment. We cover why traditional automation struggles in high-mix manufacturing, what Saba learned from DoorDash, the rise of "neo-integrators," why deployments are Almond's North Star, manufacturing robots in San Francisco, and Almond's work on teaching Axol to help build Axol. Saba Khalilnaji: https://www.linkedin.com/in/saba-khalilnaji/ Almond: https://www.almond.bot/ 𝐒𝐏𝐎𝐍𝐒𝐎𝐑 • CoreWeave — The Essential Cloud for AI. Join CoreWeave at Fully Connected in San Francisco, bringing together the people building the next generation of AI infrastructure and applications. Learn more: https://www.coreweave.com/fully-connected-2026 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 00:00 Inside Almond's San Francisco robot factory 01:02 A first look at Axol 02:12 Building robots as a kid 07:50 Science Olympiad and early robotics 11:56 Studying bioengineering at Berkeley 14:58 From robotics to DoorDash 18:19 What DoorDash taught Saba about moving fast 22:37 Why he left to start a company 25:10 How your environment shapes ambition 29:28 Discovering the automation problem inside factories 31:06 Why traditional factory automation struggles 34:49 What Almond is building 36:03 The rise of the "neo-integrator" 38:36 Why deployments are Almond's North Star 40:17 Building America's robot factory 43:09 Why Almond believes in owning the full stack 44:05 Teaching Axol to help build Axol 46:09 Saba's advice to his younger self 47:25 Why it's called Almond 49:25 Closing Follow 22Astronauts: Newsletter: 22astronauts.com LinkedIn: https://www.linkedin.com/company/22astronauts Instagram: https://www.instagram.com/_22astronauts_/

  3. Sep 10

    Ep 108 | AI Is Inventing Hardware Humans Can't Design (w/ Prof. Mario Krenn, Feyer)

    Prof. Mario Krenn is the Scientific Director & Co-Founder of Feyer GmbH and Professor for Machine Learning in Science at the University of Tübingen, where he leads the Artificial Scientist Lab. For over a decade, Mario’s research has focused on using AI not just to analyze physics data, but at a conceptual level; building AI explorers that discover completely novel experimental setups, optics, and quantum hardware. In July 2026, alongside CEO Jonathan Klimesch and CTO Sören Arlt, he co-founded Feyer GmbH: a frontier AI lab for automated physical invention. As one of only 10 European teams selected for SPRIND's €125M Next Frontier AI Challenge (€3M non-dilutive seed phase), Feyer couples neural explorers with ultra-fast, differentiable physics simulators. Their mission is to autonomously invent next-generation industrial hardware (from advanced microscopy and lasers to lithography and quantum sensors) scaling Europe's high-tech manufacturing strengths. Feyer GmbH: https://feyer.ai Mario Krenn: https://mariokrenn.wordpress.com Ilir on X: https://x.com/IlirAliu_ Ilir on LinkedIn: https://www.linkedin.com/in/ilir-aliu/ Timestamps: 0:00 "AI that invents industrial hardware": What is Feyer GmbH? 3:08 How the Cyber Valley ecosystem turned an academic researcher into a founder 5:43 Growing up in Austria: Programming operating systems at age 10 11:31 Stephen Hawking, mysteries of space, and choosing physics over engineering 15:01 Joining Anton Zeilinger's lab in Vienna: "What is the next to the next step?" 18:33 March 2014: Writing a program to design a quantum experiment humans couldn't solve 21:58 Finding solution.txt & the realization that computers can be creatively scientific 28:28 Moving to Toronto & Vector Institute: Learning AI material discovery from Alán Aspuru-Guzik 34:49 Returning to Europe & building the Artificial Scientist Lab in Erlangen & Tübingen 37:47 Asking questions to the universe: Why physics experiments are fundamental 43:35 Breaking resolution limits in microscopy & applying AI to industrial high-tech 45:49 Winning SPRIND's Next Frontier AI Challenge & founding Feyer GmbH 47:25 Scaling European hardware strengths: Semiconductor, photonics, and optics leadership.

  4. Sep 3

    Ep 107 | "We Don't Retrain Models, We Teach Them Cause & Effect" (w/ Johannes Haux)

    Johannes Haux is the Co-Founder & CEO of kausable (Heidelberg, Germany), a deep-tech AI startup building reasoning-first causal foundation models. Instead of memorizing internet-scale text patterns or relying on millions of trial-and-error attempts, kausable’s models (based on the Prior-data Fitted Network / PFN approach) learn abstract cause-and-effect structures from synthetic data—enabling them to adapt to entirely new physical environments in-context from just a handful of examples. After working in computer vision under Prof. Björn Ommer at Heidelberg University (alongside the future Black Forest Labs founders) and serving as Head of AI at AskUI, Johannes co-founded kausable with Dr. Benjamin Herdeanu (CTO) and Gregor Ramien (COO). The company recently raised a €12M seed round led by UVC Partners and Entourage, backed by top-tier angels from OpenAI, DeepMind, Black Forest Labs, and Neura Robotics. kausable: https://kausable.ai Johannes on LinkedIn: https://www.linkedin.com/in/jhaux/ Ilir on X: https://x.com/IlirAliu_ Ilir on LinkedIn: https://www.linkedin.com/in/ilir-aliu/ Timestamps: 0:00 Building foundation models in the Cyber Valley deep-tech ecosystem 1:25 Working in Prof. Ommer’s lab & meeting the future Black Forest Labs team 3:48 Early startup lessons at Sysmagine & AskUI 4:09 Why internet-scale LLMs aren't enough for general-purpose physical intelligence 4:52 Discovering Prior-data Fitted Networks (PFNs) & founding kausable 7:00 "I was a bad student": Why structure and habits matter more than raw talent 12:19 Wanting to be a movie director before choosing physics at Heidelberg 18:37 Quitting academia right before COVID lockdowns & taking the entrepreneurial leap 27:38 Why community & ecosystem matter for European deep-tech startups 29:26 How humans actually learn vs. brute-force reinforcement learning in robotics 32:01 In-context learning: Adapting to distribution drift & new sensors without retraining 33:47 TipPFN & predicting critical transitions: Seizures, blackout risks, and physical dynamics 37:37 Michael Black's perspective: Why Europe is a strong launchpad for disruptive AI 41:37 Exploratory tech vs. concrete customer problems: Making the "faster horses" bet 47:17 Moving from a research lab to early design partners 50:36 "Don't fake it, but think big": Advice for European deep-tech founders

  5. Aug 20

    Ep 106 | "There Is Zero ROI in Home Humanoids" (w/ Nic Radford)

    Nic Radford is the Co-Founder & CEO of Persona AI (Houston, TX) and former Founder/CEO of Nauticus Robotics (NASDAQ: KITT) & Lead of NASA’s Robonaut 2 and Valkyrie humanoid programs. With nearly 30 years of experience building humanoid robotics (from human-rated space manipulation at NASA Johnson Space Center to subsea autonomous robots) Nic brings a veteran, unfiltered perspective to the commercial humanoid market. Together with Co-Founders Dr. Jerry Pratt (CTO, ex-IHMC & Figure AI) and Jide Akinyode (COO, ex-NASA & Nauticus), Persona AI is building modular industrial humanoids for heavy, labor-constrained industries. Rather than chasing general-purpose home helpers or $15/hr warehouse sorting, Persona targets skilled industrial trades—starting with autonomous welding humanoids for shipbuilding in partnership with HD Hyundai and POSCO. Persona AI: https://persona.ai/ Nic on LinkedIn: https://www.linkedin.com/in/nicolaus-radford/ Ilir on X: https://x.com/IlirAliu_ Ilir on LinkedIn: https://www.linkedin.com/in/ilir-aliu/ Timestamps: 0:00 Why the commercial humanoid robotics market has it completely wrong 3:17 Growing up in rural Indiana & fixing mechanics out of necessity 5:31 Decathlon, severe arthritis & learning "tenacity squared" as a founder 8:16 CB radios, 286/386 PCs, and entering the early Internet at Purdue 12:35 The 2000 Wired cover that sparked a 30-year humanoid obsession 15:23 Getting lost at NASA JSC and stumbling upon Robonaut 1 23:18 Camping in the Texas desert: Building amateur rockets during the early SpaceX era 25:25 Why networking is the lifeblood of deep tech partnerships 28:00 Storytelling for VCs: Why presentation skills are learned, not innate 30:50 From 15 years at NASA (Robonaut 2 & Valkyrie) to becoming an entrepreneur 35:47 Taking space tech underwater: Building Aquanaut & taking Nauticus public on NASDAQ 36:41 Partnering with Jerry Pratt to start Persona AI 37:36 Why general-purpose "Me-Too" robots face an ROI dead end 38:37 Targeting skilled trades: Why shipbuilding and heavy industry need humanoid welders 41:46 GM assembly lines & the brutal reality of automotive cycle times 44:42 The home humanoid myth: "Can we all just stop this? There is zero ROI." 48:34 First-time founders vs. Veteran founders: Tech obsession vs. Cash flow & GTM 49:50 Raising a $42M pre-seed & closing a $100M+ seed round 51:20 Delivering humanoid welders to HD Hyundai in 24 months 52:35 "Look what we built in 90 days": Calling out fake startup timelines

  6. Aug 13

    Ep 105 | Red Tape Cost Us a 5-Year Lead in Humanoid Robotics (w/ Jan Peters)

    Prof. Dr. Jan Peters is Full Professor of Intelligent Autonomous Systems at TU Darmstadt, Department Head of Systems AI for Robot Learning (SAIROL) at DFKI, and a Founding Research Faculty Member of hessian.AI. With over 54,000 Google Scholar citations, Jan is one of the world’s most influential robot-learning pioneers; having co-developed foundational algorithms like Natural Actor-Critic, REPS, and Probabilistic Movement Primitives (ProMPs). IAS Lab: https://ias.informatik.tu-darmstadt.de Jan's Website: https://www.jan-peters.net Ilir on X: https://x.com/IlirAliu_ Ilir on LinkedIn: https://www.linkedin.com/in/ilir-aliu/ Timestamps: 0:00 Combining machine learning with physical robotics before it was cool 4:05 Studying 4 Master’s degrees & dodging the German military draft 8:27 Why DLR and ATR in Japan were lightyears ahead of German universities 12:37 Meeting Kawato, Chris Atkeson, and Stefan Schaal in a bamboo forest 17:10 Turning down Stanford and CMU for a smaller lab at USC 21:46 How double-blind reviews leveled the academic playing field 23:44 Injecting physical mechanics into reinforcement learning 26:01 How 9/11 permanently shifted American culture and optimism 29:40 Returning to Max Planck: The "monastery" era of AI research 35:14 Why being authentic & speaking your mind wins long-term respect 44:01 Surviving hostile German hiring commissions in the 2000s 47:55 Why TU Darmstadt became Europe’s secret powerhouse for physical AI 57:39 High-speed table tennis, juggling, and the limits of robot perception 58:32 Raising €2M for humanoids and fighting 4 years of European bureaucracy 65:49 German red tape vs. American risk-taking: What's holding Europe back? 68:33 Why TU Darmstadt rivals top US universities in AI breadth

  7. Aug 6

    Ep 104 | How to Train 99.9% Reliable Robots for $5 (w/ Igor Kulakov)

    Igor Kulakov is the Co-Founder and CEO of MicroFactory (SimpleAutomation, Inc.), a San Francisco-based robotics startup building autonomous "factories-in-a-box" for precision electronic assembly. Backing their bet that tabletop manufacturing cells beat humanoids for real-world reliability, MicroFactory is backed by Naval Ravikant and Hugging Face CEO Clément Delangue, using continuous human teleoperation feedback loops to reach near-100% precision. MicroFactory: https://microfactory.com Igor on X: https://x.com/ihorbeaver Ilir on X: https://x.com/IlirAliu_ Ilir on LinkedIn: https://www.linkedin.com/in/ilir-aliu/ Timestamps: 0:00 Why we don't need humanoid robots for tabletop assembly 2:24 Inspired by "Back to the Future": Building pinball machines and telescopes at 15 6:30 Creating indie games and viral social media apps for 1M daily users 11:40 The pain of physical hardware: Running a wedding light startup in Ukraine for 9 years 21:16 Moving to San Francisco to be at the frontier of physical AI 32:06 Discovering the problem: Why hardware startups struggle with assembly 36:18 The viral photo frame demo that launched MicroFactory at Founders, Inc. 39:38 Why big AGI labs ignore precision and 99.9% reliability 43:07 Beyond pure data collection: Why reinforcement learning damages hardware 45:00 Human-in-the-loop DAgger: Correcting errors on Jetson Nano for $5 per retraining 52:15 Positive ROI vs. perpetual demos: Why shipping matters 62:41 Advice to founders: Change your environment if your experiments aren't working

  8. Jul 30

    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

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About

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.

Information

  • Creator
    22Astronauts with Ilir Aliu
  • Years Active
    2024 - 2026
  • Episodes
    110
  • Rating
    Explicit
  • Copyright
    © 22Astronauts with Ilir Aliu
  • Show Website
    22Astronauts

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