22Astronauts

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.

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

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

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

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