Cleaning robots are real. Greeter robots are real. Anything with an arm is not, at least not as a product you can buy and trust to work unsupervised.

Prof. Dr. Yulia Sandamirskaya said it precisely: nobody in the world has yet dared to leave a robot with a manipulator doing real work in a care facility and then gone to bed. That is the line between a demo and a product, and the industry has not crossed it.

She is a professor at ZHAW, the Zurich University of Applied Sciences, where she leads the Centre for Cognitive Computing in Life Sciences, and she is spinning a company out of her lab to bring robots into elderly care. So this is not scepticism from the sidelines.

We get into neuromorphic computing and why a fruit fly performs acrobatics on roughly 100,000 neurons and almost no power. Then the line that reframes everything: your eye is sharp across only about two degrees and jumps three times a second, so the steady scene in front of you is 95% imagination. Intelligence, she argues, is closer to how many things you can imagine at once than to how much data you collected.

She is blunt about AGI. It has been almost here since the Dartmouth summer school in 1956, and bigger static models do not close the gap. She makes the case against humanoids on legs, because a robot on stairs is a hazard to everyone near it, and describes a Neuraverse where robot skills work like apps.

Her team toured a care home, ended up in the staff room, and she asked a caregiving team leader almost as a joke why he needed robots at all. He paused, then started listing, and she had to get her notebook out. The people who will work beside the machine know where the real bottlenecks are.

She also explains why the business model has to be robot as a service rather than a purchase, and tells the story of her grandmother in Belarus, living alone and refusing help, which is the actual reason she is building this.

We just started a TechDrive Zürich WhatsApp group. Every episode the moment it lands, behind the scenes, the bloopers that did not make the cut, and updates straight from the guests themselves.

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When Kateryna Portmann was a kid in Ukraine, she asked her parents for a robot every time they travelled. They could never find one, so she got dolls instead. She works in robotics now, as Senior Product Manager at ANYbotics, and she runs the Women in Robotics Society.

Her route there was not a straight line: international business, an executive MBA, consulting, a PhD in Hong Kong she could not finish, then a startup where a language barrier pushed her towards numbers and into product management. She landed in robotics in 2019, for a reason that never shows up on a CV. Her sister has cerebral palsy and used neurorehabilitation devices, which is how she found the company that made them.

The core of this conversation is what actually breaks a robot deployment. Assume the robot works perfectly. It has been simulated, tested and deployed correctly. Then people leave a ladder in the corridor, prop open the door that has to stay shut, and walk the stairs while the robot is on them. The machine is rarely the hard part. The building, the workflows and the people are.

In this episode:

• Why the robot is usually the easy part of a deployment
• Nobody wants another interface, and what that means for integration
• Robot ready, facility ready, organisation ready, and why all three have to line up
• The gap between three robots and a hundred, and why most pilots never cross it
• Why almost nobody has twenty years of mobile robotics experience, and why that helps
• Compliance running behind the technology, and building safe by design anyway
• Moving from brownfield sites today to greenfield in three to five years
• How to get into robotics now, and what these companies are actually hiring for
• Serving a population that is half women with teams that are twenty to thirty percent

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About the guest: Kateryna Portmann is Senior Product Manager at ANYbotics, working on robots for hazardous zones and critical infrastructure, and runs the Women in Robotics Society. She was previously at Hocoma in neurorehabilitation robotics.

About the show: TechDrive Zürich is a series of candid, in-car conversations with the people building technology in and around Zürich, hosted by Justinas Mišeikis.

▶ Watch the video version on YouTube: https://youtu.be/uvoba2PyXEQ

🔗 Guest: https://www.linkedin.com/in/katerynaportmann/

🔗 Women in Robotics Society: https://www.linkedin.com/company/women-in-robotics-switzerland

🔗 ANYbotics: https://www.anybotics.com/

🔗 TechDrive Zürich: https://techdrivezurich.lovable.app/

🔗 Hosted by Justinas Mišeikis: https://www.linkedin.com/in/justinasmiseikis/

For the first time on TechDrive Zürich there are two guests in the car!

Katka Letzing and Anna Hakobyan co-initiated Swiss {ai} Weeks, five weeks of AI events running across Switzerland from 1 September into early October, with more than 200 partners and more than 200 events behind it. We recorded two weeks before it opened.

It takes about twelve months to build, and they start the week after the previous one ends.

Most of the conversation is about restraint rather than acceleration. Anna explains why generating ten pages of a document in two minutes does not mean you should, and what happens when the person receiving it summarises it with AI. Katka explains why leading with AI stopped being impressive the moment everyone started doing it. Both of them describe the shift away from large frontier models toward smaller specialised ones, and the gap between organisations that pilot and organisations that scale.

They are also unusually direct about themselves. Katka says she handles negotiation and diplomacy because she was trained to negotiate in war zones, then says in the next breath that the technical side is not her strength. Anna talks about taking ego out of a project you care about, and admits that asking for help is the part she still works on.

And one number worth sitting with: partner organisations taught 6000 children about AI, and then those children went back to classrooms where the teachers had not had the same training.

In this episode:• Why they built a movement instead of a programme• Coming in with the mindset of an experiment• From Czechoslovakia and the UN to Zürich• Why organisations backed this with no direct business return• What people keep getting wrong about Apertus• Why smaller specialised models are winning• AI consciousness, and generating less• Whether hackathons actually go anywhere

⏱️ Chapters

00:00 Two guests, two weeks to go

01:44 It takes 12 months to build five weeks

02:54 Why a movement and not a programme

04:21 Come in with the mindset of an experiment

05:35 Katka: Czechoslovakia, Silicon Valley, Kickstart

07:46 Anna: the UN, Montreal, New York, tech

10:34 What each of them brings to the team

11:29 Taking ego out of the equation

13:29 Getting partners on board

14:32 They backed it with no direct business link

15:03 Why this works in Switzerland16:18 What would make this year a success

17:22 6000 kids, and the teachers who were not ready

18:41 Where AI is actually heading

19:42 The Apertus misunderstanding

20:51 Away from the frontier models

21:53 Ten pages in two minutes

22:55 AI does not make you cool any more

23:43 Do hackathons actually go anywhere

24:47 How to take part

Join exclusive WhatsApp Group: https://chat.whatsapp.com/JgGidD8SqsuFzohXvZmo5z

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Swiss {ai} Weeks: https://ai-weeks.ch/

Katka Letzing: https://www.linkedin.com/in/katkaletzing/

Anna Hakobyan: https://www.linkedin.com/in/annahakobyan/

More of TechDrive Zürich: https://techdrivezurich.lovable.app/

Watch the video version on YouTube: https://youtu.be/mS4hiMQVwpk

TechDrive Zürich is hosted by Justinas Mišeikis:

https://jmiseikis.lovable.app/

You have probably seen the videos of a robot rallying against a real table tennis player. This episode is about the five years, and the team, behind it.

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In this TechDrive Zürich drive, Mireille El Gheche shares a path that starts with electrical engineering in Lebanon, runs through a master's in radio communication in Paris, a PhD in optimisation, a postdoc in machine learning in Bordeaux and a stint at EPFL, and lands at Sony AI. The recruitment was unusual: nobody would tell her what the project was. They sent her two research papers, one on computer vision and one on table tennis from DeepMind, and let her connect the dots.

She guessed right, joined as a team lead on reinforcement learning, and ended up leading 10 engineers and researchers on a problem that had not been solved before.

The technical heart of the conversation is the gap between a system that works in simulation and a machine that has to survive the real world. Every component worked on its own. Making them work together, in real time, against a fast spinning ball, is where the five years went. Or as Mireille puts it: in the digital world you can reset and restart, but in the real world the physics does not forgive you, and if you are late by a few milliseconds the ball is already gone.

In this episode:

• Getting recruited for a secret project with two research papers and no details
• Why the 80/20 rule breaks down when nobody knows the solution yet
• Research team and engineering team, working in parallel for five years
• The real bottleneck: making every component work together on a real robot
• Why building a robot is fundamentally different from building an AI system
• How the sim-to-real gap narrowed over five years, and why it will never fully close
• What technical leadership actually demands: clarity, trust across disciplines, and making different voices heard

• Going from individual contributor to leading 10 people, and learning to let go
• Where robotics is heading, from care and industry to self-driving cars and drones
• Would she be the patient for a fully autonomous surgical robot?
• Women in Robotics, and why whoever builds the future shapes the future
• Studying engineering in Lebanon in a class that was almost 50/50

About the guest: Mireille El Gheche is a robotics and machine learning researcher who led the reinforcement learning team on Sony AI's table tennis robot project, and is an active participant in the Women in Robotics community.

About the show: TechDrive Zürich is a series of candid, in-car conversations with the people building technology in and around Zürich, hosted by Justinas Mišeikis.

Most offices are clean, quiet, and a little boring. Stefan Zimmer built the opposite. In this episode of TechDrive Zürich, I drive through Zürich with Stefan, employee number one at FlexOffice and the head of DARE Campus.

FlexOffice started in 2018 with nothing but an idea and four laptops. Today it is the biggest serviced-office provider in Switzerland, with 11 locations and around 30,000 square meters of space. DARE Campus is Stefan's boldest bet yet: a home built on purpose for deep-tech and robotics startups, with raw concrete, no fancy double floors, and big rooms where teams can get a little wild with heavy hardware.

We also get into how an office company survived a COVID home-office mandate, the day a humanoid robot ran through the campus, the one piece of office tech everyone secretly hates, and why the "far away" neighbourhood of Schlieren is actually nine minutes away by train.

⏱️ Chapters
00:00 Welcome
01:15 From four laptops to Switzerland's biggest
02:05 From 15 years in nightlife to running an office
03:02 Where the name came from: Join, Explore, DARE
03:52 Why the campus is all raw concrete
05:07 Taking the distractions away from founders
06:53 Building a community, not just renting desks
08:22 How the model changed, and surviving COVID
10:30 A humanoid robot running through the campus
12:37 The office tech everyone secretly hates
13:39 Who DARE Campus is for
15:46 Is Schlieren really that far? The 9-minute playlist
16:04 Events, hackathons and knowledge sharing
17:28 Wrap-up

💡 A few takeaways

• Start small, think big: four laptops became Switzerland's largest serviced-office provider in under a decade.
• Build for your user, not for looks: raw concrete and big rooms beat polished floors when customers bring robots.
• Remove the friction: founders do their best work when someone else handles the boring stuff.
• A crisis can be an accelerator: when offices were "banned," FlexOffice leaned into flexibility and came back stronger.
• Community is the real product: people come for the space, but they stay for the people.

🎁 Special offer for builders
DARE Campus has space open right now, from a single desk to hundreds of square meters of maker space. Mention "TechDrivePodcast" when you sign for a desk or a space, and your first month is completely rent-free. If you work in robotics, deep-tech, or AI and want room to get a little wild, this one is for you.

Join exclusive WhatsApp Group: https://chat.whatsapp.com/JgGidD8SqsuFzohXvZmo5z

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🔗 Connect
Guest: Stefan Zimmer - https://www.linkedin.com/in/stefan-zimmer-flexoffice/

DARE Campus: darecampus.ch

FlexOffice: flexoffice.ch

TechDrive Zürich - hosted by Justinas Mišeikis - https://techdrivezurich.lovable.app/

🎧 Also available on YouTube

#TechDrive #Zürich #Switzerland #robotics #deeptech #startups #FlexOffice #DARECampus #makerspace #innovation

What turns brilliant Swiss research into a company the world actually wants? This episode of TechDrive Zürich is a driving conversation with Raffael Kellner, who has spent six years at VentureLab / Venture Kick - the programs behind roughly 80% of Switzerland's innovation-based startups.

Raffael shares his own path (business school → the startup scenes of Slovakia and Vienna → a failed app startup → consulting → VentureLab), then unpacks what he looks for when a scientist wants to commercialize their work. The recurring theme: mission comes first - "the key thing is to know that you want it" - and everything else can be taught.

In this episode:

• Why a PhD is surprisingly good preparation for startup life - "you've already learned how to suffer"
• The mindset flip from research perfectionism to startup "good enough, and easy to scale"
• Why you must validate demand before you build
• The data behind the method: an ~84% success rate for completed Venture Kick projects
• Switzerland's "unfair advantage" - world-class IP and an ecosystem that's international from day one
• The blind spot: the world's growth is shifting to Asia, and why founders should learn those markets
• A wow-moment from China's "dark factories," where robots - not cheap labour - build (self-driving) cars
• What Raffael would build if he started a startup today, and the values that would guide it

About the guest: Raffael Kellner works at VentureLab / Venture Kick, supporting Switzerland's most promising deep-tech and innovation-driven startups from first idea to global markets.

About the show: TechDrive Zürich is a series of candid, in-car conversations with the people building technology in and around Zürich - hosted by Justinas Mišeikis.

Join exclusive WhatsApp Group: https://chat.whatsapp.com/JgGidD8SqsuFzohXvZmo5z

You'll get sneak peek into upcoming guests, behind the scenes and more.

▶ Watch the video version on YouTube: https://youtu.be/X6pt5X9Z0-M

🔗 VentureLab: venturelab.swiss • Venture Kick: venturekick.ch

🔗 Guest: https://www.linkedin.com/in/raffaelkellner/

In this episode of TechDrive Zurich, I’m taking a drive with deep tech executive and venture partner, Dr. Robert MacKenzie (Ellipsis Ventures, former C-level at ANYbotics, Hocoma, Labster).We dive into what it actually takes to get robotics out of the lab and into the real world. We discuss the transition from flashy demos to achieving "boring reliability", the 99.999% dependability required for industrial scaling. Robert shares insights from his experience scaling ANYbotics into a global player, and breaks down what investors are truly looking for in the next generation of AI and robotics startups.As always on TechDrive, we explore these complex topics while navigating the streets, blending high-level strategy with real-world execution.Three things stuck with me:

1. In deep tech, "if you build it, they will come" is rarely true. Robert's warning is premature commercialization. Chasing revenue with a product that isn't finished. His fix is to stop treating real-world deployments as expensive guesswork ("osmosis," as he calls it, basically put an expensive robot out there and hope you learn something) and turn them into a tight, conscious learning loop that feeds straight back into the product. Build the value first and the adoption follows.

2. The robotics correction is coming. It's a planning signal, not a reason to panic. He's predicting a corrective dip in early 2027 as the hype meets reality and investment cools. His practical advice to Zürich robotics founders was blunt: if you want to raise, raise in 2026. He's not anti-humanoid, but they "do amazing movements with zero understanding of the movements they're doing." The near future is a mixed fleet of specialized robots, not one humanoid doing everything.

3. Founders, especially researchers, shouldn't lose their superpower. Scientists are masters of the learning loop: form a hypothesis, don't know the answer, find a way. But once a spin-off finds one solution that works in the lab, the loop often stops, and they fall in love with it. Keep that loop running in the real world and it's a game-changer. His related, honest note: don't default to CEO/CTO because the title is romantic, but take the role that's best for the company. Sometimes that means letting someone else drive.Subscribe for more in-car conversations with the leaders shaping the future of tech, AI and robotics!

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He started his career teaching trains to catch their own failures before they happened. Now he does the same for founders.

Nikos Kaliorakis, president of J Floor, joins TechDrive for a drive through Zurich. We get into leaving Greece, the jump from fixing machines to backing people, and why he's set on keeping young builders in Zurich instead of losing them to London or San Francisco.

Plus what J Floor actually is, and what it refuses to be: no coworking space, no accelerator, no equity, no fees. Just founders helping founders.

No stage, no script. Just an honest conversation in a moving car.

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Tech chat with Nelija Mišeikienė