Techically a member of staff @Machenta_
London
Joined August 2026
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Owain Thorp retweeted
How someone reacts to this demo from a technical perspective exposes how much they actually know about robotics
You can now book our humanoid cleaners on a recurring subscription, for up to 3 hours per cleaning at tau-robotics.com.
Video is first take, uncut, shown at 4× speed. See the reply for detailed footage at 1× speed.
We don't overfit to certain hardware at Machenta!
Instant Robot Learning at @Machenta_ also works on SO-101 robots! Physical Vibe Coding at home.
By the way, we're now hiring for somebody to come and build a thriving Machenta community with us around our model: tinyurl.com/9a25j7jv.
This is going to be fun!
Translation: no one used dots and opus 5.5 means no one is using codex
Day 25/
We are doubling all usage limits for all Pro 100/200/500 tiers and Business Premium, effective today.
We heard your kind feedback and won’t be reducing usage limits for Pro 200, so your Work and Codex usage will stay the same. We’re also going to continue offering extended limits for dots for now, and usage of your dot will still continue to be separate from your default usage.
And we'll of course also keep shipping better models and other efficiency improvements that increase your effective usage over time.
Owain Thorp retweeted
Videos like this, to me, really show the future. It's a ways off still, but this is what a "real world" claude should look like -- a guy can unpack his robots, show them a task, and get them doing something useful basically right away, even though they can't be fully trusted on their own yet.
We’ve built a one-shot, one-person factory!
We taught a robot assembly line using Instant Robot Learning at @Machenta_.
Normally, this would take weeks of system integration, but it took us two minutes to teach.
See the video below 👇
Three different bimanual robots are collaborating on a packaging task. All three robots:
• Have different camera setups.
• Were taught using different teaching modes.
But they all run the same end-to-end model.
The model has never seen these objects before. It was trained 100% in simulation, and these objects were not in the simulation.
I was also asked about this one-person factory at @MTSlive. Check out our conversation below!
Super exciting and important role!
What might happen when anyone can teach a robot any new task in just a minute? We're looking for someone to help us find out.
At @Machenta_, we're now hiring for a really unique, creative, and exciting role: our Community Lead.
You're going to be building a new community around our Instant Robot Learning model, from the bottom up. Just imagine what a robotics hackathon might look like when you can teach robots instantly, and all the creative ways people will use our model now that we're enabling "Physical Vibe Coding".
You'll fully own our community approach, from strategy to execution — whether you're building relationships with developers, creating online content and tutorials to showcase our model, or organising events and hackathons.
This is a hands-on role, ideal for someone energetic and creative who's excited about being an external ambassador for Machenta, whilst working closely with us all in person in London. Although you're not expected to be a robot learning expert, you'll need to have a good understanding of the robotics and AI space, and you should be excited to learn about our technology well enough to talk about it with confidence.
To learn more, visit machenta.com/team. See you there!
And please share with anybody who might like to see this. It's going to be perfect for the right person!
Owain Thorp retweeted
Machenta is hiring! 🤖
We just raised a $40M seed led by Creandum & USV to build robots that learn a new task from one demo.
We're a small, talent-dense team in London, and everyone owns their work end to end. Sound like you? machenta.com/team
Machenta is hiring!
Following our $40M seed round, we are looking for the brightest minds in robotics and machine learning who want to work in a high-velocity, high-agency team. Come and join us if you're the very best! machenta.com/team
This is so cool
I've always believed that intelligence should come from simple, general building blocks that learn their own abstractions directly from raw data; in other words, the bitter lesson. I think we're finally seeing a real step towards AI that can learn from all data.
Language modeling on raw bytes is a microcosm of this ideal, and to me it's a central problem in AI: if we can't build LLMs that learn end-to-end from bytes, how will we handle the rest of the world's data that we understand even less?
Last year we introduced hierarchical networks (H-Nets) as a first step. Our new version finds up to 3-5x efficiency gains in controlled scaling law experiments, and at larger scale matches an open-source model trained on 11T tokens with ~10x less data and compute. The posts below walk through what we found and why we think it works.
Owain Thorp retweeted
Google strategically shipped Carbon before OpenAI and Anthropic drop their next gen monsters
I think they are still ~2 months behind
Owain Thorp retweeted
One-Shot, One-Person Factory with Instant Robot Learning.
We’ve built a one-shot, one-person factory!
We taught a robot assembly line using Instant Robot Learning at @Machenta_.
Normally, this would take weeks of system integration, but it took us two minutes to teach.
See the video below 👇
Three different bimanual robots are collaborating on a packaging task. All three robots:
• Have different camera setups.
• Were taught using different teaching modes.
But they all run the same end-to-end model.
The model has never seen these objects before. It was trained 100% in simulation, and these objects were not in the simulation.
I was also asked about this one-person factory at @MTSlive. Check out our conversation below!
Owain Thorp retweeted
We’ve built a one-shot, one-person factory!
We taught a robot assembly line using Instant Robot Learning at @Machenta_.
Normally, this would take weeks of system integration, but it took us two minutes to teach.
See the video below 👇
Three different bimanual robots are collaborating on a packaging task. All three robots:
• Have different camera setups.
• Were taught using different teaching modes.
But they all run the same end-to-end model.
The model has never seen these objects before. It was trained 100% in simulation, and these objects were not in the simulation.
I was also asked about this one-person factory at @MTSlive. Check out our conversation below!
Machenta CEO @Ed__Johns explains how his team automated an entire assembly line in just 2 minutes, something that normally takes weeks or months:
"I decided I wanted to automate an entire assembly line. We put three robots side by side and created a task where the robots would package a box and then close the box, and each robot would do a different part of that task."
"I thought it’d be really cool if we could automate that whole thing in about two minutes, because traditionally automating an assembly line would take weeks or maybe even months of systems integration and manual programming. It’d be extremely expensive."
"If we could get instant robot learning working on an entire assembly line, this would be evidence of what the future of the manufacturing industry would look like."
"That’s one of my favorite tasks, an entire assembly line automated in two minutes."
@Machenta_
Owain Thorp retweeted
Quick video showing some of the "Reactivity & Recovery" capabilities of Instant Robot Learning at @Machenta_:
1. One real demonstration: putting blue object in grey box and closing box.
2. Robot reacts in real time when object and box are moved around, with a closed-loop end-to-end policy.
3. Robot recovers when object is pulled out of gripper, and re-grasps it.
4. Robot notices that object is removed from box, and places it back in.
5. Robot notices that box lid is opened, and re-closes it.
The important part:
1. None of this reactivity and recovery needed to be shown in the demonstration: it all comes from the intelligence of the pre-trained model.
2. Model has never seen these objects before. It is trained 100% in simulation, and these objects were not in the simulation.
machenta.com/blog/instant-ro…
Owain Thorp retweeted
This government is obviously VERY keen to attract the highest-quality global talent.
One of the more interesting announcements in the budget was the expanding of the "High Potential Individual visa"
The aim is to:
"to support the world’s best scientists and engineers to come to work in UK industry"
NICE
The UK budget is in. Here's everything you need to know:
🇬🇧 No exit tax or increase in capital gains
🇬🇧 Brand new "founder’s relief” - 10% tax up to £10m lifetime gains and BADR thresholds cut by half
🇬🇧 The non-compete ban we already knew about, but slightly more fleshed out
🇬🇧 The additional AI money, which we already knew about, but in more detail
🇬🇧 Some very important changes to visas to attract better talent to the UK
🇬🇧 £5bn for BBB including more money to back female founders
🇬🇧 "Young Entrepreneurs Allowance" which covers living costs for young entrepreneur
I have probably missed some bits but overall this is a lot more pro-tech and pro-entrepreneur than I think people were expecting.
Great stuff from @adepledge, @Dom_Hallas and all those working tirelessly behind the scenes to advocate for a strong entrepreneurial economy here in the UK.
LETS GO
Owain Thorp retweeted
It‘s becoming obvious that large-scale data collection is a dead end for robotics. LLM training was the wrong reference.
Today we’re out of stealth, and we’ve raised a $40m seed round co-led by @creandum and @usv, to bring Instant Robot Learning to life.
For the past few months, we‘ve been busy building a new company.
Machenta.
This follows results from a new kind of robot foundation model we’ve built, which I’m so excited to share with you today!
Usually, it takes hours/days of data collection and training to teach a robot.
We’ve built a model that learns tasks instantly: one demonstration, no further training.
A model trained entirely in simulation, without a single pixel of real-world data.
A model where teaching robots is so quick and easy, it feels like physical vibe coding.
A model for robots that learn like humans do, from someone like you.
Welcome to the era of Instant Robot Learning.
Thank you @Kathi_Wilhelm, @rebeccakaden, @hkanji, @jonno_evans and all of our angels for your support!
@Machenta_
Learn more: machenta.com/blog/instant-ro…
See below for what you can do with Instant Robot Learning!
Owain Thorp retweeted
Thanks @MTSlive for the chat last night about Instant Robot Learning! Here's a little clip about why we're excited at @Machenta_ to be building AI for robots that learn instantly.
Machenta CEO @Ed__Johns reveals how betting against the robotics industry's approach led his team to build robots that learn new tasks instantly from just one demonstration:
"I decided what I wanted to build is a robot brain that can learn tasks like a human. And the rest of the world went off in a different direction."
"They started collecting lots and lots of data in the real world, with the assumption that you would need to provide hundreds of demonstrations."
"I always thought there’s something not quite right about that, where a robot would need to spend hours or days to learn a task. That’s what I bet on at Imperial College."
"The internals of it are nothing like the human brain. But the way you interact with it is like interacting with a human."
"If I wanted to teach you a task, I could give you a demonstration, and you’d be able to do that task. You wouldn’t need hundreds of demonstrations, and you wouldn’t need days or weeks of training."
"You provide one demonstration of the task, and then instantly the robot will be able to perform that task. Which is very different to what’s been going on elsewhere in robotics, where the assumption has been that you need lots and lots of data to teach a robot even a basic task."
@Machenta_