
building @abstractpbc. prev. maths @uwaterloo, @contrary, @longdotxyz
New York, NY
Joined May 2023
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Great builds are to come…
Great people are inside…
Great ideas come from within.
@akatoshouse x @BDC_Capital x @Canada x @HackTheNorth x @cansbridgeproj ❤️
Robots are getting better at completing tasks. But what happens when they make a mistake?
We fine-tuned π₀.₅ on two real-world manipulation tasks to showcase whether recovery demonstrations can improve policy reliability more effectively than additional successful demonstrations. 🧵
Brenda retweeted
started WaterlooAGI
we do experiments, evals, and research about AGI from different directions
my first experiment was on noisy vs structured corruption on LLM dreaming
looking for researchers to exchange ideas and sponsors with spare compute. dm me 🔎
links below :)
I've spent years in China building robots. I can tell you this playbook won't work:
Pre-seed $: Invent the ultimate actuator.
Seed $$: Figure out mass production.
The hard part isn't inventing a beautiful topology. It's process engineering.
The real delta between the US and China is the ability to execute the enormous amount of physical x mental work required to iterate thousands of times on product designs and manufacturing processes. Partly because much of the tacit knowledge / management systems has left the US, but also because of the sheer human labor required.
This isn't something you can solve by buying traditional automation lines either. It requires:
1. Ideation driven by human intuition. Walking up and down the line, talking to assembly workers, and developing hypotheses about what and where improvements can be made. Raw human hours and attention spent understanding a specific manufacturing process.
2. Large batches of experiments across multiple variables. Coordinating experiments that can easily involve 50+ people, issuing instructions, and tracking the execution and results of each experiment.
3. Purpose-built test design to identify key metrics. For example, a change in gear hobbing profile might require accelerated aging tests on a dyno, while a change in bearing tolerance might require NVH testing.
4. Data + human intuition-driven analysis. Interpreting test results and deciding whether to implement a process change or run the next set of experiments.
5. Strict process control. Reissuing work instructions to the line and ensuring every process is followed to the letter.
The best manufacturers in Asia, from Foxconn to TSMC, have built their competitive advantage on systematically turning thousands of physical experiments into better manufacturing processes.
Their moat isn't just production scale. It's the organizational machinery that makes manufacturing learn and improve faster than anyone else.
I don't think most people in SF clock this.
Say you're manufacturing actuator gears in-house in the US. After you've made your first article, will you hire a team of 10 process engineers to coordinate the 50 technicians running concurrent experiments with designs, processes, and materials?
To understand wear patterns across every pin in a cycloidal drive after 10,000 hours? To reduce backlash from 15 arcmin to 5, then to 1? Just to keep pace with China's progress over the next few years?
Do you have the skill set and management systems in place to do this?
That's why our approach isn't just to automate manufacturing. It's to automate the process of learning how to manufacture better.
Automate simulation and design optimization.
Automate assembly and physical testing.
Automate the design and execution of process experiments.
Feed real-world experimental data back into simulation to continuously improve sim-to-real accuracy.
The goal is to turn what currently takes 50 engineers coordinating thousands of experiments into a closed-loop system that continuously learns and improves.
Then the same robotic line mass-manufactures the product.
PS: Coming back to actuator design, many actuator designs are already commoditized in China. The project in the video is open source, and CNC machining cost in China is just $27 (watch the video).
I hope people understand this reality. I'll link more examples in the replies.
Brenda retweeted
The billion dollar raise isn't even the most exciting part about this announcement
Replying to @flappyairplanes
We’ve developed the world’s most complete megakernel framework. It can perform entire training runs, serve inference, play video games, and even do all three simultaneously in a single kernel.
Come by and meet very interesting people.
Whether you’re working on LLMs in a lab, ex-lab, or building your stealth company.
Good connections are made every single time.
Private event. Select attendance only.
Thanks for posting @arankomatsuzaki! I look forward to seeing you there.
Robotics research meetup happening at SF tomorrow night!
Enjoy pizzas and papers :)
luma.com/ud78bwvv
love it, we all use slashy ;)
Today we're launching @slashyemail for Outlook.
Slashy is the new era of email, the era where everyone gets their own assistant, and is now open to anyone who's still unfortunate enough to be on Microsoft 365
Some things outlook beta users used Slashy for include:
- Sorting important emails from noise (after all outlook's spam filter sucks)
- Drafting replies that sounded like them instead of GPT slop
- Handling scheduling end-to-end (including timezones, and reschedules)
- Prepping them before every call
Set it up in 5 minutes and start saving 2 hours a day at slashy.com
Coming to sf during tech week, crashing with @RastinRassoli, @KCarol_Amor, Shiv, Igor, @quantbagel and others was eye-opening.
Huge thank you to @veer_ukrani and @slashapp for sponsoring our sf popup house.
Thanks to @budwindruid, @McCauley (sorry can't find your handle, @scotthsutw1, @MiniUlisse and many others for coming all the way to Daly for a dinner we threw with 1h notice.
We
- built a green robot with Derek;
- attended an event sponsored by @PalatialSim and chatted with a Berkeley researcher about tactile data;
- watched atlas' unveiling;
- ingested papers on inference and social robotics data in the most delicious french cafe; scheming
- visited the most beautiful grocery store with Seungmin and another Derek @simantic and got treated to delicious conveyor belt sushi; and
- bumped delightfully into @NaomiWalch on the plane here; and jumped in the ocean with @quantbagel, @RastinRassoli and @KCarol_Amor (would recommend)
and much more...part 2 coming along. – at San Francisco, CA
Come ‘round to our house tonight :).
Shoutout to the homeboys at @slashapp and @veer_ukrani. Beautiful folks, always supporting Waterloo and founder community.
Expect…us to ask you uncomfortable questions.
Building robots.
Talking about fine-tuning an open-source model and distilling Astra
yo @liquidcompute are you building compute for the moon i wanna do that





















