Brenda (@librendaa072) header
Brenda (@librendaa072) profile picture
New York, NY
Joined May 2023
Photo by Brenda (@librendaa072)Photo by Brenda (@librendaa072)Photo by Brenda (@librendaa072)Photo by Brenda (@librendaa072)Photo by Brenda (@librendaa072)Photo by Brenda (@librendaa072)Photo by Brenda (@librendaa072)Photo by Brenda (@librendaa072)Photo by Brenda (@librendaa072)Photo by Brenda (@librendaa072)
Brenda retweeted
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. 🧵
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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 :)
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Brenda retweeted
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.
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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.
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Brenda retweeted
hosting an 8 hr learning hackathon this sunday in sf. dm if you're interested:)
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Brenda retweeted
fruit fly made a 5 leg parlay! elite ball knowledge
fruit fly brain placing parlays on prediction markets via @totalistrading
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Today we introduce Kairos 1: the world's first model built to simulate individual human behavior. Frontier models only understand population averages, ignoring the individual differences that make us human. Kairos beats Persimmon, Astra, Fable, and Gemini across 13 simulation benchmarks.
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New research from Team Shard & @jasminexli! AIs increasingly fake good behavior, which might ruin our ability to evaluate models. We trained models to be 𝘦𝘷𝘢𝘭-𝘤𝘰𝘰𝘱𝘦𝘳𝘢𝘵𝘪𝘷𝘦: to want to give evaluators accurate info. This surfaces hidden misalignment! 🧵
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Brenda retweeted
if you're deploying robots somewhere ill give you compute, ill put a check in and will help you raise
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A Waterloo engineer turned my polygon idea garden into the actual Waterloo park 🤯 Should I merge this into Iwantwaterloo.com?
In the spirit of bringing a canada.gov type of website together, I'm starting in Waterloo and helping make iwantwaterloo.com This is the new design I've built up with @TheMingjie Thoughts?
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are you a Waterloo student who interned at Palantir? Anduril? did they try to keep you? we want you more: let's talk. we're looking for students who can bring the frontier of defence to Canada. we want deep technical depth and substantial work. wherever you got that, we want to see it. the team already includes people who have: - been interning in SF since 14 - spent 7+ years doing robotics - USAMO qualifier & USACO Platinum - first-authored at NeurIPS - accumulated too many hackathon wins to count we raised significant funds days after launching and are in talks with some of the largest defence contractors in the world. Apply below ;)
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I want to host UW’s Physical AI hackathon, called “How To Train Your Robot”. Looking for roboticists, graphic designers, and general help - dm if you want to learn more!
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Introducing Palatial Mad Max, a state-of-the-art parametric generation agent that unlocks scalable Real2Sim for robotics and physical AI. It's a generalized agent that can create extremely detailed SimReady assets with precise articulated parts and grounded physics properties designed for dexterous manipulation tasks. Try it now at dashboard.palatial.cloud (1/4)
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Brenda retweeted
A year ago, I entered the world of robotics through a hackathon that me and @librendaa072 did. despite knowing nothing, i enjoyed the experience of building a hardware project immensely more than any of my software ones (immediately regretted picking CS instead of Tron) after one hardware hack came another, and then another. All while me and Brenda hosted events across Canada and the US. our revelation? we can’t wait for humanoids, but we also couldn’t imagine them—in their current state, smoothly integrating into society. perhaps this can be solved in the way we know best: events... but this time, to *also* capture social data. want a spot at our next event? leave a comment or DM us :)
What used to be sci-fi a year ago is swiftly becoming a reality. Robotics companies around us are racing to create the first, deployable robot into human society. Training is continuously evolving in the age of physical AI, and it won’t be long before clanker friends join us in our homes, in our hospitals, and everyday life. In 2035, 13M of walking robots in society are expected to be humanoids. It’s time to teach these robots how to play, and interact in our society. Introducing: Interplay For years we’ve hosted events for the people. Somewhere along the way, startups and companies picked up on going IRL as the new method for building trust, creating community, recruiting, and advertising products. Interplay is creating an entirely new category of events: those curated to bring out the best in humanity… carefully designed to train the best social robots. Want to teach them? Leave a comment or DM us to grab a spot at our next event :)
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Brenda retweeted
Space has raised a $2.4M pre-seed to give your computer infinite storage. Today teams lose hours each week downloading files before humans and agents can begin working. Space removes the wait. Every file, instantly accessible while using zero disk space. – at San Francisco, CA
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The Bracket Bot team is full of competitive roboticists who are not phased by other companies with $1B funding rounds and accolades. We all crushed teams with 50x more funding in our competitive robotics days. In hardware engineering, perception is not reality. Best robot will win, and we are building the best robot.
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Brenda retweeted
actually, jk the Akatos team is in London, Canada supporting the Alchemy demo day at @momentum_place! @realfigmafiend and @ella_schlags owning the stage :)
Last night, we closed off Symposium week by bringing the Pixar lamp to life. Akatos guest @SarkaryShahvir and the @humancomplab team assembled and tested LeLamps at our house. Waterloo, Socratica, and the world… what a week, thank you for everything.
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Brenda retweeted
CANADA IS IN THE WORLD CUP KNOCKOUTS! And we’re all gonna watch it at @akatoshouse Join us tomorrow!
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Brenda retweeted
We’re joining YC S26 :) Pre revenue, no Ivy leagues, first time founders YC flew us out for an interview with 5 partners at once Follow me, @victorvannara, @trope_ai to see why they bet on us
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Brenda retweeted
Want to see distributed computing explained via Pong? Inspired by TinyTPU and TinyTapeout workshop at FOSSi, I wrote a paper under a week pairs this demo with a proposed next-gen optical I/O chip architecture & a roadmap to prototype it. Read it on GitHub: github.com/llhtimlam/tt_um_l…
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