deep tech research | embodied agi, world models, math
Joined February 2026
- Tweets 486
- Following 3,170
- Followers 323
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25 Photos and videos
Our team is unreal.
- AI and Robotics Researcher at a Top Robotics Startup in Europe, IMC Prosperity 4 Top Percentile and Founder of a Startup affiliated with Founders, Inc. Zerobase and Various Race Teams around Asia and Europe.
- EECS Researcher at UC Berkeley, Worked with Labs sponsored by Microsoft, experience at Morgan Stanley and Boston Common Asset Management
- Physics Researcher at UCLA Henry Samueli School of Engineering and Applied Science, worked with top Chinese Universities, experience in Optiver programs and Open Source Contributor to different Quant Repos including Tauric Research's Trading Agents (77.9K Stars)
- Ex Researcher at The University of Tokyo, ikegami lab, MSc Maths at Indian Institute of Science Education and Research (IISER), Pune, ex. Indian Institute of Technology, Madras, Winners List for Emergence AI's Hackathon
- Ex Researcher at Caltech, IMC Prosperity 4 Top Percentile, Professional Quant Researcher and ex High Energy Physics Researcher
- Researcher, Quant Intern and MSc Quant Finance at Georgia Institute of Technology, experience in GreenSky®, Goldman Sachs, Strike (YC W25), and DLR Group | Collins Cooper Carusi Architects
We are currently looking for Non Dilutive Grants and sponsorships for our research project and are in the middle of discussing backing with Microsoft, if anyone is interested in backing this project via compute, credits, direct funding, or any way.
Please reach out to me at: moseslua@amphichirallabs.com
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backtest:
NLCLS: 2.7 sharpe
Ridge: 2.3 sharpe
OOS:
NLCLS: 0.67 sharpe
Ridge: 1.87 sharpe
Quant funds pay millions for linear regression?
Non linear characteristic liquidity sweep waiting for people like him
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Oh and one more thing,
Be your worst enemy.
Framework today, try to kill it as much as possible with robustness tests tommorow!
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moses retweeted
Jun 6
String theory is probably a field that has set back quant trading by at least 10 years. Stealing top tier trading talent to do make believe 26 dimensional geometry, inflate boomer professors’s grant budget, and produce zero testable hypotheses or applications after 50 years
Jun 6
jane street is probably a place that has set back science by at least a 100 years. Stealing top tier research talent and making them do high speed coupon clipping to make rich people richer and also organize military coups in South Sudan.
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Jun 3
We're launching the microagi Research Fellowship.
Fellows get up to $2M in compute, robotics hardware, our evals, and one of the largest physical AI datasets ever assembled. You build in our lab, with our team, alongside partners like Unitree, Nvidia, and Google Cloud.
The hard part of AI left is physical. That's the part we're working on. Come build with us.
One more thing: know someone who belongs here? Reply with their name. If they get in, we send you 10.000 USD
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"To listen to the soul, we must lend an ear, because the soul's voice is not a shout, but a whisper."
May 30
Connecting young people to digital networks serves no purpose if they remain disconnected from themselves, others, and their own interiority. We must help young people rediscover silence, reflection, the ability to ask questions, the depth of relationships, and openness to transcendence. To listen to the soul, we must lend an ear, because the soul's voice is not a shout, but a whisper.
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i didnt wake up a loser
May 30
🇺🇸Jensen Huang is out there living his best life, dancing at the NVIDIA all-employee celebration event in Taipei, Taiwan
You'd never guess he's the CEO 😂
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as a founder i struggle to understand what hard work is but i dont think this is it
in this line of work 2 hours of work can easily trump 20
for pro valorant i grinded 12 hours a day
during yc i worked “7 days a week”
despite success i burned out in both
now i work a little bit more “balanced” schedule (5-6 days a week, ~10 hours). i get more work done, i make way better decisions, and theres still an argument to be made that i could do more by doing less
at a startup, there’s infinite things to do, no matter how much u work. its much more about tackling whats important rather than how much.
i’m not sure if i’m correct on my current setup either, i think i would benefit from having both more structure (consistent sleep/wake up time) and less structure (work doesnt always have to look like office work, if anything the most important things happen outside it). i just think this narrative below is wrong, contradictory from my experience.
May 30
"If you are not working 7 days per week, you are going to lose".
Corgi Insurance is the most intense workplace culture in startups.
- The company works 7 days per week.
- Founder (@nico_laqua) lives and sleeps in the office.
- He built a cafe in the office because there was no local cafe that was open 24/7.
- 2/3 of the first 30 team members have the Corgi logo as a tattoo.
Today I went behind the scenes with Nico, who has used this culture to scale the company to a $2.6BN valuation in just two years.
My condensed notes below:
1. If You Are Not Working 7 Days Per Week, You Are Going to Lose:
Whatever you can get done in 5 days, you'll get more done in 6 and 7. If you are trying to solve the world’s hardest problems, a standard 5-day workweek will not cut it.
2. Work Trials Repel the Mediocre:
Corgi forces candidates into mock work trials over the weekend. If seeing a full office on a Saturday scares them, they don't belong. True intensity acts as a natural filter to attract killers and repel clock-watchers.
3. Lead from the Front Lines
You can’t demand 7-day weeks while sitting on a yacht. Nico sleeps 3–4 hours a night on a mattress inside the office. If you want your troops to bleed, you have to be in the trenches with them.
4. Culture Only Means One Thing: Winning
Forget superficial jargon like "hackers" or "ex-founders." Strip away the corporate fluff. A great startup culture is aggressively optimized around one single word: Winning.
5. Lifespan vs. Victories
Building something world-historic requires radical sacrifice. When asked if he'd rather build a trillion-dollar company and die at 50, or fail and live to 80, the answer was easy. "I would rather measure my lifespan in victories."
6. Reject the Comfort of "Quiet Quitting."
If you are operating in a hyper-growth environment and your days off happen to be Saturday and Sunday every single week, you are quiet quitting. To win, you must deliberately bypass the off-ramps of personal comfort and low volatility.
Corgi isn't for everyone—and that’s exactly the point.
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moses retweeted
May 30
My girlfriend called me at 2am crying. She had seen a photo on Instagram of me and another girl at a party.
She sent me the photo. I looked at it and I'm like, what? Only my nose looks like the guy in the photo! I keep telling her, “We're not the same person,” but she is not ready to accept it.
She then forwarded the photo to my friends asking them to confirm.
Even they were confused. Bro that really does look like you.
Now, at this point, the only hope I have is my last line of defense - a Cosine Similarity Test.
I know you guys are thinking, what the hell is this Cosine Similarity.
Cosine similarity is a mathematical way to measure how similar two things are by treating them as vectors in space. Think of it like measuring the angle between two arrows - the smaller the angle, the more similar they are.
In math, cosine similarity works like this:
cos(θ) = A·B / (|A| × |B|)
Where:
- A·B is the dot product of A and B.
- |A| and |B| are the magnitudes.
Understanding the Scale (-1 to 1):
- cos(0°) = 1 : Perfectly identical
- cos(45°) = 0.7 : Partially similar
- cos(90°) = 0 : No similarity at all
- cos(180°) = -1 : Complete opposites
Now let me prove to my girlfriend that the guy in the photo is not me. Let's say my facial features are Vector A and the guy in the photo is Vector B:
Vector A = [2, 4, 6, 8]
Vector B = [1, 2, 3, 4]
Step 1: Calculate Dot Product
Multiply each corresponding element and add them all up:
A·B = (2×1) (4×2) (6×3) (8×4)
A·B = 2 8 18 32
A·B = 60
Step 2: Calculate Magnitude
Take the square root of the sum of squares of each element:
A = [2, 4, 6, 8]
|A| = √(2² 4² 6² 8²)
|A| = √(4 16 36 64)
|A| = √120
B = [1, 2, 3, 4]
|B| = √(1² 2² 3² 4²)
|B| = √(1 4 9 16)
|B| = √30
|A| × |B| = √120 × √30
|A| × |B| = √3600
|A| × |B| = 60
Step 3: Apply the Formula
cos(θ) = A·B / (|A| × |B|)
cos(θ) = 60 / 60
cos(θ) = 1
Cosine of 1 means perfectly identical.
Congratulations 🎉, you just learned Cosine Similarity.
Bonus:
Why does AI/ML care about cosine similarity?
Recommendation Systems: Netflix uses it to find movies similar to what you have watched.
Image Recognition: AI systems compare feature vectors extracted from images to identify faces or detect similarities between pictures.
Document Classification: Text classification systems use it to categorize emails as spam or not spam by comparing document vectors.
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May 28
Today, we're launching shift. We're starting by cleaning your apartment in New York City, for free.
Here's how it works. Book a shift cleaning. A vetted shift operator comes to your home wearing one of our devices. They clean. They leave. You pay nothing.
In exchange, we record the cleaning. Robotics is being built on data about how people do daily tasks, and the value of that recording is what funds the service. Anything personal in it is anonymized before the recording is processed.
By now, you have heard about the shift to AI more times than you can count. About the shift toward you, the part where you actually feel it, you have heard almost nothing. Shift is what starts to make it concrete, in specific cities, with specific services.
Today, cleaning in New York. Soon, handymen, repairs, and errands across the globe. And this is just one side of shift, with more on the way.
Comment “shift” and we’ll send you an early access link.
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moses retweeted
May 28
马斯克说，大学基本上就是用来玩的，不是学习的地方。
读个好大学也证明不了你有超凡的能力，只能证明你能完成一些分内的杂活儿。
大学的真正价值有两个，一是熬过那些无聊作业的过程，能让你学会硬着头皮把事情做完，
二是给你一段缓冲期，让你在被推进社会之前，先和同龄人一起混一段时间。
至于学习知识，现在网上免费就能拿到，想学什么都有，用不着去大学。
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May 28
AI economy = cheaper goods & services everywhere
even before an agentic robot has seen the light of day
May 28
Today, we are launching shift. Starting in NYC, we are bridging the economy of today into the AI economy where all services, goods, and leisure will be affordable, and humanity will progress towards abundance. Please enjoy your free home cleaning and join shift for a lot more!
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moses retweeted
May 28
We built a magic hat to capture the entire archive of human data.
May 28
Today, we're launching shift. We're starting by cleaning your apartment in New York City, for free.
Here's how it works. Book a shift cleaning. A vetted shift operator comes to your home wearing one of our devices. They clean. They leave. You pay nothing.
In exchange, we record the cleaning. Robotics is being built on data about how people do daily tasks, and the value of that recording is what funds the service. Anything personal in it is anonymized before the recording is processed.
By now, you have heard about the shift to AI more times than you can count. About the shift toward you, the part where you actually feel it, you have heard almost nothing. Shift is what starts to make it concrete, in specific cities, with specific services.
Today, cleaning in New York. Soon, handymen, repairs, and errands across the globe. And this is just one side of shift, with more on the way.
Comment “shift” and we’ll send you an early access link.
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moses retweeted
May 28
Today, we are launching shift. Starting in NYC, we are bridging the economy of today into the AI economy where all services, goods, and leisure will be affordable, and humanity will progress towards abundance. Please enjoy your free home cleaning and join shift for a lot more!
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moses retweeted
May 27
lowkey one of the best things about ML right now is how many legit research paths exist outside the traditional PhD route
- MATS
- OpenAI Residency
- Anthropic Fellows
- DeepMind Student Researcher
- ML Collective
- FAR. AI
- Mila
- INSAIT
- EleutherAI
- Redwood Research
- Apart Research
- Encode
- AI2, LAION
- Berkeley BAIR
- Stanford SAIL
- MIT CSAIL
- Vector Institute
- HuggingFace also quietly has some insanely strong open source contributors btw
stupidly exciting time to be in ML if you genuinely like building and researching things
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