@quantbagel
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billions will thrive robot inference @hf0, ex-quant 2x
SF | Montreal
Joined August 2025
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I’m hiring for my robotics inference startup, we’re working on solving fast cheap long context batch invariant Inference for VLAs and WMs, billions will thrive!
when you sell infra to startups there is a venture investing quality to it
if your clients can't win & grow fast over the next years, you're ngmi
but if you're useful early to people about to win, you're having the easiest sell process for the best future outcome
at boat.dev we optimize everything from product positioning, gtm and tech for that, maximally serving the future winners
- be where they are: on X
- be how they are: opinionated, outspoken, grinding, high-integrity
- optimize for what they'll do but large incumbentd don't: infra for long-running employee agents
- sell to who decides for them: their agents (publish lots of data, benchmarks, have detailed docs)
frontier coding models tokens are almost always worth more than other models so those inference providers can always bid more per gpu/h
Lucas retweeted
the best people to work with are:
- high agency
- high ownership
- low ego / hungry for feedback
Lucas retweeted
The unreasonable effectiveness of actually looking at data
We (@PantheonInc) have been working on a robotics data quality pipeline that uncovered a series of major problems in public robotics datasets, especially for world modeling.
To improve the quality of data available to open-source robotics, we're publishing annotations for four of the most popular datasets. Some examples of issues, and our report 🧵
Lucas retweeted
I spoke to some MBAs recently, and this was my provocation:
You are here to become big important CEOs some day... but given modern AI tools, you kinda already are one! Everyone has a company of smart people in their pocket now.
So why wait? Start acting like a CEO now!
I’m going to make a 20$ physical Ai inference sub with the strict purpose to just try to break even. At scale I think it’s possible
Lucas retweeted
I’m hiring for my robotics inference startup, we’re working on solving fast cheap long context batch invariant Inference for VLAs and WMs, billions will thrive!
cache hit rate is the next thing to optimize for we are currently at ~70%, noisy cameras and ego motion are REALLY hard problems
we've had 30ms VLA cloud inference for a while, tail latencies are a major problem:
colocated racks on a factory floor
we're been looking for more hardware deployment partners, we gather data, train models and inference them, we can run ~200 bimanual VLA policies on a single node
