@raunakdoesdev Yeah but think about all of us suckers who invested a month ago :(
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Thomas Boser
56 posts
Thomas Boser
@thomasboser
bad cop @hiloopai
San Francisco, CA Katılım Aralık 2019
89 Takip Edilen89 Takipçiler
apologizing for being up 80% YTD is crazy work
leopold is a mad man in the best ways
TBPN@tbpn
Here is the full letter Leopold sent to his LPs last night. Rumors of his demise are greatly exaggerated.
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i'll be in vegas next week! tag your most degenerate gambler founders you know i should meet while i'm there!
Reducto@reductoai
We'll be at Ai4 in Vegas next week! Find Reducto at Booth P8 🔮 Our events lineup: 🗓️ Tuesday, August 4th: @aditabrm will be speaking on a panel about leveraging Data Strategy to Enable Effective AI 📍 Titian Ballroom 2302 ⏰ 3:00 - 3:45 PM 🗓️ Wednesday, August 5th: Join us for racing simulators and real talk with data & AI leaders on trusting agents in production. 📍F1 Arcade ⏰ 7:00 - 10:00 PM 🔗 Sign up: event.montecarlodata.com/monte-carlo-ev…
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Dinner or not, I’d love to chat with folks interesting autoresearch at AI4 next week!
Karan Brar@deepmatmul
What happens when AI systems can improve themselves? At Ai4, we’re bringing together founders and AI/ML leaders for a small dinner on systems that learn from real-world use, run their own experiments, and keep getting more accurate, faster, and cheaper. Join us: luma.com/q7u2yg9w
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Thomas Boser retweetledi
Every AI company should own its data, its models, and the research lab that keeps making them better.
Today, @thomasboser and I are launching @hiloopai to make that possible.
The frontier advantage isn’t access to a model. It’s the research organization continuously improving it.
Your product already generates the raw material for better intelligence: proprietary data, production feedback, evaluations, and domain expertise. Very few teams have the research capacity to turn those assets into better models.
Hiloop builds and operates that capability with you.
Bring us the model your product depends on, the data that makes it different, and an evaluation that defines success. We reproduce your baseline and run an autonomous research campaign against it.
Agents pursue competing hypotheses in parallel, build on previous results, and promote only improvements that survive verification. Our researchers validate the winners and bring them into production.
The work can run hosted or inside your environment. You retain control of your data, and the resulting models, evaluations, and research artifacts are yours.
We’re starting with model training, post-training, and inference optimization, where progress is measurable and the value is immediate.
But this isn’t a one-off model improvement. It’s a persistent research capability that begins each campaign with everything learned from the last.
Over time, the lab accumulates research memory and improves its own tools, evaluations, and agents. The process used to create better intelligence gets better itself.
That’s infrastructure for recursive self-improvement.
If your product depends on a model and an important metric has stopped moving, bring us the model you can’t make better. We're much better at research than making videos!
Reach out to us: founders@hiloop.ai
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A more detailed overview of what we're doing at hiloop. Something we don't really mention - we're also making this secure for enterprise customers (data exfiltration controls, fully deployable in your cloud, etc. Reach out to learn more!
hiloop (YC S26)@hiloopai
Check out our launch YC post for more details on what we're doing! ycombinator.com/launches/SBN-h…
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We're still working on our cinematography skills, but we're pretty good at autoresearch. Hit us up if that's something you want to get better at too!
Karan Brar@deepmatmul
Every AI company should own its data, its models, and the research lab that keeps making them better. Today, @tboser and I are launching @hiloopai to make that possible. The frontier advantage isn’t access to a model. It’s the research organization continuously improving it. Your product already generates the raw material for better intelligence: proprietary data, production feedback, evaluations, and domain expertise. Very few teams have the research capacity to turn those assets into better models. Hiloop builds and operates that capability with you. Bring us the model your product depends on, the data that makes it different, and an evaluation that defines success. We reproduce your baseline and run an autonomous research campaign against it. Agents pursue competing hypotheses in parallel, build on previous results, and promote only improvements that survive verification. Our researchers validate the winners and bring them into production. The work can run hosted or inside your environment. You retain control of your data, and the resulting models, evaluations, and research artifacts are yours. We’re starting with model training, post-training, and inference optimization, where progress is measurable and the value is immediate. But this isn’t a one-off model improvement. It’s a persistent research capability that begins each campaign with everything learned from the last. Over time, the lab accumulates research memory and improves its own tools, evaluations, and agents. The process used to create better intelligence gets better itself. That’s infrastructure for recursive self-improvement. If your product depends on a model and an important metric has stopped moving, bring us the model you can’t make better. We're much better at research than making videos! Reach out to us: founders@hiloop.ai
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Just learned my coworker finished a half marathon under 01:35... I feel old
Yifei Hu@hu_yifei
Finish time < age. I am happy
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5.6 sol is too agentic it keeps sending slack messages to my colleagues
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silicon valley's obsession with pain is very interesting. what a sad way to live.
Han Wang@handotdev
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wow didn't know codex pets had functional utility, but would recommend now
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who would want an SE/FDE mixer at @reductoai’s beautiful new space? was wanting to pick people’s brains on technically supporting deals in AI GTM teams!
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@AlvinRyanputra @deepmatmul 500k each from OpenAI and anthropic. Who knows how long it’ll last…
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@raunakdoesdev yeah that makes sense. i definitely agree that fable feels a lot worse to talk to than opus. fair enough, we'll see tomorrow when they GA sol.
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@thomasboser remember how I used to prefer opus over codex even though 5.5 was technically smarter? feel very similarly in the opposite direction with these two models
fable may have more IQ but to actually work with on the day to day sol clears
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@_vatsadev These guys are amazing! Anybody solving hard verifiable problems should definitely reach out.
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AMAZING WORK
wonder how one even designs with this output in mind though, like how do you make 4.1K experiments remotely readable to a human/quick to iterate on
honestly making a opionated github repo and throwing 4000 experiments at it must feel awesome
hiloop (YC S26)@hiloopai
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I also expect the norm to be that 99% of companies will mis-time the creation of the research division and mis-time the expected returns by several quarters, which will then lead to the shuttering of these departments before they give srs returns
Cody Blakeney@code_star
As fun as the memes are, I expect this will be the norm. Any company with sufficiently large AI spend in their app will want to be doing research on how to get more out of it. That doesn’t mean every company will do architecture research or scaling laws, but it will be normal.
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Thomas Boser retweetledi
A bit of a late update, but @thomasboser and I got into YC S26. We're building @hiloopai, and we got a pretty cool result. Check it out!
hiloop (YC S26)@hiloopai
@deepmatmul pointed agents at Karpathy's autoresearch benchmark and achieved a SOTA result. We're building infrastructure to scale autoresearch. We work with teams on their hardest problems. Hosted or on-prem. Reach out to us: founders@hiloop.ai
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