
co-founder @getenergy_, previously research at @OpenAI & @midjourney solving future of computer work with @getenergy_
San Francisco
Joined March 2019
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- Following607
- Followers132K
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gabriel retweeted
We've designed a custom stratospheric balloon platform weighing just under 10 g. anyone can build and launch one by following the docs stratolink.org
gabriel retweeted
I’m hiring a full time creative operator
I made this video in 48 hours, I will teach you how
Must enjoy talking to AI researchers and hollywood cinematographers. In-person 6 days a week in SF. Get equity in top companies. 5k referral bonus. Duties may include:
Last month, we demonstrated high-rate alchemy: turning mercury into real, stable gold, beating CERN’s record by a factor of 10.
Last week, we enriched isotopes in the world’s most powerful plasma centrifuge, beating the Soviet record that stood for 40 years.
Now, we’re building a fusion reactor in San Francisco to achieve record power density.
you don't have to hide that you want to win
everyone here already wants to win. it requires huge effort to work in sf or have a big following
the decision is between lying that you don't care, or being honest and let people make informed decisions. choose honesty
rant:
Replying to @drgurner
you are literally possessed by status and your career depends on it
only people whos lives purpose is status have an urge to point out how "low status it is to chase status"
how ironic, pretending not to care, and at the same time cite WSJ in your bio 😂😂
Buried within gabriel’s tendency to provocateur-maxx, the basic point he’s making in this thread is that when choosing your early career moves, you should almost always take the high status/prestige option. And he’s right.
I’ll shit on consulting plenty, but working at an MBB was unequivocally the best career decision I ever made and it continues to pay enormous dividends.
gabriel retweeted
Cancer patients with the same diagnosis often have very different tumor biology.
Molecular testing can reveal underlying differences, but that's slow and expensive.
Introducing Holon-S1, our platform to predict genes and biomarkers from routine pathology slides.
• beats two other models at predicting spatial gene activity in a controlled comparison
• has identified potentially novel biomarkers in breast cancer and colon cancer
• evaluated across 16 organ types and more than 15 scanners, using slides from both formalin-fixed, paraffin-embedded and fresh-frozen tissue.
We believe Holon-S1 has the potential to help researchers find new biomarkers in slides they already have, discover treatment targets, and bring more personalized cancer care within reach!






