Triatomic Capital

135 posts

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Triatomic Capital

Triatomic Capital

@TriatomicCap

‘AppliedAI’ in Deep tech, Health tech, & New economy // Helping great entrepreneurs build 'century-defining' technologies & businesses.

Palo Alto, CA USA شامل ہوئے Ocak 2022
395 فالونگ568 فالوورز
Triatomic Capital
Triatomic Capital@TriatomicCap·
We're growing – thanks to our opinionated view on AI, our all-star Fund I portfolio, and imminent launch of Fund II. We're looking for a superstar Chief Financial Officer (CFO) to help drive our next chapters. Applications and/or referrals of great candidates welcomed. More here: lnkd.in/gzHgFEqh
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Eric Nguyen
Eric Nguyen@exnx·
The next frontier in AI is science, the physical world. Biology will be the *most* impactful and consequential application of AI, from curing disease to biosecurity. We need AI labs pushing both the limits of biological design and the systems to defend against it. We’re building exactly this intelligence layer and scaling fast. Hiring across AI and biology. Come build at the frontier, let's talk. job-boards.greenhouse.io/radicalnumerics
Michael Poli@MichaelPoli6

We're growing rapidly at @RadicalNumerics and scaling our core teams. Join us in building the next generation of scientific world models. We're hiring across a few roles, each with significant ownership and cross-functional scope: - Member of Technical Staff, Post-Training - Member of Technical Staff, Infrastructure and Training Systems - Member of Technical Staff, Pretraining Science - Member of Technical Staff, AI Bio - Member of Technical Staff, Biosecurity Our technology brings together numerics, systems engineering, and architecture design to tackle large-scale pretraining on scientific data. Our blogs (see below) give a flavor of the work. We believe that advancing capabilities must go hand-in-hand with advancing safety and biosecurity. The same systems that design biology must also help defend against it. Ping me or others in the team if you'd like to learn more. job-boards.greenhouse.io/radicalnumerics

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Gleb Kuznetsov
Gleb Kuznetsov@glebkuz·
Behold the power of massively parallel multiplexing @ManifoldBio brought to this study
Kieran Didi@DidiKieran

@ManifoldBio @viva_biotech @novonordisk @Cambridge_Uni @DukeU @LMU_Muenchen Massive campaign: ~1M designed candidates screened across 127 diverse/challenging targets with all-to-all binding readouts. We solve more than 2/3 of the targets given a very limited compute budget and often quite challenging hotspots and crops 11/n

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iPRONICS
iPRONICS@iPronics·
At @nvidia #GTC2026, one theme became clear: as AI infrastructure reaches massive scale, silicon photonics has moved to present‑day necessity. At @iPronics, we welcome this shift. The market is aligning with a truth we’ve championed from the beginning: photonics is here to stay.
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Samip
Samip@industriaalist·
kinda wild that larry page had the bitter lesson figured out in ~2007. for context, sutton published his version in 2019
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Pierce
Pierce@PierceOgdenJ·
Really great collaboration between @ManifoldBio and @nvidia to test 1M de novo designed binders against 127 targets, measuring over 100 million potential protein-protein interactions! This was a great collaboration with some very exciting results. NVIDIA's new Proteina-Complexa method is SOTA for de novo minibinder design. If you're interested in designing minibinders to targets you couldn't hit with other methods, try it out! I'm particularly excited about what this large scale data enables. As we generate 1000s of experimentally validated structures, this data becomes the input to training new protein design models. At Manifold, we are generating datasets of this size continuously, and have experimentally validated thousands of de novo designed binders across many formats (VHH, minibinders, peptides, etc). New models will open up new hard to hit targets, paired with our large scale in vivo measurement, will enable us to create previously impossible therapeutics. Up next is training new models on this and other data we have generated, stay tuned! And thanks to NVIDIA for setting up such a great collaboration, its been fun and fruitful!
Pierce tweet media
Christian Dallago@sacdallago

🧵 We ran the largest head-to-head benchmark of protein binder design methods in the wet lab. Project page: research.nvidia.com/labs/genair/pr… 1 million designs. 127 targets. RFdiffusion, BindCraft, BoltzGen, and Proteina-Complexa — all tested side by side.👇

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Jeff Huber 🇺🇸
"AI drug development" needs a real-world reinforcement learning (RL) loop, like @ManifoldBio enables. This is how you get LLM & world models that work. Paving the path to true zero-shot clinical design. Great job @GlebKuz, @PierceOgdenJ & Team!
Gleb Kuznetsov@glebkuz

Just announced our joint study with @NVIDIAHealth running a million molecule benchmark of AI-designed proteins for Nvidia's new model Protein-Complexa. Here we brought our massively multiplexed all-against-all AI binder testing platform that has been core to progressing our own protein design model mBER. The key to advancing protein design models beyond what's possible from public data is experiment scale that can match the scale of generative AI. Together we were able to show some quite fantastic results with a 68% hit rate for Protein-Complexa. More designs generated and more designs tested is better (when you can do it efficiently).

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Jeff Huber 🇺🇸
Great meeting you last night, Ethan! Thank you for your service to the country, and congratulations on the progress with the Genesis Mission ("to unleash a new age of AI‑accelerated innovation and discovery that can solve the most challenging problems of this century.") whitehouse.gov/presidential-a…
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Gleb Kuznetsov
Gleb Kuznetsov@glebkuz·
Just announced our joint study with @NVIDIAHealth running a million molecule benchmark of AI-designed proteins for Nvidia's new model Protein-Complexa. Here we brought our massively multiplexed all-against-all AI binder testing platform that has been core to progressing our own protein design model mBER. The key to advancing protein design models beyond what's possible from public data is experiment scale that can match the scale of generative AI. Together we were able to show some quite fantastic results with a 68% hit rate for Protein-Complexa. More designs generated and more designs tested is better (when you can do it efficiently).
Manifold Bio@ManifoldBio

@ManifoldBio and @NVIDIAHealth announce a joint study validating Proteina-Complexa, NVIDIA's latest BioNeMo model for protein binder design.

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@dMatrix
@dMatrix@dMatrix_AI·
AI inference is no longer just a compute challenge. It is a memory challenge. At d-Matrix we built our architecture around SRAM for ultra-low latency inference. Now we’re pushing further with 3DIMC, a 3D stacked DRAM approach validated by our Pavehawk chip to scale memory for the next generation of AI workloads. Read the blog: d-matrix.ai/going-vertical… #AIInference #Semiconductors #AIInfrastructure #MemoryArchitecture #dMatrix
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Sam Rodriques
Sam Rodriques@SGRodriques·
Tomorrow…
Sam Rodriques tweet media
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stash
stash@stash_pomichter·
Dimensional is the #3 trending repo on Github 72 hours after our launch Amazing to see thousands of developers using dimOS to release their Openclaw / other Agents into the physical world Run dimOS to give your agent access to hardware and physical tool calls
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Axiom
Axiom@axiommathai·
"When formal verification becomes fast, cheap, and automatic, the addressable market is the right of first refusal to generate every line of AI-generated code that has any consequence." The TAM Is All AI Code's ROFR. If you share this dream, join us! menlovc.com/perspective/ai…
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stash
stash@stash_pomichter·
Holy shit This developer used Dimensional to vibecode a flight simulator for his Openclaw-powered Drone in a SINGLE DAY. Now your agent can test its drone piloting skills locally before flying on real hardware 🚀🚀
Mourad Ouaz@mourad_zauo

@dimensionalos DAY 7 IT IS - DimOS drone module only supported real MAVLink or replay. No simulation. I integrated Skydio X2, a MuJoCo drone module, with real quadrotor dynamics, PD attitude controller, and full blueprint compatibility. Now anyone can prompt drone agents without hardware.🚁

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