Triatomic Capital

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

[stash @stash_pomichter]

Just got the keys to our new robotics warehouse(s) right in Dogpatch

Will be giving free office space to 15 amazing companies reply here + DM if you or someone you know wants to join!

[stash @stash_pomichter]

Introducing the Dimensional Hardware Grant Program

We’re giving away quadrupeds and arms to devs and creators to build with dimOS

Deploy robot agents as easily as software

Apply below, reply with your project ideas and we’ll fast track your application

[@dMatrix @dMatrix_AI]

The path to infinite inference.

d-Matrix CEO @sidsheth took the Main Stage at #AIInfraSummit2026, while Satyam Srivastava and Chris Nicol joined discussions on low-latency inference and distributed AI infrastructure.

Thanks to everyone who joined us at Booth 722.

#AIInference #dMatrix

[Carina Hong @CarinaLHong]

Axiom is going through hypergrowth 📈

We are hiring 20+ roles, technical (model, eval, FV, hardware design, product eng, FDEs, etc) and GTM (founder's office) 🪐

I am esp seeking high-agency folks - way smarter than me and push my thinking - to own the hardest problems E2E 🚀

[Efficient Computer @efficient_hq]

Graham Gobieski, CTO and co-founder of Efficient Computer, was named a Most Innovative Person by Embedded Computing Design. Graham, alongside co-founders Brandon Lucia and Nathan Beckmann, developed the Fabric spatial dataflow architecture that powers the Electron E1.

https://t.co/5vFxkukSTd

[@dMatrix @dMatrix_AI]

Bloomberg Tech: d-Matrix joins NVIDIA’s AI inference push.

CEO Sid Sheth joins Ed Ludlow to discuss NVIDIA NVLink Fusion and why inference is becoming the next major battleground in AI compute.

Watch: https://t.co/OyHPCGQaj4

#AIInference #NVLinkFusion #NVIDIA #dMatrix

[Edison Scientific, Inc @EdisonSci]

We're honored to be named to @BostonGlobe's inaugural 'Next in Medicine' list, which recognizes companies using research and technology to shape the future of patient care.

At Edison Scientific, that means building Kosmos, an AI scientist capable of compressing the months long, iterative work of R&D to one day. From discovery, to development, to the clinic, Kosmos is driving scientific advancement across domains.

[Sam Rodriques @SGRodriques]

Edison is named on @BostonGlobe's 'Next in Medicine' list. Thank you! We are just getting started...

[Jeff Huber 🇺🇸 @jhuber]

Why is NVIDIA partnering with @dMatrix_AI?

“NVIDIA already has Groq 3 LPX with its 128 GB of rack-level SRAM. @dMatrix_AI Raptor brings 18x the capacity for the frontier models SRAM can't fit.”

[Gimlet Labs @gimletlabs]

Congratulations to our friends at @dMatrix_AI and @nvidia !

Bringing Raptor to NVIDIA MGX with NVLink Fusion is an exciting milestone for multi-silicon inferencing, and towards delivering faster AI for everyone.

#AIInfrastructure #NVLinkFusion

[Peter Zhou @xtzhou]

We’ve always been impressed at the technical depth and execution at @dMatrix_AI, and it’s great to see industry leaders such as @nvidia and @AsteraLabs recognizing this. Excited to see the 🔥 performance of Raptor + Vera Rubin!

[Triatomic Capital @TriatomicCap]

Massive multiplexing meets biology & AI

@ManifoldBio

[Gleb Kuznetsov @glebkuz]

As it becomes viscerally apparent just how rapidly and thoroughly AI is conquering the realms of numbers and code, I keep thinking about what this means for the realm of atoms. While the concern about the risks is real and warranted, the potential for positive impact is immense and imminent.

But the limits now shift to the complexity, time, and cost of interfacing with the physical world.

What I love about biology, and what distinguishes it from most other realms of atoms, is the power of massive parallelism to overcome these limits. This is what drew me to the field over a decade ago.

The moment has arrived for those of us who have been building massively parallel interfaces between the vast space of molecular designs and the complexity of biology. Our team at @ManifoldBio has been building an interface directly into whole organisms.

We now have the potential to catalyze some of the most beautiful and beneficial applications of powerful AI.

[Gleb Kuznetsov @glebkuz]

As it becomes viscerally apparent just how rapidly and thoroughly AI is conquering the realms of numbers and code, I keep thinking about what this means for the realm of atoms. While the concern about the risks is real and warranted, the potential for positive impact is immense and imminent.

But the limits now shift to the complexity, time, and cost of interfacing with the physical world.

What I love about biology, and what distinguishes it from most other realms of atoms, is the power of massive parallelism to overcome these limits. This is what drew me to the field over a decade ago.

The moment has arrived for those of us who have been building massively parallel interfaces between the vast space of molecular designs and the complexity of biology. Our team at @ManifoldBio has been building an interface directly into whole organisms.

We now have the potential to catalyze some of the most beautiful and beneficial applications of powerful AI.

[Triatomic Capital @TriatomicCap]

*Very* big news for @dMatrix_AI, @nvidia, and ultra-low latency AI inference.

[@dMatrix @dMatrix_AI]

Big news for d-Matrix and AI inference.

We’re collaborating with NVIDIA to bring our next-gen Raptor inference XPUs into NVIDIA's MGX rack-scale infrastructure with NVIDIA NVLink scale-up interconnect. Ultra-low latency inference. Premium-level token services. Built to scale.

Read the full announcement: https://t.co/PJ8XLnrLmq

#NVLinkFusion #AIInfrastructure #AgenticAI #dMatrix

[Jerry Tworek @MillionInt]

Big labs are moving away very slowly from transformers because they’re making small gradient steps in each iteration and iteration takes them multiple months.

You can just front run it by… taking big steps 😀

[Dina Bass @dinabass]

Gimlet Labs, an AI startup that helps companies divide AI tasks between multiple kinds of chips, is now valued at $3B after a $300 million round led by @a16z with $ from ARM and Microsoft’s M12 https://t.co/R1mrYTakzn

[EPIC Photonics @EPIC_photonics]

📣 @iPronics secures $125M in Series B funding led by Maverick Silicon and Light Street Capital, alongside NVIDIA, to accelerate deployment of its iPronics ONE optical switching platform for AI data centers. https://t.co/g2GZC9BC1s #EPICMemberNews #Photonics #SiliconPhotonics

[Eric Nguyen @exnx]

Turns out genome language models can design cancer vaccines.

Pretty exciting direction, the context-adapting machinery of language models is what may unlock personalized medicine.

Great work team!
@RadicalNumerics

[Jerry Tworek @MillionInt]

It is an amazing historic achievement and a new jewel in the crown of transformers, pretraining, reinforcement learning and scaling time compute.

Civilization is being moved forward by AI and it’s not hard to extrapolate how those systems will be driving our progress in coming years.

[Radical Numerics @RadicalNumerics]

1/5 We pretrained Omnii, a multimodal language model on DNA. Then, we asked it to design a cancer vaccine

In new research, we show how Omnii learned to turn a tumor DNA sequence into a personalized mRNA vaccine design.

Read more here: https://t.co/0Uw5yLn8pd