Peter Zhou retweeted
Thanks to amazing AI, deeptech, & techbio founders / portfolio companies, our Fund I crushed, and our Fund II landed oversubscribed. We're growing and hiring two Principals at @TriatomicCap – focused on Next-gen Compute and on Engineered Biology.
We’re looking for obsessively curious people who:
. are deeply technical/scientific
. think from first-principles
. have conviction before others have understanding
. are fully AI-pilled builders and default to creating infrastructure & products instead of spreadsheets
. have real relationships with the founders, engineers, and scientists building hard stuff.
Eng/Science/CS/Math/Physics with BS/MS/MD/PhD preferred. No prior VC experience required (but we won't hold it against you if founders you've backed love you). Offices in Palo Alto & SF Mission Bay.
If this sounds like your dream (where you get paid to do the stuff you love anyway) – please reach out!
If your inflated-equity golden handcuffs make it impossible for you right now – please point us to the smartest, most-thoughtful, most-interesting people you know, so you can live vicariously through them after they join us. :)
Apply: jobs.ashbyhq.com/triatomic
We’re looking for obsessively curious people who:
. are deeply technical/scientific
. think from first-principles
. have conviction before others have understanding
. are fully AI-pilled builders and default to creating infrastructure & products instead of spreadsheets
. have real relationships with the founders, engineers, and scientists building hard stuff.
Eng/Science/CS/Math/Physics with BS/MS/MD/PhD preferred. No prior VC experience required (but we won't hold it against you if founders you've backed love you). Offices in Palo Alto & SF Mission Bay.
If this sounds like your dream (where you get paid to do the stuff you love anyway) – please reach out!
If your inflated-equity golden handcuffs make it impossible for you right now – please point us to the smartest, most-thoughtful, most-interesting people you know, so you can live vicariously through them after they join us. :)
Apply: jobs.ashbyhq.com/triatomic
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We're hiring two Investment Principals at @TriatomicCap, one for Compute and one for Bio.
No VC experience needed. We want deeply technical people who use AI agents for everything and know founders and engineers in the space.
Palo Alto / SF: jobs.ashbyhq.com/triatomic
No VC experience needed. We want deeply technical people who use AI agents for everything and know founders and engineers in the space.
Palo Alto / SF: jobs.ashbyhq.com/triatomic
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AI scientists are only as useful as your ability to check their work.
In math, @axiommathai can check it all the way down to the kernel, and the Stacks release shows that works at the scale of a whole field. Congrats to @CarinaLHong and the whole team!
In math, @axiommathai can check it all the way down to the kernel, and the Stacks release shows that works at the scale of a whole field. Congrats to @CarinaLHong and the whole team!
Most think vibecoding at scale is slop. Here’s a counterexample.
Today we release a 16M-line formalization of the entire Stacks Project, critical infra underlying modern math, with optimized code quality and its highly interconnected structure preserved.
A mathematical city 🌆
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AI editing AI weights directly, without training, is one of those results that sounds like science fiction until it's a paper. Interpretability (maybe w/o human involvement) just went from "understand the model" to "edit the model."
We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math.
It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training.
We call this Weight-Space Programming: fronely read/write neural network weights! 🧵
Blog: rikiyat.github.io/blog/weight-sp…Community noteLLM was given weights explicitly as text in prompt and used code/forward passes (per authors' logs) to ablate Qwen looping direction, a known thinking-mode issue per model card. Primarily fixed repetition in that mode, not general 'natively' improving weights/math.
rikiyat.github.io/blog/weight-sp…
github.com/RikiyaT/lm_und…
huggingface.co/Qwen/Qwen3.5-0…
huggingface.co/RikiyaT/Qwen3.…
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Superintelligence for medicine won't come from a chatbot. It'll come from AI scientists plugged into the data and labs of companies like @pfizer. Huge milestone for @EdisonSci. Congrats to @SGRodriques, @andrewwhite01, and the team! x.com/EdisonSci/stat…
At Edison, our goal is to bring superintelligence to medicine.
Today, we’re thrilled to announce an agreement with @pfizer to deploy our AI scientist, Kosmos, across Pfizer’s R&D pipeline.
By learning from Pfizer’s robust repositories of data across oncology, immunology, internal medicine and more, Kosmos will enable every program, experiment and clinical readout to sharpen Pfizer’s R&D decision-making and accelerate their pipeline, with compounding advantages to the discovery and development of life-saving medicines.
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Mathematicians spent generations building the 'periodic table of symmetry.' @axiommathai just made a computer check every page. Verified AI reasoning is moving much faster than people realize, and it won't stay in math for long.
The largest math proof in human history is now computer-verified.
Today, Axiom announces a complete Lean auto-formalization of the Classification of Finite Simple Groups, the "periodic table of symmetry."
About 15,000 pages, built by over 100 mathematicians across generations.
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When we backed @RadicalNumerics, the bet was that one general model could learn the language of biology, the same way LLMs did for text. Today Omnii-1 beats AlphaGenome, designs antibodies and cancer vaccine candidates, and designed a phage covered by @carlzimmer in @NYTimes. All from one model. 🧬
Introducing Omnii-1, our most powerful genome language model, and a major step toward general biological intelligence
In a world first, Omnii-1 designed the first AI-generated bacteriophages to be administered to a human patient with an antibiotic-resistant infection under compassionate use
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We've been following @semiDL and team for over a year and are thrilled to be a part of their Series A. Tapa's assembled a world-class team tackling the core problems of memory capacity and bandwidth that hold back model intelligence. Excited to see this team build!
Excited to announce Volantis's $88M Series A.
We are solving Al's memory bottleneck by using optics, enabling chips with huge amounts of fast & cheap memory.
By boosting both the memory bandwidth and capacity per chip by orders of magnitude, we enable ultra-fast inference (up to 1ge models (>10T) - with low $/tok to boot.
Initially, this will enable insanely fast agents - think coding agents that finish in minutes or even seconds instead of hours.
More excitingly, optics is a fundamentally scalable way to increase memory systems. Not 2X/year, but by orders of magnitude across new generations. This will enable a structurally new Al industry, including restarting scaling laws, holding entire repos in context windows & more.
Our team has pioneered many core semiconductor technologies: the 1st CoWoS product, early HBM, the 1st silicon photonics CPO systems, the 1st high volume tunable VCSELs, the 1st processors to directly communicate using light & more.
We’ve already sent data >10× farther than equally tiny electrical wires inside a chip package. Our next iteration is already taped out and targets world-record bandwidth density over relevant distances, read more: volantissemi.ai/news-insights/…
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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!
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.
ment: d-matrix.ai/announcements/…
#NVLinkFusion #AIInfrastructure #AgenticAI #dMatrix
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Peter Zhou retweeted
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.
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.
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Peter Zhou retweeted
A note from our co-founder and CEO @zainasgar on Gimlet Labs' $300M Series B.
This milestone belongs to the team building Gimlet Labs.
We’re hiring across the company as we scale our multi-silicon inference cloud. If you want to tackle some of AI infrastructure’s hardest problems and help build for the agentic era, join us: gimletlabs.ai/join_us
This milestone belongs to the team building Gimlet Labs.
We’re hiring across the company as we scale our multi-silicon inference cloud. If you want to tackle some of AI infrastructure’s hardest problems and help build for the agentic era, join us: gimletlabs.ai/join_us
1/ Today, we announced Gimlet Labs’ $300M Series B, led by @a16z, joined by @SapphireVC as a major investor bringing our valuation to $3B.
We started Gimlet with a simple conviction: inference would become the dominant AI workload, and its infrastructure would need to be rebuilt from the ground up.
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This is really cool. Congrats to the @axiommathai team!
1/ ✨ World record today on bounded gaps between primes, one of number theory’s oldest open conjectures.
We show that infinitely many pairs of prime numbers are separated by 212 or less.
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Don’t use AI that forgets after every session. Bring your context to any model. Love what @ATCalder and @HeresTheChurch have built!
Today we're launching OM2.
Your AI re-reads your entire company from scratch every time you ask it something.
It’s why more than 50% of your token bill isn't in the answer, but in the search for it.
OM2 gives your AI a permanent memory of your company. 🧠
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Maintain access to the global robotics hardware ecosystem with secure, compliant software from @dimensionalos 💪
Excited to announce that Dimensional is now THE compliant gateway for robots to access the US
Big thanks to dimOS contributors cited in the National Security Determination and our supporters in government
Working closely with our partners home & abroad to secure network attacks, eliminate data exfiltration, and protect American infrastructure from foreign backdoors
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Teleop is the quiet unlock for the whole robotics stack: training data, remote services, human-in-the-loop RaaS. dimTELE makes it open source and low-latency for ANY robot. Entire businesses will be built on this layer. 🤖
Announcing dimTELE.
Remote control ANY robot, from ANYWHERE in the world, with ultra low latency, fully open source.
Required for training data collection, remote professional services, human intervention for RaaS and more. Whole businesses can be built on teleop.
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Spatial intelligence and navigation start developing at infancy for human beings. @dimensionalos is democratizing this capability for robots 🤖
Announcing the first production robot navigation framework on $500 hardware
Explore the world once → your robot agent will relocalize and build a persistant, spatial memory across sessions
SLAM, relocalization, loop closure, map i/o, planning, control
No ROS. Open source.
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Made it to Top 8 (for now) after Claude suggested taking a break from neural nets and submitting a strong rules-based agent. Submission derived from this Kaggle notebook, which is now all over the top of the ladder: kaggle.com/code/masamikob…
There’s very little sign of ents across deck archetypes so far. Deck choice and training data curation makes every agent, even the neural-net-based ones, a custom engineering effort.
There’s very little sign of ents across deck archetypes so far. Deck choice and training data curation makes every agent, even the neural-net-based ones, a custom engineering effort.
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Top 4 now. But the top of the ladder only plays one another intermittently and it’s either mirror or Alakazam. Will be fascinating to see how this meta evolves in the next 6 weeks.
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