Co-founder and President @RadicalNumerics | Researcher @ RIKEN | AI ∩ numerics ∩ signal processing
Bunkyo-ku, Tokyo
Joined July 2019
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@RadicalNumerics has raised $50 million in Seed funding. Evolution is the longest optimization run in history: four billion years of search toward an objective no one chose. We are here to design what evolution didn’t — and the defenses to keep that power safe. Both are inseparable. With my brothers @exnx, @athmsx and @MichaelPoli6. The work of a lifetime.
Together with my co-founders Michael @MichaelPoli6, Stefano @Massastrello and Armin @athmsx, I am excited to announce @RadicalNumerics is emerging from stealth with a $50M seed round to build general biological intelligence.
We’re also sharing an early preview of our new model Omnii, the most powerful genome language model to date.
Omnii preview link:
radicalnumerics.ai/blog/radi…
At Radical Numerics, our mission is to master the code of life, and to drive the frontier of biological AI for both design and defense.
This is our dual mandate, which comes from something our own team helped make possible.
Our founding team trained Evo and Evo 2, the largest biological AI models (40B params) trained on DNA sequences. Trillions of tokens across all of life, from microbes to mammals. It’s fully open source, and created the field now known as generative genomics.
Last year, scientists used Evo to generate the world’s first complete genome from scratch using AI. Turns out it was a bacteriophage—a type of virus. It functioned in the real world, and in this case it was harmless. But for us, it was a clear turning point.
It showed that AI is no longer just analyzing biology. It is on the cusp of generating functional lifeforms. Eventually, AI will have the power to design and control life itself.
That should make all of us incredibly excited, and incredibly uneasy. (Anyone can design DNA with a new function, and have it synthesized and delivered, like something from Amazon Prime).
The same technology that will help us cure cancer is the very technology that might create the next global pandemic, or worse, allow the creation of bioweapons that can wipe out populations.
We believe these forces are inseparable. If you work on the frontier of biology, you have to build technology to safeguard it from its misuse. Existing biosecurity tools are sorely losing the arms race, relying on outdated “have I seen this exact thing before?” style algorithms.
We founded Radical Numerics to turn the tide.
And we can’t do that by training on textbooks and natural language. We must understand the language of biology from the raw physical data itself, to reason across every molecule and modality, from DNA to proteins.
The next frontier for AI goes far beyond chatbots or video generators to models that can understand and engineer life.
Today, we’re previewing Omnii, which is already far surpassing Evo 2, and will continue improving as we scale and add new modalities (training now).
1. For human health, Omnii can read and write whole genomes (more on writing later). It’s state of the art (SOTA) on detecting causal variants for disease, and can rank Alzheimer's mutations zero-shot. We’re partnering with a diagnostics company to use Omnii for early cancer detection (pancreatic and multi-cancer).
2. For defense, Omnii is SOTA at detecting AI-generated pathogens. We benchmarked existing detection tools, and they simply can’t detect the AI-generated ones (“deepfake viruses”). We’re partnering with a US national lab to pilot Omnii for detecting the next pandemic, both natural and AI-generated.
We have a data center full of Blackwells in construction now to build the most powerful biological AI models ever. This mission takes a new kind of AI lab that can actually scale on physical, biological data: new alignment research (mid/post training), scaling long context, building out mech interp teams to dissect what these models learn, new architectures and systems designs, all from the ground up.
Our team is made up of AI researchers and scientists from top labs and institutions (e.g. Stanford, MIT, Google DeepMind), but more importantly, we all share the belief that this is the most important challenge of our lifetime. If you feel similarly, we are hiring. We aim to bring the brightest minds in AI and science together to save lives.
Thanks to our partners on this journey, led by Emergence Capital @emergencecap, with Obvious Ventures @obviousvc, Triatomic @TriatomicCap
, and Patrick Collison @patrickc. Our advisors include Eric Horvitz @erichorvitz, CSO of Microsoft, Chris Re @HazyResearch of Stanford, George Church @geochurch of Harvard, and Andrew Weber @AndyWeberNCB, former Assistant Secretary of Defense for Nuclear, Chemical and Biological Defense Programs.
Fortune article: fortune.com/2026/06/15/exclu…
Jobs: radicalnumerics.ai/join-us
Omnii-1 is a huge milestone for @RadicalNumerics.
Building it required advancing architectures, pre-training, post-training and inference to make new biological applications possible.
Pre-training meant tokenizing and blending continuous and discrete biological modalities. Post-training adapted that foundation to different applications.
At inference, we’re exploring algorithms for reasoning across biological modalities and allocating test-time compute across selective generation and conditioning steps.
Making these models train and run at scale meant pushing the underlying numerics and systems alongside the modeling. The frontier of biological AI runs all the way down the stack.
We have a cracked team. Really proud of what we’ve built together.
Stefano Massaroli retweeted
I'm excited to share that @tri_dao has joined @RadicalNumerics as a scientific advisor!
Tri and I were labmates at Stanford's Hazy Research, where he pioneered advances in efficient ML systems (FlashAttention).
Scaling AI across multimodal biological data demands entirely new approaches to ML systems, and Tri will help guide our research at this frontier.
Welcome aboard, Tri!
Read more: radicalnumerics.ai/blog/tri-…
Stefano Massaroli retweeted
New research on pretraining data mixing in biology.
At Radical we're huge supporters of driving frontier research in AI and sharing it with the community.
So much cool work at the intersection of biology, this is the next frontier of AI 🧬🔥📈
Stefano Massaroli retweeted
1/5 What does it take to scale pretraining to 20+ data modalities at once? Improved data mixing methods are one important ingredient.
Today, we share how we scale data mixing to thousands of sources for DNA and natural language pretraining of Omnii, our multimodal genome model.
We are building biological intelligence.
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: radicalnumerics.ai/blog/omni…
Stefano Massaroli retweeted
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: radicalnumerics.ai/blog/omni…
Stefano Massaroli retweeted
Genomic design and defensive guardrails are intrinsically linked AI capabilities. Stoked to keep pushing both frontiers with our stellar team!
1/ Leaders of OpenAI, Anthropic, & GDM signed a letter urging Congress to mandate DNA synthesis screening.
But chatbots & agents can't read DNA.
So we built Omnii to defend against natural & AI-designed pathogens.
Blog: radicalnumerics.ai/blog/omni…
Letter: screendna.org
Stefano Massaroli retweeted
Showcasing a critical application of our new frontier genome language model, Omnii.
Omnii can strengthen biodefense pipelines by covering blind spots of existing search-based methods.
1/ Leaders of OpenAI, Anthropic, & GDM signed a letter urging Congress to mandate DNA synthesis screening.
But chatbots & agents can't read DNA.
So we built Omnii to defend against natural & AI-designed pathogens.
Blog: radicalnumerics.ai/blog/omni…
Letter: screendna.org
Stefano Massaroli retweeted
One thing I'm excited about is to build a community of AI researchers to work on biodefense.
It feels similar to what we tried to do for genomics, which eventually led to the creation of the generative genomics field. It wasn't obvious before, yet alone sexy. But hugely, hugely impactful.
There's a lot of solid existing work in biodefense, but missing frontier AI, let's change that.
1/ Leaders of OpenAI, Anthropic, & GDM signed a letter urging Congress to mandate DNA synthesis screening.
But chatbots & agents can't read DNA.
So we built Omnii to defend against natural & AI-designed pathogens.
Blog: radicalnumerics.ai/blog/omni…
Letter: screendna.org
Stefano Massaroli retweeted
Making dangerous DNA is basically a print job nowadays. You design it on a laptop and it shows up at your door. The screening meant to catch it is mostly spell-check: it matches your sequence against a list of known threats. Omnii actually reads. It understands what a sequence would do, even the AI-designed ones meant to sneak past today's tools. First look into our biodefense work @RadicalNumerics below. Much more to come!
1/ Leaders of OpenAI, Anthropic, & GDM signed a letter urging Congress to mandate DNA synthesis screening.
But chatbots & agents can't read DNA.
So we built Omnii to defend against natural & AI-designed pathogens.
Blog: radicalnumerics.ai/blog/omni…
Letter: screendna.org
For a single toxin there are more working disguises than atoms in the universe -- sequences that kill the same way but match nothing on record. You can't screen a list against infinity; bio-defense has to understand function, not compare strings.
That's exactly what Omnii does.
1/ Leaders of OpenAI, Anthropic, & GDM signed a letter urging Congress to mandate DNA synthesis screening.
But chatbots & agents can't read DNA.
So we built Omnii to defend against natural & AI-designed pathogens.
Blog: radicalnumerics.ai/blog/omni…
Letter: screendna.org
Stefano Massaroli retweeted
1/ Leaders of OpenAI, Anthropic, & GDM signed a letter urging Congress to mandate DNA synthesis screening.
But chatbots & agents can't read DNA.
So we built Omnii to defend against natural & AI-designed pathogens.
Blog: radicalnumerics.ai/blog/omni…
Letter: screendna.org
Stefano Massaroli retweeted
Our CEO Eric Nguyen @exnx sat down with @agihouse_org to talk about our origin, mission, and why we exist.
Super fun sitting down with AGI house discussing @RadicalNumerics and our origin story.
Thanks @agihouse_org!
Stefano Massaroli retweeted
What if AI could read and write the language of life itself?
In this interview with AGI House, @exnx, founder of @RadicalNumerics, breaks down how foundation models are being trained on DNA, RNA, and proteins — and why the next frontier of multimodal AI isn't just text or images, but the physical world of human biology.
Stefano Massaroli retweeted
Congrats to the incredible team @RadicalNumerics on this exciting milestone. 🧬 🚀
Together with my co-founders Michael @MichaelPoli6, Stefano @Massastrello and Armin @athmsx, I am excited to announce @RadicalNumerics is emerging from stealth with a $50M seed round to build general biological intelligence.
We’re also sharing an early preview of our new model Omnii, the most powerful genome language model to date.
Omnii preview link:
radicalnumerics.ai/blog/radi…
At Radical Numerics, our mission is to master the code of life, and to drive the frontier of biological AI for both design and defense.
This is our dual mandate, which comes from something our own team helped make possible.
Our founding team trained Evo and Evo 2, the largest biological AI models (40B params) trained on DNA sequences. Trillions of tokens across all of life, from microbes to mammals. It’s fully open source, and created the field now known as generative genomics.
Last year, scientists used Evo to generate the world’s first complete genome from scratch using AI. Turns out it was a bacteriophage—a type of virus. It functioned in the real world, and in this case it was harmless. But for us, it was a clear turning point.
It showed that AI is no longer just analyzing biology. It is on the cusp of generating functional lifeforms. Eventually, AI will have the power to design and control life itself.
That should make all of us incredibly excited, and incredibly uneasy. (Anyone can design DNA with a new function, and have it synthesized and delivered, like something from Amazon Prime).
The same technology that will help us cure cancer is the very technology that might create the next global pandemic, or worse, allow the creation of bioweapons that can wipe out populations.
We believe these forces are inseparable. If you work on the frontier of biology, you have to build technology to safeguard it from its misuse. Existing biosecurity tools are sorely losing the arms race, relying on outdated “have I seen this exact thing before?” style algorithms.
We founded Radical Numerics to turn the tide.
And we can’t do that by training on textbooks and natural language. We must understand the language of biology from the raw physical data itself, to reason across every molecule and modality, from DNA to proteins.
The next frontier for AI goes far beyond chatbots or video generators to models that can understand and engineer life.
Today, we’re previewing Omnii, which is already far surpassing Evo 2, and will continue improving as we scale and add new modalities (training now).
1. For human health, Omnii can read and write whole genomes (more on writing later). It’s state of the art (SOTA) on detecting causal variants for disease, and can rank Alzheimer's mutations zero-shot. We’re partnering with a diagnostics company to use Omnii for early cancer detection (pancreatic and multi-cancer).
2. For defense, Omnii is SOTA at detecting AI-generated pathogens. We benchmarked existing detection tools, and they simply can’t detect the AI-generated ones (“deepfake viruses”). We’re partnering with a US national lab to pilot Omnii for detecting the next pandemic, both natural and AI-generated.
We have a data center full of Blackwells in construction now to build the most powerful biological AI models ever. This mission takes a new kind of AI lab that can actually scale on physical, biological data: new alignment research (mid/post training), scaling long context, building out mech interp teams to dissect what these models learn, new architectures and systems designs, all from the ground up.
Our team is made up of AI researchers and scientists from top labs and institutions (e.g. Stanford, MIT, Google DeepMind), but more importantly, we all share the belief that this is the most important challenge of our lifetime. If you feel similarly, we are hiring. We aim to bring the brightest minds in AI and science together to save lives.
Thanks to our partners on this journey, led by Emergence Capital @emergencecap, with Obvious Ventures @obviousvc, Triatomic @TriatomicCap
, and Patrick Collison @patrickc. Our advisors include Eric Horvitz @erichorvitz, CSO of Microsoft, Chris Re @HazyResearch of Stanford, George Church @geochurch of Harvard, and Andrew Weber @AndyWeberNCB, former Assistant Secretary of Defense for Nuclear, Chemical and Biological Defense Programs.
Fortune article: fortune.com/2026/06/15/exclu…
Jobs: radicalnumerics.ai/join-us
Stefano Massaroli retweeted
Excited to continue the journey with Eric, Stefano, Armin, the team at @RadicalNumerics, and to have the chance to preview our next-generation model, Omnii.
True progress in biological AI demands a culture where the same conversation routinely covers frontier pretraining, systems, and data mixing one moment and complex biology the next. If that sounds like a blast, consider joining us.
Together with my co-founders Michael @MichaelPoli6, Stefano @Massastrello and Armin @athmsx, I am excited to announce @RadicalNumerics is emerging from stealth with a $50M seed round to build general biological intelligence.
We’re also sharing an early preview of our new model Omnii, the most powerful genome language model to date.
Omnii preview link:
radicalnumerics.ai/blog/radi…
At Radical Numerics, our mission is to master the code of life, and to drive the frontier of biological AI for both design and defense.
This is our dual mandate, which comes from something our own team helped make possible.
Our founding team trained Evo and Evo 2, the largest biological AI models (40B params) trained on DNA sequences. Trillions of tokens across all of life, from microbes to mammals. It’s fully open source, and created the field now known as generative genomics.
Last year, scientists used Evo to generate the world’s first complete genome from scratch using AI. Turns out it was a bacteriophage—a type of virus. It functioned in the real world, and in this case it was harmless. But for us, it was a clear turning point.
It showed that AI is no longer just analyzing biology. It is on the cusp of generating functional lifeforms. Eventually, AI will have the power to design and control life itself.
That should make all of us incredibly excited, and incredibly uneasy. (Anyone can design DNA with a new function, and have it synthesized and delivered, like something from Amazon Prime).
The same technology that will help us cure cancer is the very technology that might create the next global pandemic, or worse, allow the creation of bioweapons that can wipe out populations.
We believe these forces are inseparable. If you work on the frontier of biology, you have to build technology to safeguard it from its misuse. Existing biosecurity tools are sorely losing the arms race, relying on outdated “have I seen this exact thing before?” style algorithms.
We founded Radical Numerics to turn the tide.
And we can’t do that by training on textbooks and natural language. We must understand the language of biology from the raw physical data itself, to reason across every molecule and modality, from DNA to proteins.
The next frontier for AI goes far beyond chatbots or video generators to models that can understand and engineer life.
Today, we’re previewing Omnii, which is already far surpassing Evo 2, and will continue improving as we scale and add new modalities (training now).
1. For human health, Omnii can read and write whole genomes (more on writing later). It’s state of the art (SOTA) on detecting causal variants for disease, and can rank Alzheimer's mutations zero-shot. We’re partnering with a diagnostics company to use Omnii for early cancer detection (pancreatic and multi-cancer).
2. For defense, Omnii is SOTA at detecting AI-generated pathogens. We benchmarked existing detection tools, and they simply can’t detect the AI-generated ones (“deepfake viruses”). We’re partnering with a US national lab to pilot Omnii for detecting the next pandemic, both natural and AI-generated.
We have a data center full of Blackwells in construction now to build the most powerful biological AI models ever. This mission takes a new kind of AI lab that can actually scale on physical, biological data: new alignment research (mid/post training), scaling long context, building out mech interp teams to dissect what these models learn, new architectures and systems designs, all from the ground up.
Our team is made up of AI researchers and scientists from top labs and institutions (e.g. Stanford, MIT, Google DeepMind), but more importantly, we all share the belief that this is the most important challenge of our lifetime. If you feel similarly, we are hiring. We aim to bring the brightest minds in AI and science together to save lives.
Thanks to our partners on this journey, led by Emergence Capital @emergencecap, with Obvious Ventures @obviousvc, Triatomic @TriatomicCap
, and Patrick Collison @patrickc. Our advisors include Eric Horvitz @erichorvitz, CSO of Microsoft, Chris Re @HazyResearch of Stanford, George Church @geochurch of Harvard, and Andrew Weber @AndyWeberNCB, former Assistant Secretary of Defense for Nuclear, Chemical and Biological Defense Programs.
Fortune article: fortune.com/2026/06/15/exclu…
Jobs: radicalnumerics.ai/join-us
Stefano Massaroli retweeted
Together with my co-founders Michael @MichaelPoli6, Stefano @Massastrello and Armin @athmsx, I am excited to announce @RadicalNumerics is emerging from stealth with a $50M seed round to build general biological intelligence.
We’re also sharing an early preview of our new model Omnii, the most powerful genome language model to date.
Omnii preview link:
radicalnumerics.ai/blog/radi…
At Radical Numerics, our mission is to master the code of life, and to drive the frontier of biological AI for both design and defense.
This is our dual mandate, which comes from something our own team helped make possible.
Our founding team trained Evo and Evo 2, the largest biological AI models (40B params) trained on DNA sequences. Trillions of tokens across all of life, from microbes to mammals. It’s fully open source, and created the field now known as generative genomics.
Last year, scientists used Evo to generate the world’s first complete genome from scratch using AI. Turns out it was a bacteriophage—a type of virus. It functioned in the real world, and in this case it was harmless. But for us, it was a clear turning point.
It showed that AI is no longer just analyzing biology. It is on the cusp of generating functional lifeforms. Eventually, AI will have the power to design and control life itself.
That should make all of us incredibly excited, and incredibly uneasy. (Anyone can design DNA with a new function, and have it synthesized and delivered, like something from Amazon Prime).
The same technology that will help us cure cancer is the very technology that might create the next global pandemic, or worse, allow the creation of bioweapons that can wipe out populations.
We believe these forces are inseparable. If you work on the frontier of biology, you have to build technology to safeguard it from its misuse. Existing biosecurity tools are sorely losing the arms race, relying on outdated “have I seen this exact thing before?” style algorithms.
We founded Radical Numerics to turn the tide.
And we can’t do that by training on textbooks and natural language. We must understand the language of biology from the raw physical data itself, to reason across every molecule and modality, from DNA to proteins.
The next frontier for AI goes far beyond chatbots or video generators to models that can understand and engineer life.
Today, we’re previewing Omnii, which is already far surpassing Evo 2, and will continue improving as we scale and add new modalities (training now).
1. For human health, Omnii can read and write whole genomes (more on writing later). It’s state of the art (SOTA) on detecting causal variants for disease, and can rank Alzheimer's mutations zero-shot. We’re partnering with a diagnostics company to use Omnii for early cancer detection (pancreatic and multi-cancer).
2. For defense, Omnii is SOTA at detecting AI-generated pathogens. We benchmarked existing detection tools, and they simply can’t detect the AI-generated ones (“deepfake viruses”). We’re partnering with a US national lab to pilot Omnii for detecting the next pandemic, both natural and AI-generated.
We have a data center full of Blackwells in construction now to build the most powerful biological AI models ever. This mission takes a new kind of AI lab that can actually scale on physical, biological data: new alignment research (mid/post training), scaling long context, building out mech interp teams to dissect what these models learn, new architectures and systems designs, all from the ground up.
Our team is made up of AI researchers and scientists from top labs and institutions (e.g. Stanford, MIT, Google DeepMind), but more importantly, we all share the belief that this is the most important challenge of our lifetime. If you feel similarly, we are hiring. We aim to bring the brightest minds in AI and science together to save lives.
Thanks to our partners on this journey, led by Emergence Capital @emergencecap, with Obvious Ventures @obviousvc, Triatomic @TriatomicCap
, and Patrick Collison @patrickc. Our advisors include Eric Horvitz @erichorvitz, CSO of Microsoft, Chris Re @HazyResearch of Stanford, George Church @geochurch of Harvard, and Andrew Weber @AndyWeberNCB, former Assistant Secretary of Defense for Nuclear, Chemical and Biological Defense Programs.
Fortune article: fortune.com/2026/06/15/exclu…
Jobs: radicalnumerics.ai/join-us
Stefano Massaroli retweeted
1/ Introducing GPIC: a Giant Permissive Image Corpus and benchmark for visual generation!
🚀100M VLM-captioned image-text pairs for training
📊1M image-text pairs for benchmarking
🖼️~28 trillion pixels
🤗Centrally Hosted
✅Fully permissive for research + commercial use
Dataset, benchmark and models🧵👇
Co-led with @KyleSargentAI
Stefano Massaroli retweeted
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/rad…
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/rad…
Really proud of the progress we’re making at @RadicalNumerics.
AI has made incredible strides in the world of bits. But science lives in the world of atoms — messy, complex, and grounded in physical reality.
Bridging that gap requires a fundamentally different approach to models, data, and systems.
That’s the direction we’re pushing as a team, and it’s exciting to see it come together.
We’re growing fast — if you want to work on some of the hardest and most meaningful problems in AI, we’d love to talk.
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/rad…