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June 15, 2026
Funding & Investment

Radical Numerics launches with $50M to build general biological intelligence

Overview

, an artificial intelligence research lab building what it calls general biological intelligence, launched today with $50 million in funding to scale up its models and hire frontier AI talent. The company is the work of the team behind generative genomics, the field built around Evo, the first AI model able to read [... ] The post Radical Numerics launches with $50M to build general biological intelligence appeared first on SiliconANGLE.

Key Takeaways

  • SiliconANGLE UPDATED 18:13 EDT / JUNE 15 2026 AI Radical Numerics launches with $50M to build general biological intelligence by Duncan Riley Radical Numerics Inc.

    The company is the work of the team behind generative genomics, the field built around Evo, the first AI model able to read and write DNA at large scale and the largest fully open-source AI project in any domain.

  • Radical Numerics says early results show Omnii setting a new state of the art in identifying causal regulatory variants and transferring zero-shot to experimental settings.

    Without specific training, the model recovers experimentally validated functional variants at genetic locations tied to Alzheimer's disease and it also leads on detecting AI-generated or AI-manipulated pathogens.

  • Biology will be the most consequential application of AI.

    " Nguyen founded the company with Chief AI Scientist Michael Poli, President Stefano Massaroli and Chief Technology Officer Armin Thomas.

  • Emergence Capital led the seed round.

    Obvious Ventures, Triatomic Capital Private LP, Factory and First Spark Ventures also took part.

  • About SiliconANGLE Media SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-time audience engagement.

Stats & Key Facts

  • #, an artificial intelligence research lab building what it calls general biological intelligence, launched today with $50 million in funding to scale up its models and hire frontier AI talent.
  • #, an artificial intelligence research lab building what it calls general biological intelligence, launched today with $50 million in funding to scale up its models and hire frontier AI talent.
Radical Numerics launches with $50M to build general biological intelligence

SiliconANGLE UPDATED 18:13 EDT / JUNE 15 2026 AI Radical Numerics launches with $50M to build general biological intelligence by Duncan Riley Radical Numerics Inc. , an artificial intelligence research lab building what it calls general biological intelligence, launched today with $50 million in funding to scale up its models and hire frontier AI talent. The company is the work of the team behind generative genomics, the field built around Evo, the first AI model able to read and write DNA at large scale and the largest fully open-source AI project in any domain.

Evo and its successor Evo 2 made the cover of Science and Nature and external scientists later used the model to generate the first complete AI-designed genome, a bacteriophage that infects bacteria and is harmless to humans. Radical Numerics is building a class of models that learn directly from biological data across DNA, RNA, proteins and beyond, folding the separate strands of biology into a single system. The company argues that multimodal models reasoning across every dimension of biology at once can open paths to cancer diagnostics, drug target identification and biosecurity that single-modality models cannot reach.

Alongside the launch, the company previewed Omnii, its next-generation genomic language model. Radical Numerics says early results show Omnii setting a new state of the art in identifying causal regulatory variants and transferring zero-shot to experimental settings. Without specific training, the model recovers experimentally validated functional variants at genetic locations tied to Alzheimer's disease and it also leads on detecting AI-generated or AI-manipulated pathogens.

For more details please read the original article at SiliconANGLE AI.

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