Radical Numerics

1/ With Omnii Diagnostics, we asked whether a multimodal genome language model could help find cancers whose signals in blood are too faint for current classifiers.

We adapted Omnii-1 to a biomarker never seen in pretraining. In a test cohort, Omnii's features improved early-stage cancer detection

1/10 Introducing Omnii Genome, one of eight Advances built on Omnii-1.

A single generalist model now outperforms leading specialized models (AlphaGenome) in linking genetic changes to gene activity and mapping regulatory interactions.

These capabilities help make sense of the 98% of the human genome that doesn’t code for proteins

How Omnii-1 works:

Launching Omnii-1, our most powerful genome language model yet.

1/8 Does text-to-image generation need language pretraining?

Today, we share Halcyon, a family of early-fusion, base models trained from scratch. Halcyon outperforms strong late-fusion baselines with up to 275× less pretraining compute. Models and recipes are open.

Halcyon is part of a research program at Radical Numerics on the science of multimodal pretraining and scaling.

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.