Geodesic Intelligence

Build AGI that discovers the shortest path from biology to medicines

[Geodesic Intelligence @Geodesiclab]

NovaDDE Plus is now live!

Built for scientists who use AI for drug discovery every day — more compute, priority access, concurrent runs, API access, and end-to-end campaign execution.

$30/month and sign up by September 25 to get your first month free.

Our goal is simple: put the most powerful AI for drug discovery into the hands of every scientist.

https://t.co/eOpEF3XKoQ

[Geodesic Intelligence @Geodesiclab]

We’re launching the Geodesic Grand Challenges.

What are the hardest questions in drug discovery that, if solved, could change what’s possible over the next 5–10 years?

We’re asking you to help define them.

Selected questions will become official Geodesic Grand Challenges. Each selected contributor receives 10,000 Geodesic credits.

Once the challenges are selected, we’ll open a call for solutions, with a $1 million prize for a verified solution to each challenge.

The next breakthrough starts with the right question.

Submit yours！
https://t.co/hQZUWhuqyN

[Geodesic Intelligence @Geodesiclab]

6/ Today is Day 1 for Geodesic Intelligence.

NovaDDE is live.
NovaAtom-Lite-Preview is here.
Larger NovaAtom models are coming.
Our wet lab is scaling.
And there is much more ahead.

We’re building AI to create medicines, and we’re hiring exceptional people to build it with us.

Explore NovaDDE: https://t.co/o42snNpXK9
Join us: https://t.co/LqdvL4OWFf

[Geodesic Intelligence @Geodesiclab]

1/ Today, we’re introducing Geodesic Intelligence, and launching NovaDDE and NovaAtom-Lite-Preview.

Geodesic is building an AI-native platform for protein therapeutics, building AGI for drug discovery to find the shortest path from biology to medicines.
https://t.co/SNuR5NPVxs

[Geodesic Intelligence @Geodesiclab]

5/ But computation alone isn’t enough. Biology has to work in the real world.

That’s why we’re building our own wet-lab capabilities alongside our AI stack, and creating a closed learning loop between AI and the physical world:

AI → Design → Experiment → Learn → Repeat.

Better models generate better experiments. Better experiments generate better data. Better data builds better models.