DeepMind and AlphaFold are clearly moving in a closed-source direction, since they created Isomorphic Labs as a division of Alphabet essentially focused on doing this stuff closed source. In theory it seems nice for academic tools to have an open source version, although I'm not familiar enough with this field to point to a specific benefit of it.
So what's your plan for the company itself, do you intend to continue working on this open source project as part of your business model, or was it more of a one-off? Your website seems very nonspecific about what exactly you intend to be selling.
fngjdflmdflg
Have you considered publishing your own paper about your implementation? It would make it easier to cite in the literature later on. Would major journals accept such a paper? I would assume they would if they really had questions about reproducibility.
dwayne_dibley
Hi, how are predictions verified? Does one still do experimental techniques (X-ray crystallography, cryogenic-em etc.) one you have the prediction? Or are predictions so close to reality you can progress without experiment?
boldlybold
Thanks for releasing this, I've been looking forward to a truly open version I can use in a commercial setting. What a way to launch the company!
dekhn
You probably want to change the name of this implementation as it's not truly AlphaFold3. I wouldn't be surprised if you got a C&D from DM for using the name.
snolbert
Who would've thought only releasing pseudo-code isn't good enough...glad to see the scientific immune system fighting back against closed-source science. Your move Google.
benreesman
I did a very brief stint on computational proteomics. That stuff is absolutely next level.
westurner
Does this win the Folding@home competition, or is/was that a different goal than what AlphaFold3 and ligo-/AlphaFold3 already solve for?
> making it the world's first exaflop computing system
londons_explore
If I'm understanding correctly, the model code itself is only a tiny proportion of the challenge. The training compute and training data are far bigger parts.
Google has access to training compute on a scale perhaps nobody else has.
ck_one
What's your next step? Why did you decide to focus on enzyme design?
DeepMind and AlphaFold are clearly moving in a closed-source direction, since they created Isomorphic Labs as a division of Alphabet essentially focused on doing this stuff closed source. In theory it seems nice for academic tools to have an open source version, although I'm not familiar enough with this field to point to a specific benefit of it.
So what's your plan for the company itself, do you intend to continue working on this open source project as part of your business model, or was it more of a one-off? Your website seems very nonspecific about what exactly you intend to be selling.