alt Hacker NewsAll of what you said makes sense from the perspective of a product manager working for a for-profit company trying to maximize profit either today or eventually.
But the submission blog post writes:
> To advance scientific research, we’re making AlphaGenome available in preview via our AlphaGenome API for non-commercial research, and planning to release the model in the future. We believe AlphaGenome can be a valuable resource for the scientific community, helping scientists better understand genome function, disease biology, and ultimately, drive new biological discoveries and the development of new treatments.
And at that point, they're painting this release as something they did in order to "advance scientific research" and because they believe "AlphaGenome can be a valuable resource".
So now they're at a cross-point, is this release actually for advancing scientific research and if so, why aren't they doing it in a way so it actually maximizes advancing scientific research, which I think is the point parent's comment.
Even the most basic principle for doing research, being able to reproduce something, goes out the window when you put it behind an API, so personally I doubt their ultimate goal here is to serve the scientific community.
Edit: Reading further comments it seems like they've at least claimed they want to do a model+weights release of this though (from the paper: "The model source code and weights will also be provided upon final publication.") so remains to be seen if they'll go through with it or not.
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But to add some historical context.
Similarly with alpha Go they claimed to do it "to advance go" and help go community, but they played Lee se dol, released few curated self play games, collected publicity and abandoned go with no artifacts like source or weights.
But in hindsight their paper turned out to be almost 100% reproducible and resulted in super-human open-source alternative less than a year later.
So the story might repeat here. And they will achieve started goal without releasing anything
Key question is the license they attach to model and weights. I have been seeing an increasing amount of releases in this space under non-commercial licenses.
I think companies in the space should either totally open source or not publish at all.
I can see publishing like this as achieving one (or more) of a several objectives:
1. Marketing software to for sales / licensing
2. Marketing startup to investors
3. Crowdsourcing use cases or product features from academia
Now here are the problems with those:
1. Selling software (exclusively) to drug companies is a terrible business model. Very low ceiling there. You can make more from one drug.
2. Indicates company focus is producing models and not drugs. See point one.
3. Computational labs want to release open source, so not viable to build on restricted tooling. Experimental labs may just be using to algo-wash prior hypotheses / biases.
Now weigh against disadvantage of letting competitors know what you are working on, how far you have progressed, as well as your methods.
I feel like this take is missing a sense of balance. You can have a goal of advancing scientific research while also still making money. You don’t have to choose one extreme end of the scale.
I’d argue that the product providing some monetary value for Google will help ensure that this team doesn’t get moved some more profitable project instead. That way they can continue improving this tool and make more tools like it in the future.
To be clear: I agree that opening up model + weights makes it possible for third parties to distill or fine tune
If you look at the frenzy of activity that happened after midjourney became accessible, that was awesome for everyone. Midjourney probably got help running their model efficiently and a ton of progress was quickly made.
I'm pretty sympathetic to a company doing a windowing strategy: prepare the API as a sort of beta release timed with the announcement. Spend some time cleaning up the code for public release (at Google this means ripping out internal dependencies that aren't open source), and then release a reference inference implementation along with the weights.
That's pretty reasonable. I wanted to push back on this idea that "the reason Google isn't dropping model + weights is because the corporate screws are coming down hard"
Google isn't waiting to release the weights so that they can profit from this. It's essentially the first step in the process, and serving via API gives them valuable usage data they they might not get if/when it's open sourced