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AlphaGenome: AI for better understanding the genome

deepmind.google

121–130 of 193 posts

Re: AlphaGenome: AI for better understanding the genome

#122

I wish there's some breakthrough in cell simulation that would allow us to create simulations that are similarly useful to molecular dynamics but feasible on modern supercomputers. Not being able to see what's happening inside cells seems like the main blocker to biological research.

You may enjoy this, from a top-down experimental perspective (https://www.nikonsmallworld.com/galleries/small-world-in-mot...). Only a few entries so far show intracellular dynamics (like this one: https://www.nikonsmallworld.com/galleries/2024-small-world-i...), but I always enjoy the wide variety of dynamics some groups have been able to capture, like nervous system development (https://www.nikonsmallworld.com/galleries/2018-small-world-i...); absolutely incredible.

Re: AlphaGenome: AI for better understanding the genome

#123

You know the corporate screws are coming down hard, when the model (which can be run off a single A100) doesn't get a code release or a weight release, but instead sits behind an API, and the authors say fuck it and copy-paste the entirety of the model code in pseudocode on page 31 of the white paper. Please Google/Demis/Sergei, just release the darn weights. This thing ain't gonna be curing cancer sitting behind an…

This is a strange take because this is consistent with what Google has been doing for a decade with AI. AlphaGo never had the weights released. Nor has any successor (not muzero, the StarCraft one, the protein folding alphafold, nor any other that could reasonably be claimed to be in the series afaik)

You can state as a philosophical ideal that you prefer open source or open weights, but that's not something deepmind has prioritized ever.

I think it's worth discussing:

* What are the advantages or disadvantages of bestowing a select few with access?

* What about having an API that can be called by anyone (although they may ban you)?

* Vs finally releasing the weights

But I think "behind locked down API where they can monitor usage" makes sense from many perspectives. It gives them more insight into how people use it (are there things people want to do that it fails at?), and it potentially gives them additional training data

Re: AlphaGenome: AI for better understanding the genome

#124

You know the corporate screws are coming down hard, when the model (which can be run off a single A100) doesn't get a code release or a weight release, but instead sits behind an API, and the authors say fuck it and copy-paste the entirety of the model code in pseudocode on page 31 of the white paper. Please Google/Demis/Sergei, just release the darn weights. This thing ain't gonna be curing cancer sitting behind an…

The bean counters rule. There is no corporate vision, no long-term plan. The numbers for the next quarter are driving everything.

I can guarantee you that some smart person actually thinks that the opportunity size is measured as a fraction of the pharmaceutical industry market cap.

Re: AlphaGenome: AI for better understanding the genome

#125

I wish there's some breakthrough in cell simulation that would allow us to create simulations that are similarly useful to molecular dynamics but feasible on modern supercomputers. Not being able to see what's happening inside cells seems like the main blocker to biological research.

Why simulate? We can already do it experimentally

Re: AlphaGenome: AI for better understanding the genome

#126

You know the corporate screws are coming down hard, when the model (which can be run off a single A100) doesn't get a code release or a weight release, but instead sits behind an API, and the authors say fuck it and copy-paste the entirety of the model code in pseudocode on page 31 of the white paper. Please Google/Demis/Sergei, just release the darn weights. This thing ain't gonna be curing cancer sitting behind an…

For AlphaFold3 (vs. AlphaFold2 which was 100% public), they released the weights if you are an affiliate with an academic institution. I hope they do the same with AlphaGenome. I don't even care about the commercial reasons or licensing fees, it's more of a practical reason that every research institution will have an HPC cluster which is already configured to run deep learning stuff can run these jobs faster than the Google API.

And if they don't, I'm not sure how this will gain adoption. There are tons of well-maintained and established workflows out there in the cloud and on-prem that do all of these things AlphaGenome claim to do very well - many that Google promotes on their own platform (e.g., GATK on GCP).

(People in tech think people in science are like people in tech just jump on the latest fads from BigTech marketing - when it's quite opposite it's all about whether your results/methods will please the reviewers in your niche community)

Re: AlphaGenome: AI for better understanding the genome

#127
"To ensure consistent data interpretation and enable robust aggregation across experiments, metadata were standardized using established ontologies."

Can't emphasize enough about how DNA requires human data curation to make things work, even from day one alignments models were driven based on biological observations. Glad to see UBERON, which represents a massive amount of human insight and data curation of what is for all intents and purposes a semantic-web product (OWL based RDF at the heart) playing a significant role.

Re: AlphaGenome: AI for better understanding the genome

#128
post #123

You know the corporate screws are coming down hard, when the model (which can be run off a single A100) doesn't get a code release or a weight release, but instead sits behind an API, and the authors say fuck it and copy-paste the entirety of the model code in pseudocode on page 31 of the white paper. Please Google/Demis/Sergei, just release the darn weights. This thing ain't gonna be curing cancer sitting behind an…

This is a strange take because this is consistent with what Google has been doing for a decade with AI. AlphaGo never had the weights released. Nor has any successor (not muzero, the StarCraft one, the protein folding alphafold, nor any other that could reasonably be claimed to be in the series afaik) You can state as a philosophical ideal that you prefer open source or open weights, but that's not something deepmind…

I think that from a research/academic view of the landscape, building off a mutable API is much less preferred than building of a set of open weights. It would be even better if we had the training data, along with all code and open weights. However, I would take open weights over almost anything else in the current landscape.

Re: AlphaGenome: AI for better understanding the genome

#129

Earlier quoted context omitted.

The bean counters rule. There is no corporate vision, no long-term plan. The numbers for the next quarter are driving everything.

I can guarantee you that some smart person actually thinks that the opportunity size is measured as a fraction of the pharmaceutical industry market cap.

Doesn't matter if that person can't convince the bean counters and lawyers that it is in the company's long-term interest to release the "proprietary" data.

Re: AlphaGenome: AI for better understanding the genome

#130
post #128
post #123

Earlier quoted context omitted.

This is a strange take because this is consistent with what Google has been doing for a decade with AI. AlphaGo never had the weights released. Nor has any successor (not muzero, the StarCraft one, the protein folding alphafold, nor any other that could reasonably be claimed to be in the series afaik) You can state as a philosophical ideal that you prefer open source or open weights, but that's not something deepmind…

I think that from a research/academic view of the landscape, building off a mutable API is much less preferred than building of a set of open weights. It would be even better if we had the training data, along with all code and open weights. However, I would take open weights over almost anything else in the current landscape.

If it came to light that somebody found a way to use this API in a way that is harmful to society would you be happy that Google could revoke access? Or unhappy?

This is a real tradeoff of freedom vs _. I agree that I'm not always a fan of Google being the one in control, but I'm much happier that they are even releasing an API. That's not something they did for go! (Of course there was a book written so someone got access)

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