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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 inst

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 API and it's not gonna generate that much GCloud revenue when the model is this tiny.

twothreeone 1y ago
The bean counters rule. There is no corporate vision, no long-term plan. The numbers for the next quarter are driving everything.
- hotstickyballs 1y ago
  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.
  - Onawa 1y ago
    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.
wrsh07 1y ago
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
- Onawa 1y ago
  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.
  - wrsh07 1y ago
    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)
    - roughly 1y ago
      If it came to light that somebody found a way to use this API in a way that is beneficial to society, would you be happy that Google could revoke access? Or unhappy?
      - wrsh07 1y ago
        This is a bit of a false dichotomy. If it's useful, it's good that it was created. We should be happy about the progress. If it's harmful, we should be happy about guardrails. Friction is a useful tool, I don't begrudge people or companies from employing it
    - nimchimpsky 1y ago
      [dead]
- LarsDu88 1y ago
  The predecessor to this model Enformer, which was developed in collaboration with Calico had a weight release and a source release. The precedent I'm going with is specifically in the gene regulatory realm. Furthermore, a weight release would allow others to finetune the model on different datasets and/or organisms.
noname123 1y ago
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)
Ameo 1y ago
> The model source code and weights will also be provided upon final publication. Page 59 from the preprint[1] Seems like they do intend to publish the weights actually [1]: https://storage.googleapis.com/deepmind-media/papers/alphagenome.pdf https://storage.googleapis.com/deepmind-media/papers/alphage...
- LarsDu88 1y ago
  Thank you for this. I did not notice this at the end of the paper.
LarsDu88 1y ago
EDIT: I should have read the paper more thoroughly and been more kind. On page 59, they mention there will be a source and code release. Thank you Deepmind :)
xcodevn 1y ago
> Once the model is fully released, scientists will be able to adapt and fine-tune it on their own datasets to better tackle their unique research questions. This is in the press release, so they are going to release the weights.
bitpush 1y ago
Such a strange position to take indeed. I dont see people clamoring behind Apple when they do proprietary things - iMessage protocol, Bluetooth improvements for Airpods, private APIs in Apple Watch. Apple's "life saving" Apple watch features are only accessible on premium devices. "Privacy is a human right" is also only possible if you buy their devices. It doesnt go around making it free to everyone, and nobody seem to be saying "if you believe in that, then why dont you make it accessible for people from all socio-economic classes?"
deleted 1y ago
[deleted]

twothreeone 1y ago

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

hotstickyballs 1y ago
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.
- Onawa 1y ago
  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.

wrsh07 1y ago

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

Onawa 1y ago
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.
- wrsh07 1y ago
  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)
  - roughly 1y ago
    If it came to light that somebody found a way to use this API in a way that is beneficial to society, would you be happy that Google could revoke access? Or unhappy?
    - wrsh07 1y ago
      This is a bit of a false dichotomy. If it's useful, it's good that it was created. We should be happy about the progress. If it's harmful, we should be happy about guardrails. Friction is a useful tool, I don't begrudge people or companies from employing it
  - nimchimpsky 1y ago
    [dead]
LarsDu88 1y ago
The predecessor to this model Enformer, which was developed in collaboration with Calico had a weight release and a source release. The precedent I'm going with is specifically in the gene regulatory realm. Furthermore, a weight release would allow others to finetune the model on different datasets and/or organisms.

noname123 1y ago

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)

Ameo 1y ago

> The model source code and weights will also be provided upon final publication. Page 59 from the preprint[1] Seems like they do intend to publish the weights actually [1]: https://storage.googleapis.com/deepmind-media/papers/alphagenome.pdf https://storage.googleapis.com/deepmind-media/papers/alphage...

LarsDu88 1y ago
Thank you for this. I did not notice this at the end of the paper.

LarsDu88 1y ago

EDIT: I should have read the paper more thoroughly and been more kind. On page 59, they mention there will be a source and code release. Thank you Deepmind :)

xcodevn 1y ago

> Once the model is fully released, scientists will be able to adapt and fine-tune it on their own datasets to better tackle their unique research questions. This is in the press release, so they are going to release the weights.

bitpush 1y ago

Such a strange position to take indeed. I dont see people clamoring behind Apple when they do proprietary things - iMessage protocol, Bluetooth improvements for Airpods, private APIs in Apple Watch. Apple's "life saving" Apple watch features are only accessible on premium devices. "Privacy is a human right" is also only possible if you buy their devices. It doesnt go around making it free to everyone, and nobody seem to be saying "if you believe in that, then why dont you make it accessible for people from all socio-economic classes?"

deleted 1y ago

[deleted]