23 ms·
From: https://www.nature.com/articles/d41586-024-01383-z https://www.nature.com/articles/d41586-024-01383-z >Unlike RoseTTAFold and AlphaFold2, scientists will
by Metacelsus 2y ago
From: https://www.nature.com/articles/d41586-024-01383-z https://www.nature.com/articles/d41586-024-01383-z
>Unlike RoseTTAFold and AlphaFold2, scientists will not be able to run their own version of AlphaFold3, nor will the code underlying AlphaFold3 or other information obtained after training the model be made public. Instead, researchers will have access to an ‘AlphaFold3 server’, on which they can input their protein sequence of choice, alongside a selection of accessory molecules. [. . .] Scientists are currently restricted to 10 predictions per day, and it is not possible to obtain structures of proteins bound to possible drugs.
This is unfortunate. I wonder how long until David Baker's lab upgrades RoseTTAFold to catch up.
- wslh 2y agoThe AI call is rolling fast, I see similarities with cryptography in the 90s. I have a history to tell for the record, back in the 90s we developed a home banking for Palm (with a modem), it was impossible to perform RSA because of the speed so I contacted the CEO of Certicom which was the unique elliptic curve cryptography implementation at that time. Fast forward and ECC is everywhere.
- l33tman 2y agoThat sucks a bit. I was just wondering why they are touting that 3rd party company in their own blog post, who commercialise research tools, as well. Maybe there are some corporate agreements with them that prevents them from opening the system... Imagine the goodwill for humanity for releasing these pure research systems for free. I just have a hard time understanding how you can motivate to keep it closed. Let's hope it will be replicated by someone who doesn't have to hide behind the "responsible AI" curtain as it seems they are now. Are they really thinking that someone who needs to predict 11 structures per day are more likely to be a nefarious evil protein guy than someone who predicts 10 structures a day? Was AlphaFold-2 (that was open-sourced) used by evil researchers?
- staminade 2y agoIsomorphic Labs? That's an Alphabet owned startup run by Denis Hassabis that they created to commercialise the Alphafold work, so it's not really a 3rd party at all.
- SubiculumCode 2y agoThere is at least some difference between a monitored server and a privately ran one, if negative consequences are possible
- perihelions 2y ago- "Imagine the goodwill for humanity for releasing these pure research systems for free." The entire point[0] is that they want to sell an API to drug-developer labs, at exclusive-monopoly pricing. Those labs in turn discover life-saving drugs, and recoup their costs from e.g. parents of otherwise-terminally-ill children—again, priced as an exclusive monopoly. [0] As signaled by "it is not possible to obtain structures of proteins bound to possible drugs" It's a massive windfall for Alphabet, and it'd be a profound breach of their fiduciary duties as a public company to do anything other than lock-down and hoard this API, and squeeze it for every last billion. This is a deeply, deeply, deeply broken situation.
- karencarits 2y agoWhat is the current status of drugs where the major contribution is from AI? Are they protectable like other drugs? Or are they more copyless like AI art and so on?
- iknowstuff 2y agoIs it broken if it yields new drugs? Is there a system that yields more? The whole point of capitalism is that it incentivizes this in a way that no other system does.
- l33tman 2y agoMy point one level up in the comments here, was not really that the system is broken, but more like asking how you can run these companies (google and that other part run by the deepmind founder, who I bet already has more money than he can ever spend) and still sleep well knowing you're the rich capitalist a-hole commercializing life-science work that your parent company has allocated maybe one part in a million of their R&D budget into creating. It's not like Google is ever going to make billions on this anyway, the alphafold algorithms are not super advanced and you don't require the datasets of gpt4 to train them so others will hopefully catch up.. though I'm also pretty sure it requires GPU-hours beyond what a typical non-profit academia outfit has available unfortunately.. :/
- lupire 2y ago
- Jerrrry 2y agoThe second amendment prevents the government's overreaching perversion to restrict me from having the ability to print biological weapons from the comfort of my couch. Google has no such restriction.
- SubiculumCode 2y ago/s is strong with this one
- gameman144 2y agoI know this is tongue in cheek, but you absolutely can be restricted from having a biological weapons factory in your basement (similar to not being able to pick "nuclear bombs" as your arms to bear).
- timschmidt 2y agoSeems like the recipe for independence, and agreed upon borders, and thus whatever interpretation of the second amendment one wants involves exactly choosing nuclear bombs, and managing to stockpile enough of them before being bombed oneself. At least at the nation state scale. Sealand certainly resorted to arms at several points in it's history.
- gameman144 2y agoThe second amendment only applies to the United States -- it's totally normal to have one set of rights for citizens and another set for the government itself.
- dekhn 2y agoSergey once said "We don't have an army per-se" (he was referring the size of Google's physical security group) at TGIF. There was a nervous chuckle from the audience.
- rolph 2y agoin other words, this has been converted to a novelty, and has no use for scientific purposes.
- ebiester 2y agoNo. It just means that scientific purposes will have an additional tax paid to google. This will likely reduce use in academia but won't deter pharmaceutical companies.
- mhrmsn 2y agoAlso no commercial use, from the paper: > AlphaFold 3 will be available as a non-commercial usage only server at https://www.alphafoldserver.com https://www.alphafoldserver.com, with restrictions on allowed ligands and covalent modifications. Pseudocode describing the algorithms is available in the Supplementary Information. Code is not provided.
- moralestapia 2y agoHow easy/hard would be for the scientific community to come up with an "OpenFold" model which is pretty much AF3 but fully open source and without restrictions in it? I can image training will be expensive, but I don't think it will be at a GPT-4 level of expensive.
- dekhn 2y agoalready did it, https://openfold.io/ https://openfold.io/ https://github.com/aqlaboratory/openfold https://github.com/aqlaboratory/openfold https://www.biorxiv.org/content/10.1101/2022.11.20.517210v1 https://www.biorxiv.org/content/10.1101/2022.11.20.517210v1 https://lupoglaz.github.io/OpenFold2/ https://lupoglaz.github.io/OpenFold2/ https://www.biospace.com/article/releases/openfold-biotech-ai-research-consortium-releases-soloseq-and-multimer-an-integrated-protein-large-language-model-with-3d-structure-generation/ https://www.biospace.com/article/releases/openfold-biotech-a... I really have to emphasize that transformers have literally transformed science in only a few years. Truly extraordinary.
- moralestapia 2y agoOh, nice! Thanks for sharing.
- p3opl3 2y agoYes, because that's going to stop competitors.. it's why they didn't release code I guess. This is yet another large part of a biotech related Gutenberg moment.
- 2y ago
- ranger_danger 2y agoNot just unfortunate, but doesn't this make it completely untrustable? How can you be sure the data was not modified in any way? How can you verify any results?
- dekhn 2y agoYou determine a crystal structure of a known protein which does not previously have a known structure, and compare the prediction to the experimentally determined structure. There is a biennial (biannual?) competition known as CASP where some new structures, not yet published, are used for testing predictions from a wide range of protein structure prediction (so, basically blind predictions which are then compared when the competition wraps up). AlphaFold beat all the competitors by a very wide margin (much larger than the regular rate of improvement in the competition), and within a couple years, the leading academic groups adopted the same techniques and caught up. It was one of the most important and satisfying moments in structure prediction in the past two+ decades. The community was a bit skeptical but as it's been repeatedly tested, validated, and reproduced, people are generally of the opinion that DeepMind "solved" protein structure prediction (with some notable exceptions), and did so without having the solve the full "protein folding problem" (which is actually great news while also being somewhat depressing).
- ranger_danger 2y agoBy data I meant between the client and server, nothing actually related to how the program itself works, but just the fact that it's controlled by a proprietary third party.
- deleted 2y ago[deleted]
- tepal 2y agoOr OpenFold, which is the more literal reproduction of AlphaFold 2: https://github.com/aqlaboratory/openfold https://github.com/aqlaboratory/openfold
- LarsDu88 2y agoTime for an OpenFold3? Or would it be an OpenFold2?
- photochemsyn 2y agoWell, it's because you can design deadly viruses using this technology. Viruses gain entry to living cells via cell-surface receptor proteins whose normal job is to bind signalling molecules, alter their conformation and translate that external signal into the cellular interior where it triggers various responses from genomic transcription to release of other signal molecules. Viruses hijack such mechanisms to gain entry to cells. Thus if you can design a viral coat protein to bind to a human cell-surface receptor, such that it gets translocated into the cell, then it doesn't matter so much where that virus came from. The cell's firewall against viruses is the cell membrane, and once inside, the biomolecular replication machinery is very similar from species to species, particularly within restricted domains, such as all mammals. Thus viruses from rats, mice, bats... aren't going to have major problems replicating in their new host - a host they only gained access to because some nation-state actors working in collaboration on such gain-of-function research in at least two labs on opposite sides of the world with funds and material provided by the two largest economic powers for reasons that are still rather opaque, though suspiciously banal... Now while you don't need something like AlphaFold3 to do recklessly stupid things (you could use directed evolution, making millions of mutatad proteins, throwing them at a wall of human cell receptors and collecting what stuck), it makes it far easier. Thus Google doesn't want to be seen as enabling, though given their prediliction for classified military-industrial contracting to a variety of nation-states, particularly with AI, with revenue now far more important than silly "don't be evil" statements, they might bear watching. On the positive side, AlphaFold3 will be great for fields like small molecular biocatalysis, i.e. industrial applications in which protein enzymes (or more robust heterogenous catalysts designed based on protein structures) convert N2 to ammonia, methane to methanol, or selectively bind CO2 for carbon capture, modification of simple sugars and amino acids, etc.
- niemandhier 2y agoThe logical consequence is to put all scientific publications under a license that restricts the right to train commercial ai models on them. Science advances because of an open exchange of ideas, the original idea of patents was to grant the inventor exclusive use in exchange for disclosure of knowledge. Those who did not patent, had to accept that their inventions would be studied and reverse engineered. The „as a service“ model, breaks that approach.
- dwroberts 2y agoThis turns it into a tool that deserves to be dethroned by another group, frankly. What a strange choice.
- deleted 2y ago[deleted]