The cost in preventable deaths, had we been continuing protein research instead of pouring the world’s resources into a fancy autocorrect, is incalculable.
Actual, real, machine-learning artificial-intelligence. Not this sycophantic human mimic shit everybody’s fallen head over heels for. At the very bare-minimum comparison, AlphaFold had an established use-case.
People don’t buy products anymore. They’re too poor to care about. Businesses sell to governments and other businesses now and couldn’t care less what you want or think.
No they are not actively working on the same area, and yes fuck google, because this exact example is as clear as it gets why we should burn every database that google owns.
deepmind by principle was meant to offer global scientific communities a tool that helped with research, cutting down errors and trial time massively, it was a free, open-scientific prediction model.
Deepmind offered its different versions of source code for free to universities and science based communities, tried to help develop and accelerate its research “non commercial rule applied”.
Deepmind was non profit, open access that had zero return value on licensing.
isomorphic lab, is a venture capitalist company that relies on hiding its research, recently get funded 2billion by the most evil zionist, the one and only, the scum of the sewers …. Joshua Kushner.
Yes, letting a person own a means of production leads to greed and they, unlike government, are not able to be voted out. They just grow more powerful and stupid drunk on wealth and they do stupid shit that destroys economies and environments and societies and surround themselves with yes men so they never have to hear about the consequences of their actions from anyone “important”.
Elon musk should not own the space program. Jeff Bezos should not own all retail. Palmer Luckey should be “disrupting” defense.
You are not a capitalist, you are a worker with Stockholm syndrome. Fuck capitalism, it’s time for it to go. It’s antiquated and unnecessary.
I installed Google Earth on every machine (thanks ninite) since it came out and think I only opened it a few times during the first year to show it to people lol
Correct me if I’m wrong, but didn’t AlphaFold basically solve protein folding, as in their master database of folds is now complete? Doesn’t it make sense to move on at this point?
It does not do everything perfectly. There’s many abnormalities to protein structures and research in that area of biology is certainly far from done too. So there is definitely room to improve it further.
If only genetic sequences were so finite. And what happens when researchers are developing a new protein that never existed before? Protein folding is NP-hard—even if P=NP is solved, protein folding may still be a challenge. It is likely that there will always be a need for software like this, and that the software will need periodic updates as new sequence behaviors come to light.
That said, as another comment points out, Google is merely stepping back from the AlphaFold project, which will continue without their funding or oversight.
AlphaFold does a couple of things. It’s capability in predicting how a single protein will be folded tends to be quite nice, but organisms often rely on complex interactions between proteins. It has a feature to calculate the folding of two or more proteins with each other, which is incredibly important to understand more complex interactions in various processes in the human body, as well as drug interactions.
It is also easier to create a database of folding for all normal proteins in the human body. Any change in your DNA, which is somewhat more common than people think, can modify your proteins to one that has not been seen before, since many proteins can have chunks that don’t do anything but act as filler. Except, when those changes affect a bit that doesn’t act as filler or make the filler suddenly interact with other proteins or structures, like making the protein fold entirely differently or become hydrophobic where it shouldn’t be, then you’re in trouble.
These modified proteins need to be analyzed as well and when their primary function in your body is to interact with other proteins, then this multimer functionality is critical. And that certainly needs much more research, as it is very, very far from perfect.
It’s still very important for genetic testing. If someone has a genetic mutation, it can be difficult to know whether that mutation is going to cause its associated protein to stop working or not. Even if we know all of the “normal” proteins in the body, there are countless variants based on people’s specific genetic differences that may or may not have major effects on how those proteins fold, which in turn can have major effects on those individuals’ health.
So I finally let my Android Auto update from Google Assistant to Gemini, which it’s been wanting for months.
First thing I did was prompt it to play a specific artist, just like I do at least once a week since it forces me to use the voice activation instead of the on screen keyboard, even when there are passengers that can type. It responded saying it is not capable of playing music at all. Wtf.
So I then rephrase and tell it to play the artist on YouTube Music… And it does so, but doesn’t get the artist even close to correct. I had to prompt it 5 times with varying emphasis to get it to finally get it right.
So literally the first thing it did wa like to me… and then it worked correctly less than 20% of the time… So much better than the Assistant it replaced that never gave me a problem. Totally better.
Same thing with swapping to Gemini on the phone. First thing and only thing I asked for was to set a reminder alarm. But Gemini couldn’t talk to the clock app and refused. In the trash it went.
It has to do that to know when you say a keyword like “hey Google”. I just wonder what other keywords it’s listening to and using to serve ads or profile me as a user.
At least all the things NSA and CIA are interested at the time…
All new things always have an intelligence aspect to it:
Find my network: Find any device globally by its ”anonymized” identifier. Make a device you hack remotely send these BLE pings and voilà, some Apple or Google device is surely nearby to hear it and tell you where it is.
Voice assistants: Hear what people talk about privately by injecting new wake-up words like ”Trump”. Cannot be used en masse yet perhaps because it’s usually only the device detecting the trigger word, and sending ”uncertain interpretations” too often would get noticed by someone.
LLM chats: Well the same as Google searches etc. historically but now way more nuanced and with more context of what the target in intending/thinking. Building a psychological profile of them through features like ”memory”. And as LLM is such an undeterministic black box, you can easily get away with injecting all sorts of ideas through its responces.
We have seen the step by step dance into dystopia for decades now. Tech is only improving our society as a side effect of monitoring people or charging more money from people.
This is why I occasionally send close friends obviously stupid messages with a ton of keywords, to throw some more noise into the surveillance aperatus.
I remember using Google Now on my Galaxy Nexus a lot and actually finding it useful. Then Google pushed for Assistant and it was a dumpster fire. Glad to see that big G is still up to the same shenanigans.
Absolutely true. Tech companies and others love to conflate them. It’s also a money thing: Idiots with too much money (that we should probably tax to use for something useful) want to invest in AI, so if I’ve been working on a project that needs funds, I just rebrand it as “AI”, even if it just runs on more traditional ML principles.
I kid you not, yesterday while reading about the ai bubble and the datacenters boom i was thinking maybe this is THE filter.
Not a nuclear winter, not the angry alien or the big scary asteroid.
Just a fucking chatbot wasting all the water and power.
We truly live in a really boring dystopia.
If anything, it’s climate change and failing systems due to late-stage capitalism, followed by some form of fascism or other authoritarian system, aided by AI to stay in power.
Electricity use from AI data centers on a global scale isn’t impactful enough to make that much of a difference, it’s more of a local issue, at least at the current rate. Water use is entirely negligible outside of the surrounding area, animal agriculture uses more than a thousand times as much as all data centers combined.
I went into hyperbole there, my bad. I agree wholeheartedly with your reply.
Admittedly, I have a bias here, since using water for food production feels more justified. Same with some industries. But I concede and agree that meat is not the most efficient way nor the most ethical source of food.
I think data centers rub me the wrong way because, for me, they are the straw that broke the camel’s back.
We see how lots of countries pull out of the fight against climate change (not that they were really fighting it, but at least they seemed to care a little) and now they waste more resources on things that are, from my point of view, not productive nor useful to most people.
(Ethics aside, my view on Gen AI is that it is a tech that is not mature enough, and that the use of brute force to make it better is a waste of resources)
Oh, no need to apologize, I fully agree with your overall view on AI data centers, and your observations of how politicians don’t even nominally stand against climate change anymore. It’s just become very blatant very rapidly, and it’s easiest to see with data centers.
The way people prioritize different causes for climate change and environmental issues does frustrate me at times, so I appreciate the reply :)
To be clear, I wasn’t necessarily disagreeing about AI’s utility, just about how protein fold AI isn’t the same as LLM AI; we’ve used computer models for predictions of protein structure and genetic mutation severity for a while, though they have always been taken with a grain of salt that I fear is no longer being done - a prediction is still a prediction, after all. Doctors were already incorrectly confusing computer model predictions of genetic mutation severity for positive test results back when I was working as a genetic counselor in the 2010’s - my concern is that the widespread trust of “AI” is only going to exacerbate that.
I’m a bit confused, though. The AI doing it was AlphaFold, which is shutting down. Shouldn’t your statement be AI was already doing it? Gemini is an LLM - not the same type of thing as AlphaFold, despite the fact that they’re both called “AI,” which was the cause of my original argument. The AI that was doing the protein fold prediction is being replaced with an “AI” that can’t. It looks like there’s still RoseTTAFold, but losing the frontrunner is still not great when it’s shutting down to focus more on LLM’s.
The article also talks about a spinoff of AlphaFold……
I didn’t click into what that spinoff was but maybe an even better headline is “for profit company creates a free AI to predict protein folding and is moving to monetize it”
It’s a actually fairly similar to LLMs architecturally. Tokens go in, pretrained transformers do black box magic, tokens come out.
Advancements in one may very well carry over to the other so maybe there’ll be an alphafold 4 one day but for now universities have access to 3 and can run it if they have the compute.
AlphaFold uses a combination of machine learning and physics simulations to predict the shape of a protein given its chemical formula.
Gemini is a Large Language Model which uses machine learning to predict text completion.
They both use “machine learning” but the machine learning models are wildly different. Machine learning is a technique that’s basically a fancy curve fitting approach. The curve AlphaFold is trained to mimic maps chemical formulas to shapes, while the curve Gemini mimics maps a text input to probabilities for predictions of the next letter(s).
It’s kind of a marvel that we all have the bulk of human knowledge at our fingertips, and instead of noble pursuits we largely use it for social manipulation and power grabs.
I guess there is just more population control in misinformation than there is in curing disease.
We just need a blanket ban on generative AI. The societal costs are just too high, we can’t bear it. We can continue on our path like this for years and dig ourselves into a deeper hole before admitting it, or we could just admit it now and save ourselves the pain.
So instead of continuing a project that could cure diseases and help understand human biology they’ll focus on a system I use for asking questions like “What adhesive is best to attaching siding trim?”
Exactly. No offense to the average liberal but this whole “but what will happen to all the compute and data centers when the AI bubble bursts” is so tiring.
Firstly, the fascist regime will absolutely bail out a few key companies. Secondly, all those centers will be used for mass surveillance, war games, predictive policing (and population control), and all the other shit in the fascist grabbag.
There is absolutely a level of speculation to this insane bubble. I’m not going to sit here and tell you to ignore the evidence of your eyes. Obviously there is an aspect of short sighted money chasing (pretty standard capitalist bs), and there is absolutely an aspect of corporate greed and the companies trying to outbuild, outcompute one another. But for the people at the top (Miller, Thiel, Elston, Musk maybe, and others), they absolutely have long term goals. They are definitely getting rich off the bubble and benefiting from the short term insanity, but there is more there.
These neofeudalist assholes want to see us in chains, under their ever watchful AI eyes.
Mass surveillance, is of questionable value beyond just creating a database of footage. Police DON’T aim to “solve all crime and be good guys”. They barely aim for investigating all crimes, and most crime they’d just need a time and date for to look at the footage only IF and WHEN a crime is reported. They’re not going to spend police resources to have cops sift through footage the AI has guessed there’s crime in every day. That would just cost time/money. At best it might be used for facial recognition at protests - but facial recognition systems predate AI, so it’s superfluous.
war games, takes appropriate training data which is increadibly difficult to simulate and get the right answers from. There are already various war-gaming departments who have been trying to do this. The YouTube channel People Make Games has an episode on this - war just has so many variables that beyond the basics of troops numbers and geography it’s kind of difficult. But even if this becomes a use, it’s niche, it wouldn’t require a large amount of compute, each country only has one military… And spending on research projects (eg. DARPA) isn’t new. It’s not enough to be a “big win” for 3 AI giants, it’s more a step back to where they came from.
predictive policing (and population control) hang on, wasn’t this your first example? Again, mis-matches and police time checking the AI are going to cost too much, and those programs would cost big money in lawsuits and time. It’d be the first program cut by most departments.
I see nothing realistic here.
More likely uses are jobs that burn through a lot of copy writers: spam/marketing, realestate ads, search engines and researching, little buddies and toys, publishing (sadly), video games, weather bureaus, text transcription and translation, scams and telemarketing. Things there’s lots of data on, and close to zero risk with.
You’re assuming that the police will actually sift through footage in a meaningful way instead of just trusting faulty, fascist trained ai algorithms. Like that one guy who got mistaken by an AI profiling systen at a casino for someone who was kicked out, and when handed his license to prove he was a different person, the cops LITERALLY just refused to believe the evidence of their eyes. They took him to jail because the almighty machine could never be wrong. The story is wild: thecivilrightslawyer.com/…/ai-software-tells-cops….
Your examples are about AIs costing police departments money, which is what I’m saying. I’m saying it won’t be a viable use long term, BECAUSE of the blow back in time, lawsuits, and money.
As I said earlier; “Again, mis-matches and police time checking the AI are going to cost too much, and those programs would cost big money in lawsuits and time. It’d be the first program cut by most departments.”
More likely uses are jobs that burn through a lot of copy writers: spam/marketing, realestate ads, search engines and researching, little buddies and toys, publishing (sadly), video games, weather bureaus, text transcription and translation, scams and telemarketing. Things there’s lots of data on, and close to zero risk with.
What about the billions ICE is spending on stockpiling weapons and vehicles, the increased military budget, rhe continued erosion of our rights, and the almost certainly rigged upcoming midterms suggests lawsuits and courts are going to be any impediment to the fascists eventually?
And no, I’m not saying we just roll over and give up. But I am being realistic with the way that most authoritarian regimes go, and how they consolidate all power. Trump campaigned on giving politice as much immunity as he could, and that includes the way that courts punish police oversight and brutality. He’s actually delivered quite well on the things that benefit him and his cronies. And since police serve as the Pinkerton class of capital, I think once he gets enough power, he will fulfill that promise.
Give DHS as much immunity as they need, CiA and FBI clearance and permissions up the wazoo, and anything else they need to stay in power.
Well, you see, there are dozens of adhesive manufacturers willing to pay for advertising or top indexing, while any medical research that could incidentally mention gender or race has its funding set on fire by the US government.
There is no story here, the original Alphafold team was moving to the private pharma service version of Alphafold. alpha fold continues, nothing is shut down.
Sounds like they just moved the research over to isomorphic labs, also even from the onset people quickly took the original approach and paper and made their own versions tuned for their needs.
Feels more like a research project having achieved its goals, the key players moved on, and they’re closing the Deepmind part of it as it’s not really useful anymore.
they seriously out here shutting down the one universally accepted good this shitshow has brought us?
ffs man
really making it hard for the common person to not fucking hate their guts, between shit like this, data center pollution and the growing mental health crisis of people with cyberpsychosis getting talked into suicide by the llm
edit:
shit i got jebaited by the title i think… the project is still available as is but the scientists have been moved to other projects yes?
They basically shifted all the research that they were doing through alpha fold to Isomorphic Labs.
Edit: there’s a case to be made for the idea that they may have wanted to lower the public profile of the work they are doing in order to monetize it. Alpha fold was a non-profit endeavor, and switching it over to isomorphic labs may give them the opportunity to sell their research as a product instead of giving it away for free.
The usefulness of alphafold had been grossly overstated by science media. The structures it generates are mostly nonsense, they typically can’t generate molecular dynamics simulation trajectories with the correct physical properties, which makes them not useful for drug discovery. in computational biology today you’ll most often find them in use as a starting point for structure refinement or as one of many sources of data for some integrative method. Again, not useless, and an improvement over previous structure prediction algorithms, but they didn’t ‘solve protein folding’ or anything, like Google might have you believe. I don’t put much stock in Nobel prizes, I mean, they gave one to Henry Kissinger.
Google also released alphafold 3 under a strict non commercial license, which severely limited its usefulness for both commercial and academic work, the latter of which all but requires using more permissive licenses. I assume Google wanted to monetize a commercial version of it at some point.
I’ve been using Openfold 3 in some work I’ve been doing recently, and while the software is a bit undercooked, it does produce structures similar to alphafold 3 without any of Google’s bullshit. So I wouldn’t worry too much about this announcement. The protein folding will continue with or without them
Though it does suck that attention is being diverted to LLM development because it’s so good at giving the illusion of being smart while still getting so much wrong.