AlphaFold: a solution to a 50-year-old grand challenge in biology • Hacker News Board

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#521

Post by thawab » Mon, Nov 30, 2020, 11:30 PM UTC

dang wrote: post #464

All: there are multiple pages of comments; if you're curious to read them, click More at the bottom of the page, or like this: https://news.ycombinator.com/item?id=25253488&p=2 We changed the URL from https://predictioncenter.org/casp14/zscores_final.cgi to the blog post, which has more background info.

unrelated but the reason i opened the link was because the .cgi file. It's been a very long time since i visited one. The page uses a 2006 YUI library and a 2010 jquery version. The amazing part is it still works in Firefox.

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#522

Post by nil-sec » Mon, Nov 30, 2020, 11:30 PM UTC

garmaine wrote: post #411

whimsicalism wrote: post #350

Earlier quoted context omitted.

Rude. I would appreciate substantive criticism, especially when I'm linking papers in Nature starting to do exactly what I'm talking about.

I cannot give constructive feedback to something which is incomprehensible. "the genome is a sequence that can be language modeled/auto-regressed for depth of understanding by the network" The genome is not a sequence so much as a discrete set of genes which are themselves sequences which specify construction plans for proteins. That distinction is important. Language modeling in the context of machine learning typic…

It is incomprehensible to you, because you just simply do not understand what your parent is talking about. You are the ignorant one here and indeed quite rude. Doesn't matter that genetics is not natural language. The point is we can train large transformers auto regressively and the representation it learns turns out to be useful for a) all kinds of supervised downstream tasks with minimal fine-tuning and b) interpreting the data by analysing the attention weights. There is a huge amount of literature on this topic and what your parent says is quite sensible.

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#523

Post by mensetmanusman » Mon, Nov 30, 2020, 11:31 PM UTC

rsiqueira wrote: post #490

pmastela wrote: post #371

Earlier quoted context omitted.

Like the old Arthur C. Clark quote goes: “Any sufficiently advanced technology is indistinguishable from magic” -- unless it might be cheating in which case throw them a curve ball. Kudos to the DeepMind team for making magic happen.

"A sufficiently advanced Artificial Intelligence would be indistinguishable from God." (Way Of The Future - AI Church)

That would require the AI to exist outside of time and space.

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#524

Post by Tomminn » Mon, Nov 30, 2020, 11:34 PM UTC

softwaredoug wrote: post #487

cs702 wrote: post #118

Two years ago, after DeepMind submitted its first set of predictions to CASP (Critical Assessment of protein Structure Prediction), Mohammed AlQuraishi, an expert in the field, asked, "What just happened?" https://moalquraishi.wordpress.com/2018/12/09/alphafold-casp... Now that the problem of static protein structure prediction has been solved (prediction errors are below the threshold that is considered acceptable i…

> I don’t think we would do ourselves a service by not recognizing that what just happened presents a serious indictment of academic science. Much like other fields, I do begin to question the academic structure to making advances. It appears something is rotten in the state of academia. Oddly it's academia doing incremental improvements to existing methods but industry making novel leaps and bounds... The other majo…

Almost every single of the tens of thousand papers by the hundreds of tenured academics in the field of protein folding are made obsolete by 10 google engineers.

This is what it's like when someone really moves the needle. And academic science cannot get it's head around it.

And yet, none of these scientists will suffer any career consequences. Their irrelevant work will be healthily cited by all the other scientists who are doing and have done irrelevant work. They'll retcon a story in their lit reviews about how their irrelevant work led to this.

The career consequences are saved for those who had their eye on the real ball for the last five years, but didn't get there first. For them, the comfortably irrelevant will have the gall to ask in accusatory tones: "What have you been doing these last 5 years?".

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#525

Post by selestify » Mon, Nov 30, 2020, 11:36 PM UTC

flobosg wrote: post #507

mFixman wrote: post #505

Earlier quoted context omitted.

I don't have a background in biology, and that quote confused me. What's an experimental method for protein folding and why is it so good? Are they talking about creating an actual, physical protein in a lab and observing how it folds?

> Are they talking about creating an actual, physical protein in a lab and observing how it folds? Exactly. Researches purify the folded protein and then use methods such as X-ray crystallography, nuclear magnetic resonance, and cryo-electron microscopy to determine its three-dimensional atomic structure.

If even the experimental approach is only 90% accurate, how do they know which 90% is accurate?

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#526

Post by mensetmanusman » Mon, Nov 30, 2020, 11:37 PM UTC

softwaredoug wrote: post #487

cs702 wrote: post #118

Two years ago, after DeepMind submitted its first set of predictions to CASP (Critical Assessment of protein Structure Prediction), Mohammed AlQuraishi, an expert in the field, asked, "What just happened?" https://moalquraishi.wordpress.com/2018/12/09/alphafold-casp... Now that the problem of static protein structure prediction has been solved (prediction errors are below the threshold that is considered acceptable i…

> I don’t think we would do ourselves a service by not recognizing that what just happened presents a serious indictment of academic science. Much like other fields, I do begin to question the academic structure to making advances. It appears something is rotten in the state of academia. Oddly it's academia doing incremental improvements to existing methods but industry making novel leaps and bounds... The other majo…

Academia is for generating problem solvers. Teams are small and made of people who will be there for around 5 years.

A better comparison would be to national labs, but they are tasked with projects that make no sense for industry to tackle.

The system is working as intended, all players are needed. The team at Alphafold busted their chops in academia and went on to working on problems they could spend decades on.

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#527

Post by calf » Mon, Nov 30, 2020, 11:45 PM UTC

softwaredoug wrote: post #487

cs702 wrote: post #118

Two years ago, after DeepMind submitted its first set of predictions to CASP (Critical Assessment of protein Structure Prediction), Mohammed AlQuraishi, an expert in the field, asked, "What just happened?" https://moalquraishi.wordpress.com/2018/12/09/alphafold-casp... Now that the problem of static protein structure prediction has been solved (prediction errors are below the threshold that is considered acceptable i…

> I don’t think we would do ourselves a service by not recognizing that what just happened presents a serious indictment of academic science. Much like other fields, I do begin to question the academic structure to making advances. It appears something is rotten in the state of academia. Oddly it's academia doing incremental improvements to existing methods but industry making novel leaps and bounds... The other majo…

Is this a scientific advance or a technological one though? Academia doesn't have the capital like industry or government to implement the latter. In America it's small small groups of young students led by a professor. Not full grown PhDs with Google levels of staff and money.

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#528

Post by xpe » Mon, Nov 30, 2020, 11:50 PM UTC

softwaredoug wrote: post #487

cs702 wrote: post #118

Two years ago, after DeepMind submitted its first set of predictions to CASP (Critical Assessment of protein Structure Prediction), Mohammed AlQuraishi, an expert in the field, asked, "What just happened?" https://moalquraishi.wordpress.com/2018/12/09/alphafold-casp... Now that the problem of static protein structure prediction has been solved (prediction errors are below the threshold that is considered acceptable i…

> I don’t think we would do ourselves a service by not recognizing that what just happened presents a serious indictment of academic science. Much like other fields, I do begin to question the academic structure to making advances. It appears something is rotten in the state of academia. Oddly it's academia doing incremental improvements to existing methods but industry making novel leaps and bounds... The other majo…

It is not always either/or.

It is not always A versus B.

These fallacies are too common.

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#529

Post by xpe » Mon, Nov 30, 2020, 11:54 PM UTC

segfaultbuserr wrote: post #513

softwaredoug wrote: post #487

Earlier quoted context omitted.

> I don’t think we would do ourselves a service by not recognizing that what just happened presents a serious indictment of academic science. Much like other fields, I do begin to question the academic structure to making advances. It appears something is rotten in the state of academia. Oddly it's academia doing incremental improvements to existing methods but industry making novel leaps and bounds... The other majo…

> something is rotten in the state of academia. Oddly it's academia doing incremental improvements to existing methods but industry making novel leaps and bounds... The other major case in point being NLP You have to realize that corporate research labs had a high level of recognition back in the 20th century. Labs like the Bell Labs, the RCA Laboratories, or the IBM Research, privately-funded, had a reputation that…

Thank you for writing this. Some key ingredients for organizational driven scientific advancement include: long term funding, risk tolerance, enough reputation to get people involved and aware, team work / collegiality, some degree of openness (depending on the problem), and of course being in the right place at the right time with the right skills, management, and people.

Re: AlphaFold: a solution to a 50-year-old grand challenge in biology

#530

Post by mnky9800n » Mon, Nov 30, 2020, 11:57 PM UTC

mensetmanusman wrote: post #526

softwaredoug wrote: post #487

Earlier quoted context omitted.

> I don’t think we would do ourselves a service by not recognizing that what just happened presents a serious indictment of academic science. Much like other fields, I do begin to question the academic structure to making advances. It appears something is rotten in the state of academia. Oddly it's academia doing incremental improvements to existing methods but industry making novel leaps and bounds... The other majo…

Academia is for generating problem solvers. Teams are small and made of people who will be there for around 5 years. A better comparison would be to national labs, but they are tasked with projects that make no sense for industry to tackle. The system is working as intended, all players are needed. The team at Alphafold busted their chops in academia and went on to working on problems they could spend decades on.

People seem to forget that you need a system like academia that's allowed to fail. Most companies aren't allowed to fail when they need to have quarterly returns. Of course academia has become more and more competitive. But tbh I think the answer is that the funding hasn't increased equally with the number of quality people who could stay in academia. But who knows.