4 ms·

"The resulting algorithm outperformed all entrants at the most recent blind assessment of methods used to predict protein structures, generating the best struct

"The resulting algorithm outperformed all entrants at the most recent blind assessment of methods used to predict protein structures, generating the best structure for 25 out of 43 proteins, compared with 3 out of 43 for the next-best method."

KKKKkkkk1 7y ago
This is remarkable. Teams of researchers all over the world have taken part in the CASP competitions for decades. Many attempts using machine learning and ANNs have been made. What is it about DeepMind that allowed them to make such a breakthrough? Do they have expertise in deep learning that does not exist in academia? Incredible amounts of compute that academia cannot afford?
- ibarelyknowher 7y ago
  Alphabet owns way, way more computers than anyone else. You could lose any of the “top supercomputers” in the cracks of their datacenters.
- dekhn 7y ago
  The techniques DM used are popular in academia right now, too. Using evolutionary data to shortcut hard problems has been key to advancement in protein research for decades. DM just executed better, a combination of smart people, some good ideas, and lots of experimentation. NEver underestimate the ability of company that exists to win games, to win competitions.
  - natechols 7y ago
    And never underestimate the amount of money that a big tech company can throw at a random problem. DeepMind probably blew through the equivalent of multiple R01 grants writing that paper.
    - robocat 7y ago
      Big biotech can throw big amounts too. And I read that the size of the team was 10 people - that's not a big number. The compute power applied was not why they had this outcome.
      - natechols 7y ago
        If their salaries are anything like what Bay Area companies are shelling out for top AI engineers, each one of those 10 people is probably costing as much as 10 grad students in any of the other labs working on this problem. Big Biotech does not usually have the money to get into a bidding war for engineering talent with companies like Google.
        robocat 7y ago
        "There are dozens of academic groups, with researchers likely numbering in the (low) hundreds, working on protein structure prediction. We have been working on this problem for decades, with vast expertise built up on both sides of the Atlantic and Pacific, and not insignificant computational resources when measured collectively. For DeepMind’s group of ~10 researchers, with primarily (but certainly not exclusively) ML expertise, to so thoroughly route everyone surely demonstrates the structural inefficiency of academic science." "What is worse than academic groups getting scooped by DeepMind? The fact that the collective powers of Novartis, Pfizer, etc, with their hundreds of thousands (~million?) of employees, let an industrial lab that is a complete outsider to the field, with virtually no prior molecular sciences experience, come in and thoroughly beat them on a problem that is, quite frankly, of far greater importance to pharmaceuticals than it is to Alphabet. It is an indictment of the laughable “basic research” groups of these companies, which pay lip service to fundamental science but focus myopically on target-driven research that they managed to so badly embarrass themselves in this episode." From: https://moalquraishi.wordpress.com/2018/12/09/alphafold-casp13-what-just-happened/ https://moalquraishi.wordpress.com/2018/12/09/alphafold-casp...
        natechols 7y ago
AndrewKemendo 7y ago
It's critical to understand that having a measured benchmark is what makes this result so important and tells us that we're making progress. Without measurable benchmarks we have no idea if we're making real progress towards human level AI.

KKKKkkkk1 7y ago

This is remarkable. Teams of researchers all over the world have taken part in the CASP competitions for decades. Many attempts using machine learning and ANNs have been made. What is it about DeepMind that allowed them to make such a breakthrough? Do they have expertise in deep learning that does not exist in academia? Incredible amounts of compute that academia cannot afford?

ibarelyknowher 7y ago
Alphabet owns way, way more computers than anyone else. You could lose any of the “top supercomputers” in the cracks of their datacenters.
dekhn 7y ago
The techniques DM used are popular in academia right now, too. Using evolutionary data to shortcut hard problems has been key to advancement in protein research for decades. DM just executed better, a combination of smart people, some good ideas, and lots of experimentation. NEver underestimate the ability of company that exists to win games, to win competitions.
- natechols 7y ago
  And never underestimate the amount of money that a big tech company can throw at a random problem. DeepMind probably blew through the equivalent of multiple R01 grants writing that paper.
  - robocat 7y ago
    Big biotech can throw big amounts too. And I read that the size of the team was 10 people - that's not a big number. The compute power applied was not why they had this outcome.
    - natechols 7y ago
      If their salaries are anything like what Bay Area companies are shelling out for top AI engineers, each one of those 10 people is probably costing as much as 10 grad students in any of the other labs working on this problem. Big Biotech does not usually have the money to get into a bidding war for engineering talent with companies like Google.
      - robocat 7y ago
        "There are dozens of academic groups, with researchers likely numbering in the (low) hundreds, working on protein structure prediction. We have been working on this problem for decades, with vast expertise built up on both sides of the Atlantic and Pacific, and not insignificant computational resources when measured collectively. For DeepMind’s group of ~10 researchers, with primarily (but certainly not exclusively) ML expertise, to so thoroughly route everyone surely demonstrates the structural inefficiency of academic science." "What is worse than academic groups getting scooped by DeepMind? The fact that the collective powers of Novartis, Pfizer, etc, with their hundreds of thousands (~million?) of employees, let an industrial lab that is a complete outsider to the field, with virtually no prior molecular sciences experience, come in and thoroughly beat them on a problem that is, quite frankly, of far greater importance to pharmaceuticals than it is to Alphabet. It is an indictment of the laughable “basic research” groups of these companies, which pay lip service to fundamental science but focus myopically on target-driven research that they managed to so badly embarrass themselves in this episode." From: https://moalquraishi.wordpress.com/2018/12/09/alphafold-casp13-what-just-happened/ https://moalquraishi.wordpress.com/2018/12/09/alphafold-casp...
        natechols 7y ago

AndrewKemendo 7y ago

It's critical to understand that having a measured benchmark is what makes this result so important and tells us that we're making progress. Without measurable benchmarks we have no idea if we're making real progress towards human level AI.