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I don't quite agree with this. I work in this field and it is quite rare to get the code along with paper by people from academia. In fact many a times big comp

I don't quite agree with this. I work in this field and it is quite rare to get the code along with paper by people from academia. In fact many a times big companies tries to replicate the the published work and publish the code/model like say TF Model Garden.

jhbadger 6y ago
It depends on what you mean by "the field". Do you mean machine learning? That might be the case given the corporate dominance of that technique. But in bioinformatics (the domain to which AlphaFold2 is applying ML to) it is generally expected that all data and code be made available for a tool. Otherwise what's the point? If people can't build upon it, science hasn't been done.
- timr 6y ago
  You're overstating the situation. The previous top-performing protein folding method is essentially impossible to reproduce from public literature, and available only via licensing agreement with the lab that created it. More generally, while it's far more common to find open-source implementations of lab research than it used to be, it's still quite common for code to be closed, and important methodological details to be secret. Even in the "open" fields of ML, today, I routinely find papers where essential bits of code, parameter sets, etc. are not made available.
throwaway2245 6y ago
In bioinformatics and academic protein folding in particular, there has been a strong tradition of sharing work and building on others' work. That's arguably why CASP exists, as part of a recognition that the field benefits from collaborative effort to solve the problem - e.g. via public identification of what approaches have worked.
- emteycz 6y ago
  How come the next best protein folding software is proprietary, then?
CJefferson 6y ago
Lots of AI competitions have requirements that competitors are open source, see for example SAT Race ( http://sat-race-2019.ciirc.cvut.cz/index.php http://sat-race-2019.ciirc.cvut.cz/index.php ). This seems to be less the norm in deep learning areas, which is unfortunate.

jhbadger 6y ago

It depends on what you mean by "the field". Do you mean machine learning? That might be the case given the corporate dominance of that technique. But in bioinformatics (the domain to which AlphaFold2 is applying ML to) it is generally expected that all data and code be made available for a tool. Otherwise what's the point? If people can't build upon it, science hasn't been done.

timr 6y ago
You're overstating the situation. The previous top-performing protein folding method is essentially impossible to reproduce from public literature, and available only via licensing agreement with the lab that created it. More generally, while it's far more common to find open-source implementations of lab research than it used to be, it's still quite common for code to be closed, and important methodological details to be secret. Even in the "open" fields of ML, today, I routinely find papers where essential bits of code, parameter sets, etc. are not made available.

throwaway2245 6y ago

In bioinformatics and academic protein folding in particular, there has been a strong tradition of sharing work and building on others' work. That's arguably why CASP exists, as part of a recognition that the field benefits from collaborative effort to solve the problem - e.g. via public identification of what approaches have worked.

emteycz 6y ago
How come the next best protein folding software is proprietary, then?

CJefferson 6y ago

Lots of AI competitions have requirements that competitors are open source, see for example SAT Race ( http://sat-race-2019.ciirc.cvut.cz/index.php http://sat-race-2019.ciirc.cvut.cz/index.php ). This seems to be less the norm in deep learning areas, which is unfortunate.