zlacker

I recognize your superior knowledge in the topic and assume you're right.

But you also ignore where we're at in the standard cycle:

https://phdcomics.com/comics/archive_print.php?comicid=1174

;)

>>lrem+(OP)
That's exactly what this is, but it's embarrassing that it's coming from somewhere purported to be a lab. Any of the hundreds or more of labs working in protein structure prediction for the past 50 years could have made this press release at any time and said, "look, we used a computer and it told us these are the structures, we solved the protein universe!"

It's not to diminish the monumental accomplishment that was the application of modern machine learning techniques to outpace structure prediction in labs, but other famous labs have already moved to ML predictions and are competitive with DeepMind now.

>>f38zf5+t1
> but other famous labs have already moved to ML predictions and are competitive with DeepMind now.

it seems obvious this was going to happen, because https://github.com/deepmind/alphafold

>>f38zf5+t1
> but other famous labs have already moved to ML predictions and are competitive with DeepMind now.

That's great! AlphaFold DB mas made 200 million structure predictions available for everyone. How many structure predictions have other famous labs made available for everyone?

>>Viking+k9
As many as you wanted to throw at them, considering the vast majority are open source and could be run on your own server cluster. CASP15 is ongoing so by the end of the year we will know how much absolute progress has been made by others.

Google has the advantage of the biggest guns here: the fastest TPUs with the most memory in the biggest clusters, so running inference with a massive number of protein sequences is much easier for them.

>>Viking+k9
Many teams have been predicting structures for enormous numbers of proteins for some time now. It's just that nobody had any confidence in the predictions.