I think the PR is making it seem that Deepmind is not standing on the shoulder of giants, when in fact it very much is. The paper itself makes this clear. I wish them luck!
To add to this, I think it is important to recognise that this is not fundamentally a Deepmind project; engineers from Deepmind came to help with the computational aspects to bring the error down after the lead and last authors brilliantly realised this approach would work with a proof of concept back in 2023. A good amount of work from Deepmind was involved, but I don't like the idea that they could get all the credit for this.
Can you say more about this? Nothing about this approach seems very amazing to me. Construct an approximate solution by some numerical method (in this case neural networks), prove that a solution which is close enough to satisfying the equation can be perturbed to an exact solution. Does the second half use some nonstandard method?
hodgehog11|5 months ago
nybsjytm|5 months ago
Can you say more about this? Nothing about this approach seems very amazing to me. Construct an approximate solution by some numerical method (in this case neural networks), prove that a solution which is close enough to satisfying the equation can be perturbed to an exact solution. Does the second half use some nonstandard method?