> Anyway, given these numbers, they are one of the worlds richest research labs, able to deploy enormous computational resources and relying for free on a highl

> Anyway, given these numbers, they are one of the worlds richest research labs, able to deploy enormous computational resources and relying for free on a highly reliable and scalable infrastructure of one of the world's biggest internet companies. Whether the results they present periodically are actually still impressive given all that burn rate, I'll leave it for the reader to decide. Why would the burn rate make the results unimpressive? The author just made a comparison to MIT, which has a burn rate 3 times as large, and no one questions if their results are impressive or not each year. It also seems like a cheap criticism of AlphaFold to say it hasn't solved protein folding by citing the NP-hardness of the problem. There's widespread expert consensus that DeepMind made a spectacular advance in the area, and the author characterizes it by saying, "well, they didn't solve an NP-hard problem..."? The author seems pretty abrasive to be honest. This is a disingenuous "AI Update" for 2020.