phreeza

Wow that's bananas. I suspected the answer would skew towards solar but not by that much. To me that also substantially discredits the "bureaucracy makes nuclear expensive" argument, my impression is the Chinese at doing this kind of engineering efficiently.

> China is doing it, even while they export the solar panels that everybody is buying.

Would be interesting to know how much nuclear vs solar they are building per year domestically.

The glory of having bested a stranger oh the internet in a battle of whits is enough for me!

I'll take that bet? Room temperature semiconductors are very common.

Nice idea in principle but (in the case of private) too long a time horizon for typical corporations to care about, sadly.

I agree with you there are other much grander challenges, but apart from that I don't think the list is horrible, because as I said it's incentive-aligned with the current moment we are in. Your suggestion would definitely be a good addition to the list for sure.

I think some of the items on the list are also way less likely to be worked on (like cryogenics) than others, because they really require some heavy infrastructure to iterate. My money for which of these gets cracked with help of an AI would be rubisco, that can be quite effectively worked on in a closed loop lab fashion with a standard lab or CRO.

Those don't have the property of being easily verified, which the problems proposed here do. I think that's a smart idea because it's a way to capture quick PR seeking AI-lab dollars for quite useful outcomes.

Next also include sales tax in label prices.

Funny there the date is April 1985, a lot earlier and almost my birthday!

This is a pretty stunning result. The time series looks really convincing. Is the way the detector itself is trained orthogonal to this or could there be some "leakage" in that the pre-chatgpt text is in the (positive) training data?