[gooseyard]

I was going to post this as well, its delightful to see that other people enjoy it since it was really mind-blowing when I read it.

It's interesting since I saw another comment near yours that raised the question of robustness of the lab-grown design, which I thought was kind of the most fascinating part of the damninteresting article was the revelation that the evolved programs were inseparable from the single physical FPGA used in the training. Since this RFIC training model employs a simulator, do you suppose that the quirks of the physical hardware on which the simulator runs are sufficiently isolated from the training such that a pair of designs would behave similarly when the simulator was run on distinct hardware? And I guess the even more obvious question is whether a design evolved on a simulator would have any hope of behaving as expected in physical hardware?

My hunch about the latter is no, although it still seems like an interesting study, and I often find myself thinking that really understanding what was going on with the FPGAs might be a prerequisite for really understanding how to master reinforcement learning.

Anyway I'm glad you posted this and if you have any other favorites related to this domain send them my way!

[jcims]

Great comment!

>I thought was kind of the most fascinating part of the damninteresting article was the revelation that the evolved programs were inseparable from the single physical FPGA used in the training.

100% agree with this!!! It gave me this weird feeling the first time i read it, like the onset of some alien intelligence. xD

I definitely think a simulator is the way to go, but I'm guessing tools like that could find problems and edge cases in the simulator that nobody thought to test for.

I'm just glad they still have the article up. I bet I've shared it 50 times over the past 20 years lol.