anna-gabriella

You are bullying and lying. Please kindly stop bullying and remove comments with lies. Thank you very much.

I am not associated with this other account. You are just making things up about people, papers, and chips.

DeepMind made huge breakthroughs, agreed. AlphaGo beat a sitting go champion, which was very cool. AlphaFold solved a large number of proteins with verified results. Are we clear on this? Hope you are taking back your ad hominem.

The team that did RL for chips work was at GoogleBrain, and you already pointed out that Google had bad demos. The fact that this team was absorbed into DeepMind does not magically rub the successes of DeepMind onto them.

The RL for chips results were nothing like AlphaGo. Imagine if AlphaGo claimed to beat unknown go players, you would laugh. But the Nature paper on RL for chips claims to outperform unknown chip engineers. Also, imagine if AlphaFold claimed to fold only proprietary proteins. The Nature paper on RL for chips reports results on a small set of proprietary chip blocks (they released one design, and the results are not great on that one). That's where imaginary results come up. One of these things is not like the others.

We are discussing AlphaChip in 2024, not AlphaGo from 2016. I don't know much about protein folding (there were some controversies there, but that's not relevant). Neither of these has been related to product claims.

As for "nobody can re-produce", no, that's not the definition. Imaginary things are not competitive advantage. They are exaggerating, and that's bad. But yeah, that's what companies do, you are right.

Reposting, as someone is flagging my comments. > People in the know are following this topic - big-wow surprise!

Hm... I also had to piece things together and agree that Google PR is pretty slick. The approach had promise 3-4 years ago, but the science seems clear now. Google is avoiding tests on shared chip designs but claims a breakthrough. There is no breakthrough as everyone is still using Cadence or Synopsys software tools.

Maybe you can make RL work for chip design at some point, but if the paper "polished up some results", why is it still getting any respect? You are right about "appropriate channels", that's what Chatterjee and Kahng tried, but Chatterjee was fired by Google as a whistleblower (red flag!) while Kahng is getting flak even these comments (another red flag!). Where would you look next as an independent observer?

Please check the textbook - that fallacy asks to accept a claim based on authority. In this case, we have a negative-spin troll (negativeonehalf) spreading FUD about an established subject expert ("a lot of other stuff wrong") with one falsehood after another (paper not peer reviewed, Kahng funded by Cadence, etc). No authority is needed to debunk the troll's claims - they are not supported by anything, basically made-up nonsense.

I can tell you get excited by SciFi, that's where Google's work belongs - people have been unable to reproduce it outside Google by a long shot.

Does this make any sense, really? - Define some common words and then let the media run wild with them. How about we redefine "better" and "revolutionize"? Oh, wait, I think people are doing that already...

Dated or not, if half of the criticisms are right, the original paper may need to be retracted. No progress on RL for chip design was published by Google since 2022, as far as I can tell. So, it looks like most if not all criticisms remain valid.

That does not mean you need to pre-train either. Common sense, no?