EchoAce

That kind of blind spot is pretty brilliant but more of a technical hack from a Go perspective. Shin is world #1 and won “the normal way”, i.e. playing good moves

It is the same. If you are not a pro punishing deviations is quite difficult (but can occasionally be easy like I'm sure it can be in chess with hanging pieces). The most obvious difficult punish example is just finding unintuitive ways to capture or suppress their stones (analogy: multi move trick captures or getting a better position). But it can be more subtle, sometimes the answer to a deviation is just to not directly punish, but just accept that their shape is slightly inefficient. But if you know they deviated incorrectly, you can be tempted to try to attack hard to directly punish when the line doesn't exist (and then you overplay). Another example of a difficult punish is to just ignore their move and make progress on a different of the board, challenging them to prove their move was actually a threat. You can kind of do that in chess with parallel pawnstorms, but it is much more common in Go.

You can think of joseki as “local opening”. Like, in a vacuum, this is known by study / AI to be an even result for black and white. It’s just like a chess opening, there’s no calculation up to a certain point. And it doesn’t exist in the midgame, it’s not similar to forced sequences which exist in both games; it’s much more like choosing French closed vs open or gambit/gambit declined. The one thing is (and this is huge), since Go board is very big, existing stone formations on other parts of the board influence the value of joseki and make certain ones more advantageous for black or white. To my knowledge this doesn’t really exist in chess, because the opening is already the entire board.

However, when Shin executed the 50 move flying knife, the board was pretty much empty. So there is really no need for calculation, both Shin and the AI know it’s locally optimal. But getting to play a very long locally optimal sequence is good for the weaker player, so they have less “real” moves to lose EV on. Notably Shin probably can’t open with the flying knife in one corner past a certain point in the game, even if that corner were completely empty - the rest of the board positions would change the end values of the variants.

If the AI could know this, they might play a variant that ends 30 moves sooner but is 0.01 pts worse. Then they would have more time to mess Shin up through organic new moves (which the AI will be better at of course).

(disclaimer: only ranked 1 dan)

Same, I take the wiggle all the time and definitely bully cars into letting me keep going :/

Yeah, this is probably better for a game like Go where evaluating raw point differentials is a common thing that professionals (and even strong amateurs) do.

As a Go player myself, I agree that Go-wise this result isn't impressive. But isn't the point that it's an "attack" on the AI? Like for password leaks, failed hash functions, etc, we don't care that it's 100% broken, just that there are tiny artifacts that can be exploited.

I strongly agree, in addition statements like "Before social media advertising would have to hitch a ride with some content produced for something else. Billboards, newspapers, television shows, and magazines all tried to provide a use value to their customers and audiences" are pretty incorrect. As bad as many people agree Facebook is for mental health, it was clearly created for and does provide value. The author does a fairly poor job of carrying out the argument without form-fitting irrelevant details to their desired narrative.

Wait, I see them everywhere in SF and in completely random places too…

Wait, I think you’re misunderstanding a bit. The culture of professionalism ALREADY inherently represses non-straight people (and allows straight people privilege to be who they want). For example, men suits women dresses. There is no culture of professionalism that I know of that gives the privilege to all people. Like a dress code would be fine if it wasn’t obviously biased towards certain culture standards (in this case, western/white, straight).

Edit: to put it another way, professionalism in the case of clothing for example would be more fair if there could be a professional qipao, or professional burka, rather than only a professional western option aka the suit.

I don’t understand the logic here. Yes, of course a wealthy person will be able to pay for procedures and avoid going broke. Isn’t this universally true? Perhaps you meant the US is poorly designed for poor people, which is not something you can say about every country.

Really? He’s a researcher at Google Brain; it’s not like his words have no weight.

Please don’t feel like this article wasn’t useful to some people though even with bias; as a new entrant to the industry I liked reading it!

This is absolutely not cheating; every hand designed algorithm can access and compare everything in the array!

The real point of what they’re saying in your italicized quote is actually that giving the net full access hinders efficiency, so they actually restrict it. Almost like the opposite of cheating.

I just read this! Gave me chills..

Unfortunately this may prove to be way more effective than “doing it out of kindness” like we do.

> “I’ve taught public school teachers, who were incredibly bad at formal mathematical reasoning (I know, because I graded their tests), to the point that I had not realized humans could be that bad at math”

Is it just me or does this come off as incredibly rude? It’s one thing to say people are bad at math but the phrasing of this seems insulting without reason, in my opinion.

While that's vacuously true on account of the fact that being rich is fundamentally good no matter where you are, I'd argue that China is even better to live in if you're rich.

I think the idea is that "calling predict and tuning on a model with the test set" is the "overfitting". It's not actual overfitting like we know in ML; it's as if the researcher is performing "descent" to get the best hyper-parameters. Problem is, if we use the test set to find these hyper-parameters, we'll have no idea how well it does in the real-world/in general. We'd need another set to figure that out - and we're back where we started.

Good for the consumer.

That seems like a valid reason; for me, it seems that the competitive nature of chess and its pre-existing establishment in society as a measure of intellect determines its popularity.

This is incredibly elitist.

It may be my lack of knowledge about optics, but from an ML perspective this seems rather mundane if not useless. Model training involves high levels of parallelism on a large scale for difficult tasks, something I can’t see these optical chips doing. Does anyone have any further information that might enlighten me to otherwise?

And that’s great if that’s what you want. OP was just saying that free, internal lunch promotes team bonding for those who do desire it.

It’s a completely different issue though; there’s already a lot of built up politics regarding Tibet in China.

That's because you value your power over your peace of mind, which is fine and true for most people. I think they just meant in terms of a purely happiness based value system.

Couldn't this simply exacerbate the very problem of echo chambers in social media?

A vm of little xs?

Accessibility to non-programmers though as a good and inspiring learning tool? Or is that not an intended purpose?