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The entire tiebreak, which was played today, is this video: https://www.youtube.com/watch?v=HBvQ36SqgqM

The entire match, played over the past weeks, is this playlist: https://www.youtube.com/watch?v=cJlVjicymKI&list=PLAwlxGCJB4...


Thanks, but I was looking for a video of them actually playing, not just people reviewing the moves.


FIDE actually owns the rights to the content. As far as I know there is no way other than to pay $20 for the video on the their main website. https://worldchess.com


Jpeg still trims the trees, just not as much.


In your demo, how are the images chosen for each image and algorithm combination? I mean how do you choose the compression level for each, to keep the comparison fair? I would hope you have a budget in KB and go as high quality as you can without going over that KB limit.


Not my demo, it's from someone at Mozilla, but, yes, the usual practice for comparisons is to match the size of the compressed content. I don't have context for that page, so I can't actually cite anything here.


How do you go about making such a map for a large code repository? I'd really appreciate a link for reading on this subject.


I basically start anywhere and study the call graph, taking notes as I go.


This limited scope is still progress though, toward the general AI he is saying will not come in the near future. The Alpha Zero project showed that it could be adapted for any 2-player perfect information game. This is still quite limited, but not nearly as much as a program like Stockfish is, which will basically only ever play chess.

Perhaps the next step is bringing the system further into the realm of the unknown in games, like chance and imperfect information. I don't know if Google is continuing this, but it would be a shame if it wasn't.


They showed that the system could be adapted to learn any two player perfect info game.

Once it has learned Go it won't play chess. Also, it has to be manually adapted.

By this logic minimax has also been shown to do the same:

https://en.m.wikipedia.org/wiki/Minimax


Minimax is a general rule on how to optimally play 2 player games. It's about as much of a learning algorithm, and as practical, as "buy low, sell high".

In pure form, it can't be applied to any game where you cannot enumerate every last possible board position (so Chess and Go are out). And with heuristics, those heuristics effectively become the algorithm and they're really complex.


The minimax principle is used in chess and go and any other competitive two player perfect knowledge game. What improves is the selection of moves to evaluate and the quality of the board evaluation. Chess and Go absolutely use minimax with sleight, but important, modifications. Deep learning extensions with Alpha Go were specifically for move selection and board evaluation.

Alpha beta pruning with heuristics is one of the most fundamental extensions of minimax. It is still minimax.

The alpha go system still clearly applies only to perfect information 2 player games, because it is fundamentally extended minimax.

Edit: I'm not saying the heuristic extensions of alpha go, or the reinforcement learning of zero, aren't brilliant and important. That doesn't take away from the basic fact that it is an algorithm for perfect info 2 player games and one of them at a time (even if modifications can adapt it to other games). Heuristics will be fundamental to general intelligence, but alpha go is not general intelligence.


Several mobile strategy games like Clash of Clans present this problem when raiding. You can skip to the next base or raid the current base.

Numberphile did a nice presentation of this problem and a solution here: https://www.youtube.com/watch?v=ZWib5olGbQ0


Money did not have the intended effect on this election. Clinton outspent Trump by quite a large margin.

https://www.washingtonpost.com/graphics/politics/2016-electi...


Whether or not spending actually influences elections, most politicians certainly believe it does. Or they wouldn't spend so much effort on fundraising, and wouldn't bother with the stupid ads. They clearly believe it works. Surely they know. Modern campaigns track this stuff religiously with polls, statisticians, and A/B tests. And this belief corrupts our democracy.

One example doesn't disprove it anyway. Clinton lost. But she might have lost even worse without the spending. It's impossible to say the spending had no effect. As the election was pretty close in many states, even small effects can make a world of difference.


It's in T-Mobile's interest to do this for its own network management. The unlimited video is of much lower quality, using less bandwidth. The only agreement between T-Mobile and Netflix/YouTube is for T-Mobile to be allowed to control which quality is served over their network.


I agree. I don't see any evidence he has attempted to solve any problem or made something with Python. This is the measure of proficiency.


I have a Github Account actually where I post my codes.

Here is the link for my github: https://github.com/aysin


It's true but it's more of an evidence than graduating from college anyway.

(not to dismiss college education here but what you get there are good theoretical fundamentals not anywhere close to proficiency in programming or specific languages)


I don't know whether you went to college/university or not, but my program definitely gives you both of those things, in addition to very good theoretical fundamentals. Not to say that you've got the necessary real-world experience after completing it, but you're well on your way.


Depends on your program. Schools vary widely in what they offer. Depending on the university, you could get a job in IT or a research lab and write code there.

Most engineers I know doing non trivial machine learning work got their start in university labs.


Just to clarify, the author is female.


Is this surprising? Facebook has a billion users. So this article is saying that <1% of users on Facebook don't understand they are using the Internet.


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