Speaker 1: Brought to you by the reinvented two thousand twelve camera.
Speaker 1: It's ready. Are you get in touch with technology? With
Speaker 1: tech Stuff from how stuff works dot com. Hello again, everyone,
Speaker 1: welcome to tech stuff. My name is Chris Pollette, and
Speaker 1: I am an editor at how stuff works dot com.
Speaker 1: Seeming across from me, as usual, is senior writer Jonathan Strickland. Yes,
Speaker 1: I'm owed old enough to remember when the m c
Speaker 1: P was just a chess program. There you go, that's
Speaker 1: pretty good. It's a good quote. Huh yeah, yeah, we's
Speaker 1: now I'm hungry for Pepperidge Farm. You can't get that
Speaker 1: from hreh Um. We're going to talk today about some
Speaker 1: pretty famous matchups between human beings and computers, uh, in
Speaker 1: in various games. And this is one of those things
Speaker 1: that people have been interested in. Well, really it goes
Speaker 1: back even before computers, because it really kind of dips
Speaker 1: into the whole man versus machine, um the idea, right,
Speaker 1: I mean this goes all the way back to John
Speaker 1: Henry versus the the steam steam engine. Yeah, and uh,
Speaker 1: people have wondered like when we're when we reach a
Speaker 1: point where computers would become better than humans at various
Speaker 1: games and we've reached the point with several games where
Speaker 1: we can pretty much definitively say computers are better at
Speaker 1: it than we are, you know, And a lot of
Speaker 1: the podcast where we've mentioned artificial intelligence or AI in
Speaker 1: the past, UM, we have talked about gaming and in
Speaker 1: those situations we were talking more about computer opponents when
Speaker 1: you're playing against something in a computer game or a
Speaker 1: console game, and that's a little different than what we're
Speaker 1: talking about here. But because and UH, I think actually
Speaker 1: I was I was reading an article UM by Jonathan Schaefer,
Speaker 1: Vadim Blikko, and Michael Burrow in the I E E.
Speaker 1: Spectrum and UH, it was talking about computer opponents in
Speaker 1: UH in software, specifically the game Fear f E A R,
Speaker 1: which is the first Encounter Assault Recon and how that
Speaker 1: has that's known as for its excellent AI. But UM,
Speaker 1: basically these games we're talking about today are are classic
Speaker 1: board games, classic tests of UH, you know, one player's
Speaker 1: skill and strategy and thinking against another human being. And
Speaker 1: we wanted to know, you know, whether that's possible now
Speaker 1: and sort of depends on the game and it sort
Speaker 1: of depends on the opponent. But that's really according to
Speaker 1: the authors in this in the Spectrum article. Um, it
Speaker 1: really started with with board games, and that's one of
Speaker 1: the things that has gone into a development of AI
Speaker 1: in computer games of all kinds, was you know, these
Speaker 1: attempts in the past to develop a formidable opponent, somebody
Speaker 1: that or something that you can play against where you
Speaker 1: don't have to go you don't really like to play
Speaker 1: a game at chess, but you know, Steve's work in
Speaker 1: a night and and I don't have anybody else that
Speaker 1: I can think of, and I really want to play
Speaker 1: a game of chess. We want something. You don't want to, uh,
Speaker 1: something that's going to annihilate you instantly, nor do you
Speaker 1: want something that's going to be a complete pushover. So yeah, exactly,
Speaker 1: he's like playing me and chess. I only know how
Speaker 1: to lose it chess. Um. So yeah, I mean it's
Speaker 1: it's an interesting question and sort of a philosophical question.
Speaker 1: It's not just programming. Yeah, I mean, there's a lot
Speaker 1: of these games have have elements to them that go
Speaker 1: beyond just a the physical number of moves that are
Speaker 1: possible at any given point. Right, some games that's pretty
Speaker 1: much all the game is. For example, Connect four. Oh yeah,
Speaker 1: Connect four. We're gonna talk a little bit about solving games. Now,
Speaker 1: to solve a game means that you have determined what
Speaker 1: all the possible moves are, and you know what the
Speaker 1: best possible move in any given situation is. Um. If
Speaker 1: you have perfectly solved a game, then in theory, you
Speaker 1: would be able to play a game, even pick up
Speaker 1: a game that had already been started by someone else,
Speaker 1: and play it from that point forward, playing the best
Speaker 1: possible moves, even if that person who had previously been
Speaker 1: playing made a lot of mistakes. Not many games have
Speaker 1: been solved to that level, but that a lot of
Speaker 1: games have been solved to the point where two players
Speaker 1: starting off with a fresh board and going from there.
Speaker 1: Uh is there is there a perfect way to play
Speaker 1: where you will either what will essentially where you'll never lose. Yeah,
Speaker 1: you're speaking for personal experience. I think Reversey is one
Speaker 1: of the games, UM, if you're not familiar, it's the
Speaker 1: game with the black and white pieces that you try
Speaker 1: to basically surround your opponent to the point where you
Speaker 1: flip all the pieces to your color and or or
Speaker 1: as many as you can and outnumber your opponents. Now
Speaker 1: I've played, uh, computer opponents in which on the easy
Speaker 1: mode it was a cakewalk, and I'd switch to the
Speaker 1: next level, and it already it seemed as though the
Speaker 1: machine had already been programmed with the best possible counter
Speaker 1: move to whatever it was, to the point where if
Speaker 1: I played on easy, I would almost always win unless
Speaker 1: I did something really stupid, and on even medium, it
Speaker 1: would know exactly how to counter every move I make,
Speaker 1: to the point where I could not win no matter
Speaker 1: how well I would play the game. And uh, I
Speaker 1: think there are certain games for which you could say, okay,
Speaker 1: well these are the moves. In this case, it's the
Speaker 1: best possible move. And you know, when you're playing a person,
Speaker 1: you go, well, I you know, oh, look he made
Speaker 1: a mistake. And you know that. You know, Jonathan in
Speaker 1: this case is sitting across from me. He made a mistake. Well,
Speaker 1: he may not have been thinking about it. The computer
Speaker 1: is not going to make a mistake. It's already been
Speaker 1: programmed with that in mind. Yeah. The mistakes computers make
Speaker 1: are based upon not expecting behavior from a human, right, right,
Speaker 1: I mean that's that's the way computers make mistakes. They
Speaker 1: don't make mistakes in the same way humans do. So
Speaker 1: for example, getting back to the Connect for uh example,
Speaker 1: that game has been solved to the point where, assuming
Speaker 1: perfect play on both sides, yes, the first player will
Speaker 1: always win. Yes, there is no way for the first
Speaker 1: player to lose if both players are playing perfectly. Uh.
Speaker 1: Perfect play means you go for that center spot, folks,
Speaker 1: Just just an f y I if you need to, uh,
Speaker 1: if you need to play Connect four and you're the
Speaker 1: first player, get grabbed that center spot on the bottom
Speaker 1: row and uh and then just play perfectly from there
Speaker 1: and you'll always win. Easier so than done. Really, but
Speaker 1: that that was one of the games that was solved
Speaker 1: fairly early on. But there are other games have been
Speaker 1: solved as well, and some games are not truly solvable.
Speaker 1: In fact, I wrote an article about computer versus human
Speaker 1: game matchups and the first one I mentioned was b
Speaker 1: KG nine point eight. That would be the computer versus
Speaker 1: Luigi Villa or Villa so uh so Luigi here he
Speaker 1: was a backgammon player. Yes, as am I, I nowhere
Speaker 1: near as good as Luigi. So so Luigi played a
Speaker 1: match against b KG nine point eight in June nineteen
Speaker 1: seventy nine, and the game was got a fair amount
Speaker 1: of press because the computer program beat the the player. However,
Speaker 1: backgammon has an element in it that is unlike games
Speaker 1: like connect for or checkers or chess. Yes, that would
Speaker 1: be dice. There's an element of chance in backgam and
Speaker 1: so depending upon the dice rolls, you may be luckier
Speaker 1: than your opponent, and that luck might be enough for
Speaker 1: you to beat someone who is technically more skilled at
Speaker 1: the game than you are, someone who is who is
Speaker 1: better at formulating strategies and picking the right moves and
Speaker 1: the best possible outcomes. Uh, you might win just because
Speaker 1: you get on a lucky streak, and that seems to
Speaker 1: be what happened with this computer program. Yes, should we
Speaker 1: mention our earlier podcast on random number generators, because if
Speaker 1: you were playing a computer and you were not using
Speaker 1: an actual die or in this case dice, then uh,
Speaker 1: and you're relying on the computer to generate random numbers, Well,
Speaker 1: in general you can't because they're they're using an algorithm
Speaker 1: and the computer number generators will generally go in a sequence. Now,
Speaker 1: this kind of goes back to what Chris was saying
Speaker 1: earlier about playing a video game in a video game
Speaker 1: world where you're playing against video game opponents. Technically in
Speaker 1: that kind of environment. Uh, the AI is totally different
Speaker 1: from a board game because it controls the entire environment.
Speaker 1: So you could create a video game that compensates for
Speaker 1: really strong players by pitting the environment against the players. Yes,
Speaker 1: you know. I mean it's it's completely within the realm
Speaker 1: of possibility. In the situations we're talking about. It's supposed
Speaker 1: to be a fair game between our as fair game
Speaker 1: as you can get between a computer and a human.
Speaker 1: There's not supposed to be any element that's going to
Speaker 1: be within the computer's control that could that could weigh
Speaker 1: it in favor of the computer, right, because it's supposed
Speaker 1: to be a test of intelligence relative intelligence, like as
Speaker 1: we mentioned with Alan Touring, Yes, yes, the touring test um. Now,
Speaker 1: in that case, the touring test was a tested determined
Speaker 1: whether or not you could tell the difference between a
Speaker 1: human respondent and a computer responded to a series of questions.
Speaker 1: In this case, we're talking about what or a computer
Speaker 1: is able to formulate a winning strategy against the human.
Speaker 1: The next one on my list was Chinook versus Marion
Speaker 1: Tinsley with Checkers. Yes, this was Checkers. Now Tinsley, Uh,
Speaker 1: was an accomplished checkers player, amazing champion. He had won
Speaker 1: the championship from nineteen fifty five to nineteen two, and
Speaker 1: he had only lost five games between nineteen fifty and
Speaker 1: that seems reasonably decent. I think I've only played five
Speaker 1: games since n probably lost all five of them. Well,
Speaker 1: this is another game, though, if unless I misunderstand the
Speaker 1: article that you so aptly wrote, um uh, in which
Speaker 1: there is a way to play perfectly. Yeah, this was
Speaker 1: that was not discovered till two thousand seven, or not
Speaker 1: not truly proven until two thousand seven. So when Tinsley
Speaker 1: played against chinook Um, the game had yet to be solved,
Speaker 1: and sadly, Tensley actually passed away before he could. Before
Speaker 1: they could definitively say whether or not the computer was
Speaker 1: a superior player, they would play thirties something games in
Speaker 1: a row and end and draw a draw every time. Um.
Speaker 1: But that suggests that I'm sorry, go ahead, I'm just
Speaker 1: gonna say that suggests that that Tense was able to
Speaker 1: play a perfect game. Yes, because in two thousand and seven,
Speaker 1: the team that that created chinook did prove or demonstrate
Speaker 1: that they had solved the game, and that if you
Speaker 1: play perfectly on either side. Let's say both sides are
Speaker 1: playing perfectly, it will the game will always end in
Speaker 1: a draw. So checkers is different from Connect four and
Speaker 1: that if you if both sides are playing perfectly, there
Speaker 1: is no winner, It's going to be a draw, whereas
Speaker 1: with Connect four, whoever goes first wins. There's actually I
Speaker 1: remember reading about a game I didn't jot down it
Speaker 1: shot down my notes unfortunately, where it was the second
Speaker 1: play if the second player plays perfectly, If both players
Speaker 1: are playing perfectly, the second player will always win, which
Speaker 1: is which is interesting because you know, it just shows
Speaker 1: that it all depends upon the actual style of the game. Now,
Speaker 1: the next one that's on my list is probably the
Speaker 1: biggest one. Yes, yeah, the one that everyone knows or
Speaker 1: has heard about, right, IBM's famous deep blue Yes against
Speaker 1: Gary Kasparov, who was the world champion chess player at
Speaker 1: the time. And uh they actually had two matches to
Speaker 1: two series of games. The first was in n and
Speaker 1: in that series Kasparov actually came out the victor. He
Speaker 1: managed to thank you, came out the winner, you know, wiener.
Speaker 1: Uh So Kasparov one in the first series of games
Speaker 1: in and then IBM redoubled their efforts, and as Kasparov
Speaker 1: says in one of his articles, um they redoubled it's uh,
Speaker 1: they doubled its its processing power. Uh. The article I
Speaker 1: was referring to it is called the Chess Master and
Speaker 1: the Computer, which was a uh, actually pretty interesting article
Speaker 1: at any rate. In that game, Kasparov won the first
Speaker 1: game of the match in the series, lost the second one.
Speaker 1: The next three were draws, and the final game deep
Speaker 1: blue one. So in that case, deep Blue one the series.
Speaker 1: And this was this made news worldwide because chess was
Speaker 1: one of those games that that people thought this game
Speaker 1: is so complex and it relies so much upon intuition
Speaker 1: and and strategy that goes beyond just numbers, that it
Speaker 1: was going to take ages before a computer could beat
Speaker 1: a true chess champion. And go ahead, I was gonna say,
Speaker 1: And this isn't just any chess champion. I mean he
Speaker 1: had the highest rating, yes, offered by the the world
Speaker 1: body that covered chess. Yeah, there are various ways to
Speaker 1: rate chess players, but yes, Kasparov held the highest rating
Speaker 1: of all human players at this point. There are computer
Speaker 1: players that have higher ratings, in fact, ratings higher than
Speaker 1: what people thought were possible. UM. But UH. The interesting
Speaker 1: thing here about this, this UH matchup was that Kasparov
Speaker 1: said he thought that he had not prepared properly for
Speaker 1: the games, and that he wished he could have had
Speaker 1: another rematch. But ibm H shut down that that project
Speaker 1: because they had pretty much proven their point, you know
Speaker 1: that they were They set out to create a computer
Speaker 1: program that could beat the world champion in chess, and
Speaker 1: it and it worked, So why continue that? I mean,
Speaker 1: there's no other application really for that. So they shut
Speaker 1: down that program and and Kesperov never had a chance
Speaker 1: to to try and and UH and and prove that
Speaker 1: he could beat this this computer. Now, since then, Kasparov
Speaker 1: has played other computer programs that are on UM extremely
Speaker 1: powerful machines, and in some cases he has played to
Speaker 1: a draw or one, and in other cases he has lost.
Speaker 1: And he has said that we have essentially reached the
Speaker 1: era where a a powerful computer running the right software,
Speaker 1: or even desktop computers running the right software, can beat
Speaker 1: a a grand master chess player. UM. And part of
Speaker 1: that is because these these computer programs often have an
Speaker 1: entire database of opening moves available to to UH to
Speaker 1: look at before making any kind of a move against
Speaker 1: an opponent. And the other is that chess is a
Speaker 1: really complicated game. You can't really map out all the
Speaker 1: possible moves easily because there's so many different pieces and
Speaker 1: they all behave differently, and there are a lot of
Speaker 1: different options at any given time. But what chess computers
Speaker 1: do very well is they can plot out all the
Speaker 1: possible moves once you get down to a certain number
Speaker 1: of chess pieces towards the end game. And so a
Speaker 1: lot of these chess programs are very very good at
Speaker 1: plotting out the best moves when they're only say seven
Speaker 1: or eight pieces on the board. Once you get more
Speaker 1: than that, the the different variables are so vast that
Speaker 1: it's a lot harder to account for all of them.
Speaker 1: That being said, it's gonna be pretty much it'll it'll
Speaker 1: take a lot of luck, really to beat a powerful
Speaker 1: chess program at this point, it can happen. Um. Casparov
Speaker 1: has shown that by playing in a kind of unconventional
Speaker 1: way you can fool a machine. He he actually did
Speaker 1: fool Deep Blue into sacrificing a piece that it shouldn't have,
Speaker 1: and that was how he managed to win one of
Speaker 1: the games in the round. So computers do make mistakes,
Speaker 1: but um, it's it, you know, it's it's hard to
Speaker 1: it's hard to predict when that's gonna happen. They don't
Speaker 1: behave the same way humans do. So um and Kasprov
Speaker 1: actually has said that now champion chess players are starting
Speaker 1: to adopt more computer like approaches to playing and has
Speaker 1: even uh talked about he's he's kind of a champion
Speaker 1: to a concept called advanced chess, which involves a player
Speaker 1: consulting a computer during play. So it's so it's a
Speaker 1: combination of human intuition and the ability of a computer
Speaker 1: to have that entire database of every game that's ever
Speaker 1: been played, essentially, and to rely on that and see like, oh, well,
Speaker 1: what what is this series of opening moves? Is that?
Speaker 1: Is that something that's been played before? And if so,
Speaker 1: what's the best thing for me to do? And you know,
Speaker 1: there are points where the human takes over and starts
Speaker 1: to make moves, or perhaps the human has a move
Speaker 1: in mind and programs it into the computer, or to
Speaker 1: see what possible counter moves could happen. Um, And it's
Speaker 1: it's kind of it in a way. You might think, well,
Speaker 1: that's sort of cheating, but in another way, you might think, Hey,
Speaker 1: this is an example of computers and human intelligence merging
Speaker 1: in a way. Yeah, yeah, I see what you're saying. Yeah,
Speaker 1: that's one of the things that I have a problem
Speaker 1: with with certain games is the lack of encyclopedic knowledge
Speaker 1: of everything you could possibly do. And in reading your article,
Speaker 1: I actually was thinking about this from a personal standpoint
Speaker 1: before I got to the next example. But yeah, I um,
Speaker 1: I'm a fan of the Scrabble brand cross word game.
Speaker 1: I love their trademark. We have to use that trademark, um.
Speaker 1: Although I love the game, so it doesn't bother me
Speaker 1: so much as quirky. UM. So the thing is, if
Speaker 1: you go to a lot of the uh, the clubs
Speaker 1: that really get into the game, UM, you will find
Speaker 1: that a lot of them offer lit and lists and
Speaker 1: lists of words, all kinds of words, lists of words
Speaker 1: that you can make with different particular letter combinations that
Speaker 1: you might have on your tile rack. And I keep thinking, Man,
Speaker 1: if I had access to all these words without having
Speaker 1: to study these lists, I might, you know, really be
Speaker 1: able to wamp up on some people playing scrabble. Now,
Speaker 1: there are people who spend lots and lots and lots
Speaker 1: of time studying the word lists, so they will be
Speaker 1: armed with all these different lexicographical weapons. Um. Yeah, I
Speaker 1: don't know if lexicography is a word. I'll have to
Speaker 1: look it up. I'm not sure that would work in scrabble. Um. Okay, However, Um,
Speaker 1: it seems that, uh that in your next example, that
Speaker 1: there is a computer able to play at that level,
Speaker 1: and that seems like it would have a severe pose,
Speaker 1: a severe disadvantage for the human opponent. Yeah. Quackle is
Speaker 1: the the program um that you're referring to calls a
Speaker 1: computer program that um that was able to beat a
Speaker 1: champion named David Boys in a series of games of
Speaker 1: scrabble and Quackle. Again. Scrabble is one of those games
Speaker 1: that also comes down in part to luck, because it
Speaker 1: all depends on what tiles you have in your you know,
Speaker 1: you have at your disposal. Uh. And Quackle was able
Speaker 1: to beat David Boys fair and square. Right, It was
Speaker 1: able to fair and square in the sense that it
Speaker 1: wasn't it wasn't making guesswork of the game. It was
Speaker 1: building words based upon what it had available and what
Speaker 1: was on the board already. Um. And yes, it did
Speaker 1: have an enormous database of words. So that gave it
Speaker 1: an advantage in that, you know, human beings, some of
Speaker 1: us are really good at remembering you know, thousands of
Speaker 1: different word letter combinations that make legitimate words. Others we
Speaker 1: rack our brains like I've got a V, A, B,
Speaker 1: and F and in a queue, and oh what can
Speaker 1: I make? You know? So that one was playing pretty
Speaker 1: much by the rules. What was interesting to me was
Speaker 1: I ran across a story about a graduate student named
Speaker 1: Mark Richards who came up with a program, a scrabble
Speaker 1: program that goes a step further. It doesn't just have
Speaker 1: a massive database of words that can play uh. And
Speaker 1: another advantage that scrabble UH computer programs have is that
Speaker 1: let's say that you have two lines of like two
Speaker 1: words that are fairly close to one another on the
Speaker 1: scrabble board, um, and but you know they're separated. There's
Speaker 1: maybe like five blank tiles between the two words. These
Speaker 1: computer programs are much better at looking at those those
Speaker 1: configurations and determining words that can span those gaps that
Speaker 1: are than humans are. And so you'll see words played
Speaker 1: by computers that most humans never would have thought of.
Speaker 1: Because to to have taken that into account, that big
Speaker 1: gap into account is just kind of beyond what most
Speaker 1: of us do when we play. There are good players
Speaker 1: out there who are really good at this, but most
Speaker 1: of us, you know, well, we sit there and we
Speaker 1: concentrate on one letter at a time, or if words
Speaker 1: are close enough, we might be able to get two
Speaker 1: letters that are already on the board incorporated into whatever
Speaker 1: we're about to lay down. Well, what Mark Richards did
Speaker 1: was he on a step further than that. He created
Speaker 1: a program that could guess what letters the opponent had
Speaker 1: at his or her disposal bye bye. You know, there
Speaker 1: are only so many letters that are in a scrabble game,
Speaker 1: so it's counting tiles, counting cards. By counting cards in Vegas,
Speaker 1: it would count tiles. So you would start playing the game,
Speaker 1: and at the beginning of the game, the computer really
Speaker 1: can't tell what you have because it's only the only
Speaker 1: information it has at the very beginning of the game
Speaker 1: is which tiles are in it's uh, it's vault right.
Speaker 1: Anything beyond that it doesn't know. So I mean it
Speaker 1: would know like, okay, well one of the q you
Speaker 1: tiles is in uh in my hand, which means that
Speaker 1: there is one less one fewer out in the actual game, right, Yeah,
Speaker 1: you can't really say, well, what are the odds that
Speaker 1: he's holding that? You know, it's it's astronomical. You know,
Speaker 1: there's no qu and scrabble, right is not qu I
Speaker 1: thought of what it's just Q some of the some
Speaker 1: of the others that are similar, because almost every instance
Speaker 1: that Q appears in the English language is followed by
Speaker 1: the letter you. Um, that's right. So at any rate,
Speaker 1: the so Q, I'm just gonna say, somebody's gonna write
Speaker 1: in so well, I don't play a lot of scrabble, clearly,
Speaker 1: but at any rate, so the computer what it can
Speaker 1: do is as the game goes on, it can start
Speaker 1: predicting with better and better accuracy, which tiles you probably
Speaker 1: hold in your in your hand. So what it what
Speaker 1: it does, It will start playing words and playing parts
Speaker 1: of the board that will block off the best options
Speaker 1: you would have and when it becomes your turn, so
Speaker 1: it's blocking you from the combinations that would get you
Speaker 1: the most points. So so you're you're handicapped even further
Speaker 1: than you were just from playing the game fair and
Speaker 1: square even. You know, another interesting thing, and another interesting
Speaker 1: point you made that was nice um in the Uh.
Speaker 1: Discussion of Quackle is that it in order to actually
Speaker 1: play uh David Boys, it actually had to beat another
Speaker 1: computer in tournament play before it was allowed to play him,
Speaker 1: which I think is funny. So I had computer versus computer. Yeah,
Speaker 1: there are a few. There are a few tournaments that
Speaker 1: I've seen like that where it's been computer pitted against
Speaker 1: computer and then the winner goes up against a human champion. Um.
Speaker 1: And then there have been other exhibit games like I
Speaker 1: remember there's one with Kasparov where he was playing against
Speaker 1: thirty two computers and he won all of all of
Speaker 1: those games. Yeah, thirty two to nothing. Uh. And then
Speaker 1: the last one in my list was a computer program
Speaker 1: that was playing the game of Go. And Go is
Speaker 1: particularly interesting in that it has if you're playing on
Speaker 1: a full board, it's a grid of nineteen by nineteen lines,
Speaker 1: and you play your pieces on the inner where those
Speaker 1: lines intersect in the grid, and that's a huge number
Speaker 1: and and so the the potential moves and go is big.
Speaker 1: Is there there are more potential moves in that game
Speaker 1: than than pretty much any of the other games we've
Speaker 1: talked about. And there are also situations that can pop
Speaker 1: up where just because of the nature of the game,
Speaker 1: a move may or may not be technically legal, or
Speaker 1: there may actually be room for you to discuss the
Speaker 1: legality of a particular move, which makes it even more
Speaker 1: difficult for a computer to win because the computer just
Speaker 1: can't make that consideration. So um Go is one of
Speaker 1: those games where we have seen computers beat champions at Go.
Speaker 1: But we've also seen cases where these these really powerful
Speaker 1: computer programs have been beaten by Go players, and sometimes
Speaker 1: they are Go players who are, you know, eight or
Speaker 1: nine years old. So it's one of those where if
Speaker 1: you're talking about solving a game, it's probably gonna take
Speaker 1: a while to solve that nineteen by nineteen grid game
Speaker 1: because it's just like I said that, the potential number
Speaker 1: of moves are I mean, it's it's it's enormous. Yeah yeah,
Speaker 1: but that's uh, I mean, it's such a difficult game too.
Speaker 1: And I mean the the player that this particular Go
Speaker 1: program took on certainly one of the best in the world,
Speaker 1: and it took a supercomputer, a crazy supercomputer, yeah, with
Speaker 1: five and twelve corps, Yeah, five and twelve corps to
Speaker 1: to calculate the best possible move. If nothing else, this
Speaker 1: kind of says. It kind of points to that the
Speaker 1: huge hurdle of creating an artificially intelligent machine capable of
Speaker 1: thinking in a way that humans think. You know, we
Speaker 1: take it for granted how complicated thinking actually is until
Speaker 1: we try to mimic it using machinery. Because just even
Speaker 1: using something where you've got a a closed environment with
Speaker 1: known rules that you have to follow, it's still incredibly
Speaker 1: difficult to match human performance in that. Yeah, yeah, fascinating
Speaker 1: stuff though, Yeah yeah, And all the players we talked
Speaker 1: about could beat the pants off of me and just
Speaker 1: about any game. There are other computer program problems that
Speaker 1: are interesting to to look at, like um, the people
Speaker 1: who solved checkers, or some of the people who worked
Speaker 1: on the whole checkers problem have moved on to things
Speaker 1: like poker and poker like Texas hold Them and that's
Speaker 1: a game that is also difficult to uh to beat
Speaker 1: or two, it's it's hard to figure out a way
Speaker 1: to program a computer to play that at the same
Speaker 1: level as a human champion. Because you think about poker,
Speaker 1: you're dealing with hidden information because you don't know what
Speaker 1: cards someone else may or may not hold. UM, and
Speaker 1: you're dealing with strategies like bluffing and um. Another thing
Speaker 1: about computers is you can upset them. So you're not
Speaker 1: going to get a computer to play on tilt, but
Speaker 1: you can make a computer think that your cards are
Speaker 1: better than what you hold or or worse, because there
Speaker 1: are a lot of strategies that involve tricking someone into
Speaker 1: thinking that you're holding a weak hand so that they
Speaker 1: over commit themselves in a bet and then you sweep
Speaker 1: in and you just take all that money and then
Speaker 1: you run away laughing and throwing chips at people. That's
Speaker 1: how I Playone likes to play with me, well except
Speaker 1: for the people who pick up the chips because they're
Speaker 1: like awesome free money. So you're saying then that if
Speaker 1: you were playing a computer opponent at poker, you wouldn't
Speaker 1: necessarily need to worry about walking away or running, and
Speaker 1: you might even be able to count your money while
Speaker 1: you're sitting at the table. Yes, that's exactly what I'm saying.
Speaker 1: I mean, even if the machine didn't get upset with you.
Speaker 1: Climb stairs. What a gambler? Yeah, well it's yeah, I'm no,
Speaker 1: I'm not gonna quote anymore from that song. That's done.
Speaker 1: But anyway, Kenny. Nice. Nice, So this will wrap up
Speaker 1: this discussion before I have an aneurysm Um, speaking of running,
Speaker 1: I should probably get to that. Yeah, So it'll be
Speaker 1: interesting to see what what the future of of computers
Speaker 1: and gaming holds, because we've already gotten to a point,
Speaker 1: like I said, where we've reached a state where computers
Speaker 1: can beat the best players in many, not all, but
Speaker 1: many games. Um, will we eventually see UH chess championships
Speaker 1: played between computers? Well, well, will we ever actually say,
Speaker 1: you know what, this comes to a point where we
Speaker 1: have to legitimately award a computer program the title of
Speaker 1: world chess Champion? I doubt it. Well, I mean they
Speaker 1: do use the UH console games on no Play to
Speaker 1: predict the outcome of the Super Bowl. So yeah, but
Speaker 1: I mean, if we allow a chess game to become
Speaker 1: world champions, shouldn't we also allow things like I don't know,
Speaker 1: like the Tesla Roadster to compete in the hundred yard dash. Me.
Speaker 1: I'm just saying, like, you know, you're already stacking the deck.
Speaker 1: I mean, yeah, I don't. Well, I mean it takes
Speaker 1: all the fun out of it for people to Yeah,
Speaker 1: I would hate to get run over by a roadster
Speaker 1: while trying to run the dash. Take the fun out
Speaker 1: of it. But that's a good point. Yeah, So don't
Speaker 1: get run over by a computer, is what what we're
Speaker 1: getting at. It was a long way around to that
Speaker 1: moral of the story apparently. At any rate, if you
Speaker 1: want to learn more about it, you can read the article.
Speaker 1: It's it's about the hang on. I've got the title.
Speaker 1: Actually I supposed to say. I'm about to work my
Speaker 1: way around it. It's top five computer versus human game matchups. Um,
Speaker 1: it's a It was fun to write, and I was
Speaker 1: so pleased that I could find other games besides chess,
Speaker 1: because that's the one everyone thinks of. But there are
Speaker 1: other games out there that people have created programs that
Speaker 1: are you know, these computers are really good at playing
Speaker 1: those games. Haven't found one that can really take me
Speaker 1: on shoots and ladders yet. I'm sure it's coming and uh,
Speaker 1: of course. Sorry. We're gonna wrap this up, you guys.
Speaker 1: If you have any comments or questions, you can contact
Speaker 1: us on Facebook and Twitter are handled. There is tech
Speaker 1: Stuff h s W or you can email us. The
Speaker 1: address is tech stuff at how stuff works dot com.
Speaker 1: And Chris and I will talk to you again really soon, Jonathan. Um,
Speaker 1: actually this was just handed to me. It looks like
Speaker 1: how stuff Works dot Com now has an iPhone app.
Speaker 1: Sweet that awesome. Yeah, actually, um, I got to to
Speaker 1: take a look at this earlier, and guys, this is
Speaker 1: pretty cool. The iPhone app is a sort of a
Speaker 1: way to integrate all the cool stuff we do at
Speaker 1: how stuff Works dot com. So you, guys may have
Speaker 1: listened one of our podcasts and we talked about there's
Speaker 1: this great article on the like, but you're not at
Speaker 1: your computer, so you can't really check it. Well. The
Speaker 1: iPhone app actually lets you browse articles and blog posts,
Speaker 1: even lets you interact on Facebook and Twitter, and you
Speaker 1: can listen to podcasts at the same time. And it
Speaker 1: has all the house stuff works dot Com podcasts on it,
Speaker 1: not just ours, but you know good ones too, so
Speaker 1: you can listen to those and look at the articles
Speaker 1: and and go on Facebook and Twitter, and it should
Speaker 1: work perfectly with your iPhones and iPod touch it awesome.
Speaker 1: What's it looks like. It's now available on the iTunes store,
Speaker 1: so that's good to know. How much does it cost?
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