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Home Artificial Intelligence

Podcast: How games teach AI to learn for itself

by admin
September 30, 2021
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Podcast: How games teach AI to learn for itself
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From chess to Jeopardy to e-sports, AI is more and more beating people at their very own video games. However that was by no means the last word aim. On this first episode of season three of In Machines We Belief, we dig into the symbiotic relationship between video games and AI. We meet the large gamers within the area, and we make a journey to an arcade.

On this episode we meet:

  • Julian Togelius, Affiliate Professor, Division of Pc Science and Engineering, New York College
  • Will Douglas-Heaven, Senior Editor for AI, MIT Expertise Overview
  • David Silver, Principal Analysis Scientist at DeepMind, Professor at College School London.
  • David Fahri, Lead Researcher, Open AI

To make this episode, we additionally spoke to Natasha Regan, Actuary at RPC Tyche, Chess WIM and co-author of “Sport Changer”.

Sounds from:

Credit:

This episode was reported by Jennifer Sturdy and Will Douglas Heaven and produced by Anthony Inexperienced, Emma Cillekens and Karen Hao. We’re edited by Niall Firth, Michael Reilly and Mat Honan. Our combine engineer is Garret Lang. Sound design and music by Jacob Gorski.

Full transcript:

[TR ID] 

[SOT: Jeopardy announces Watson Challenge]

Trebeck: As we speak we’re saying a Jeopardy competitors in contrast to something we have now ever offered earlier than.

Jennifer: Ten years in the past, the tv quiz present Jeopardy unveiled a brand new participant…

Trebeck: It is an exhibition match that includes two of the best jeopardy gamers in historical past… their challenger? Effectively, his identify is Watson. 

Documentary Announcer: [music] Watson is an IBM laptop designed to play Jeopardy. Watson understands pure language with all its ambiguity and complexity.” 

Jennifer: And maybe not surprisingly… provided that taking part in Jeopardy is the factor it was designed to do… Watson was good. Actually good.

[SOT: Montage of Watson Jeopardy answers.]

Trebek: “Watson.”

Watson: “What’s istanbul.”

Trebek: “You’re proper.”

Trebek: “Watson.”

Watson: “What’s parlement.” 

Trebek: “Proper.”

Trebek: “Watson.”

Watson: “What’s historical greek.”

Trebek: “Watson, again to you.”

Jennifer: After three nights of this, Watson gained… beating the 2 greatest gamers within the recreation present’s historical past… From chess to Jeopardy to e-sports… AI is thrashing people at their very own video games… (so to talk)… however that was by no means the last word aim. Researchers try to construct clever programs which are extra helpful and basic goal than something we have now.

David Silver: If the human mind can remedy all types of various duties, can we construct packages that may do the identical factor? 

Jennifer: I’m Jennifer Sturdy and this episode we dig into the symbiotic relationship between video games and AI. As a result of for so long as there’s been AI analysis, video games have been part of it. We meet the large gamers within the area… and we make a journey to an arcade. 

{Sport sounds}

Karen Hao: In a approach, video games have over-hyped AI capabilities somewhat bit, as a result of..

Jennifer: That’s my colleague Karen Hao… 

Karen Hao: Lots of people now consider that AI is way more succesful than it truly is, however video games are literally an indication of extremely slim intelligence. And we’re now type of trapped on this cycle the place AI analysis is particularly happening this path of increasingly more superior video games with out truly going to increasingly more superior, complicated real-world conditions, environments…which is what we really need.

{Sport sounds}

[SHOW ID] 

OC:…you might have reached your vacation spot.

Julian Togelius: Video games have been part of AI since AI began, or like for the reason that very concept of AI began.

Jennifer: Julian Togelius is a professor and laptop scientist residing in New York Metropolis… 

Julian Togelius: I work on AI for making video games higher and in addition video games for making AI higher. 

Jennifer: He’s giving me a historical past lesson on this relationship between video games and AI… and one way or the other, he manages to do it whereas additionally taking part in a couple of video video games that he’s been working with.

Julian Togelius: I notably work with the video video games and form of fashionable video video games as a result of actually chess and Go and all that… I imply, we’re form of completed with that. It is like, I imply, [laughter] to not discourage those who like taking part in chess and like taking part in Go or poker for the psychological problem. That is high-quality. However you realize, there are such a lot of extra prospects, so many extra attention-grabbing challenges within the different video games.

Jennifer: How did you get into this area?

Julian Togelius: Yeah. So when my mother gave my cats away, [laughter] It is true! I imply, she, she obtained allergic and so what are you going to do? So she gave me a pc earlier than a Commodore 64, and I began taking part in all these video games and I obtained actually fascinated by these little, little worlds. After which I grew up… nicely, roughly. [laughter] Uh, I grew up, I completed highschool. I began finding out philosophy and psychology. I used to be keen on, how does the thoughts work? What’s the relationship of consciousness and intelligence and the way does all of it come about? 

Jennifer: These questions introduced him to an early paper by the pioneering laptop scientist Alan Turing… He was the primary to show that constructing a pc was even mathematically doable.

Julian Togelius: That paper is basically about video games. It is concerning the Imitation Sport, what’s now known as a Turing Take a look at, the place you attempt to inform whether or not somebody you are chatting with basically – it wasn’t known as chatting within the fifties – whether or not somebody you’re speaking by way of textual content to is a pc or a human. It is also about chess. As a result of chess grew to become very early on a core focus of synthetic intelligence analysis.  

Jennifer: We expect of people that play chess as having a sure stage of intelligence … and so the sport grew to become a option to gauge how clever machines are too. 

And… enjoyable truth? The very first chess taking part in program was written earlier than a pc even existed to run it. Turing performed it in 1950…utilizing an algorithm labored out on paper.

(It didn’t work very nicely.)

However individuals continued to advance this analysis for many years.  

After which, in 1997, I-B-M’s Deep Blue laptop beat Garry Kasparov… the reigning world champion of chess. 

[SOT] – Deep Blue beating Garry Kasparov in Sport Six by way of YouTube

Commentator 2: Are we lacking one thing on the chessboard now that Kasparov sees? He doesn’t look.. he seems disgusted actually.  

Commentator 1: Whoah! 

Commentator 2: Deep Blue! Kasparov, after the transfer C4, has resigned!

[Applause]

Julian Togelius: And this was an enormous mental occasion individuals have been considering, okay, what now? Did we simply remedy synthetic intelligence? And it seems that no, you did not as a result of this chess taking part in program could not even play checkers with out vital reprogramming. It could not play Go. It could not play a number of issues. And much more, it could not tie its shoelaces. It could not prepare dinner macaroni. It could not write a love poem. It could not exit and purchase a newspaper. It could not do any of these items that people do on a regular basis. It actually might actually simply do one factor. It might play chess. It was rattling good at it, nevertheless it might actually solely play chess. 

Jennifer: So, people had solved what was believed to be the largest problem of making intelligence… however once you seemed below the hood of this system… he says It was basically only a type of search.

Julian Togelius: What if I take this transfer? After which, what if my adversary takes this transfer, then what if I take this transfer? So we would constructed a tree of prospects and counter prospects and calculated from that. It was truly way more sophisticated than that, however that is the guts of what it was doing. And folks checked out it like, this does not appear to be something like how our brains work. I imply, we do not actually know the way our brains work, however, um, no matter they’re doing, it is not this. [laugh]

Jennifer: However it is not JUST used to play video games in opposition to people… AI reveals up in video games in all kinds of the way.  Particularly to make them extra attention-grabbing and difficult.

For instance…. AI adjustments components of video video games…  so that they are completely different each time we play them, and that is been the case for the reason that 19-80s.

Julian Togelius: And this precept of, like, at all times creating one thing new… and each time you play the sport it is new… has survived into plenty of completely different video games. For instance, the Diablo sequence of video games relies on that, or the Civilization sequence of technique video games. Each time you play it you might have a totally new world and that is core to the sport. It simply would not be the identical in the event you did not do this. 

Jennifer: Another excuse to do that is due to storage… and he says a recreation known as Elite grew to become an essential milestone… when it was made out there for private computer systems, together with the Commodore 64. 

Julian Togelius: It could not probably slot in reminiscence on this laptop. So one model had 4,096 completely different star programs. Now, in the event you solely had 64,000 bytes of reminiscence and picture, consider how little that’s, that is a millionth of a pc you should buy right now. So, they needed to recreate the star system each time you bought there. Principally construct it up from scratch.

Jennifer:  And that’s nonetheless the case now. Positive, we have now way more storage. However video games are additionally a lot, a lot bigger and extra complicated. 

Julian Togelius: The sport of No Man’s Sky, which got here out 2016, however they hold updating it – it retains getting increasingly more spectacular. It has extra planets in it than you could possibly ever go to in a lifetime, nevertheless it one way or the other all suits in your laptop as a result of they’re recreated each time you see them. 

Jennifer: In the meantime, researchers have additionally continued to construct recreation taking part in AIs… and Togelius says, one of many subsequent challenges in that area will likely be for them to play many video games without delay… as a result of multitasking is one thing people do nicely…however that’s not but the case for these programs.

So, how can we get from these extremely structured environments with a number of predictability… to one thing nearer to actual life, which is messy and chaotic and by no means predictable.

To him and different researchers…? We play extra video games.

Julian Togelius: If we had a system that would reliably play, like with some proficiency, the highest hundred video games on a pc recreation high checklist, like Steam or the AppStore or one thing, then we might have one thing akin to basic intelligence. 

Jennifer: So, in some methods… we’re nonetheless type of the place we have been a half century in the past… considering we’d simply discover the important thing to basic intelligence with AI programs that may beat people at their very own recreation. 

[beat / music]

However we additionally combine video games and AI in all kinds of different methods…like to assist us with coaching information.

A couple of years in the past I met a workforce at Princeton making an attempt to make cease indicators extra recognizable to self-driving automobiles… utilizing the sport, Grand Theft Auto. 

Unusual as that may sound… it’s truly fairly sensible when you think about simply what number of other ways a driver may come throughout a cease sign up the actual world… be it on a stick within the floor… hanging within the air… or painted on the pavement… and we encounter them in each type of gentle and climate… generally partially hidden by tree branches… or the darkness of evening. 

Researchers might go searching for examples of all these cease indicators… or video video games can simply generate limitless examples.

We’re additionally utilizing video games to raised perceive how algorithms make selections. 

[Start to bring in sounds from Arcade. *Frogger theme music and gameplay begins, toggle moves*] 

Jennifer: We’re at a basic arcade in Boston… as a result of it has a number of of those older video video games which are used to coach A-I programs. 

Will Douglas-Heaven: Hello, I’m Will Douglas-Heaven. I’m senior editor for AI at Expertise Overview… And I can not play Frogger. 

Will Douglas-Heaven: Frogger got here up fairly not too long ago in some completely different AI analysis the place they have been making an attempt to get an AI to clarify itself and clarify like what it was doing. Um, and so they taught… they skilled an AI to play this recreation and you realize Frogger… You’ll be able to hear from the noise, I hold failing.

So Frogger is that this recreation the place you are somewhat frog down the underside and you have to cross a highway that has automobiles shifting form of throughout the display left and proper , and you have to form of dodge between them. And you then get to a river and also you soar on the again of turtles and logs to get to the opposite facet with out falling in like I did there. Um, anyway, so it is, it is a recreation which has obtained like a number of particular actions you’re taking at every step. And so once they skilled the AI to do it, each time it took an motion, they obtained it to clarify in, um, form of, you realize, human comprehensible phrases why it did that.

[*Game sounds continue*] 

Jennifer: Principally, A-I performs the sport… and over time, it really works out how you can succeed. Random strikes evolve into complicated methods… even some we did not find out about. 

[Continue games sounds underneath the VO above and also into this piece of audio]

Will Douglas-Heaven: They threw the AIs at these outdated video games and simply confirmed them the screens that they’d no concept how you can play. It was simply pixels on a display, stuff occurred. They tried issues and generally they blew up. Typically they shot the alien ships. And utilizing solely form of rewards from you realize once they did one thing, proper, the rating went up, they slowly labored out how you can play the sport. They usually went from understanding, nothing to, in lots of circumstances, form of beating the excessive scores of the very best human gamers. And even some actually cool examples the place they really discovered methods to beat the sport that people hadn’t found.

Jennifer: One instance of this comes from a recreation known as Q*Bert, which places gamers on a pyramid of squares. 

Will Douglas-Heaven:  I imply the essential concept is you have obtained this little man who jumps down the pyramid from the highest touchdown on the squares. And once you’ve modified the squares all to the identical shade, then you’ll be able to transfer on to the subsequent stage. However the AI, I feel on the primary stage, modified all the colours of the squares after which saved leaping up and down the squares fairly than shifting on to the subsequent stage. And it discovered some bug within the recreation that allowed it to form of get an infinite rating in actually a brief period of time. And even the designers of the sport have been like “ I have not seen that bug  earlier than.” 

Jennifer: After the break… We’ll meet some pioneers behind main breakthroughs  on this area. However first, I wish to inform you about an occasion known as CyberSecure in November. It’s Tech Overview’s cybersecurity convention and I will be there with my colleagues. You’ll be able to study extra at Cyber Safe M-I-T dot com.

We’ll be proper again… after this.

[MIDROLL]

David Silver: My identify’s David Silver. I work on synthetic intelligence and I apply it to video games. I work for an organization known as DeepMind and our aim is to attempt to use, um, synthetic intelligence to attempt to construct a system, which has among the smarts which are contained in the human mind.

Jennifer: DeepMind is on the middle of this work with video games. It’s a analysis lab that’s a part of Google’s Alphabet.

David Silver: If the human mind can remedy all types of various duties, can we construct packages that may do the identical factor? 

Jennifer: He’s the lead researcher behind among the greatest recognized AI programs that  have mastered how you can play video games… beginning with board video games, (together with the traditional Chinese language technique recreation of Go.) 

David Silver: We developed a system known as AlphaGo, which was the primary program to have the ability to play the sport of Go on the stage of high human skilled gamers. And actually, it was in a position to beat the world champion Lee Sedol. 

David Silver: And there is this big area of video games, a lot of which have these lovely traits that enable us to essentially simply dive in and perceive, you realize, one piece of the world in isolation with out having to take care of the entire immense complexity of the actual world unexpectedly.

Jennifer: AlphaGo discovered how you can play board video games primarily based on how individuals play.

Silver’s subsequent system, AlphaZero, discovered to play board video games and video video games differently… by studying the principles of a recreation after which taking part in itself time and again.

David Silver: After AlphaGo, we tried to take the subsequent step and make one thing much more basic, which was to have the ability to play not only one recreation, however many video games utilizing the identical expertise. And it is a large stepping stone as a result of it truly is making an attempt to do one of many issues which we, as individuals are in a position to do, which is remedy many issues, utilizing the identical sorts of equipment inside. 

Jennifer: It is a milestone in making AI extra basic goal… However with an essential caveat. The algorithm can’t study to play these video games unexpectedly. It’s as if it builds itself separate brains for every recreation. So it has to swap out its chess mind earlier than taking part in Go. 

It’s protected to say researchers are nonetheless making an attempt to determine how you can make video games a take a look at for actual life. As a result of video games have guidelines that may be outlined… and nobody actually is aware of the principles by which the world works.

David Silver: The world can be a messy place. You realize, it is obtained this extremely wealthy dynamics occurring, all types of particulars in the way in which that objects transfer round. The way in which that the issues we see relate to the issues that we contact. There’s simply this unimaginable richness and complexity to the actual world. And we won’t probably hope to handle that in the way in which that folks traditionally have approached video games. So what we’d like is one thing which might perceive the world for itself in a approach that type of understands the patterns in a approach which is beneficial for it to make selections which are truly significant in serving to to realize its objectives. 

Jennifer: His newest undertaking is named MuZero. It excels at simply as many video games as AlphaZero… (in addition to a complete host of video video games). 

…however this technique figures out how you can play with out being given any guidelines in any respect.

David Silver: So it was actually simply let unfastened. It was in a position to play video games in opposition to itself. And all it obtained on the finish of the sport was a sign to say, Hey, you gained or Hey, you misplaced. And from that sign, it was in a position to construct an understanding for itself of the principles of the sport sufficient that it might truly form of think about what would occur into the long run.. And as soon as it had this capability to  think about into the long run, it was in a position to search and begin trying forward and begin considering into the long run and saying, aha, now I perceive how this world works. I can begin to think about what would occur if I performed this transfer or took this motion. And in order that’s actually a key step that we’d like and one thing we consider is essential going ahead for the way forward for A-I.

Jennifer: He says it’s not in contrast to an toddler coming to grips with the world round it… constructing drawback fixing and artistic abilities, over time. 

David Silver: I feel we’re already seeing examples the place, inside constrained domains, that we see algorithms which are to all intents and functions, inventive. I imply, what’s creativity in spite of everything aside from, you realize, the power to find some new concept for itself. And I feel that is the essence of creativity. The essence of creativity is what our algorithms are doing, which is to find step-by-step one thing new and to study by way of their expertise that this new concept that they’ve provide you with is definitely one thing which is highly effective and which helps it to realize its objectives. So I feel sooner or later, we’ll see increasingly more creativity of this kind. We’ll see, you realize, machines that are in a position to uncover for themselves concepts that assist them to realize objectives. Not as a result of an individual’s advised them, that is the factor you must obtain that aim, however as a result of they figured it out for themselves.

Jennifer: And.. that creativity has led AlphaZero to find new issues about how you can play chess. Now…. human gamers are literally adopting it in their very own video games … calling it.. “taking part in an alpha zero transfer”.

[SOT: how to play like AlphaZero]

Host: “Welcome to a different version of How you can Assault lLike AlphaZero! I hope you might be prepared for right now’s lesson….”

Jennifer: That’s additionally taking place with e-sports… that are online game competitions which are typically performed in entrance of a stay viewers… just like a sporting occasion… With a worldwide viewers of practically half a billion viewers tuning in to look at their favourite video games performed by among the greatest players on the earth. 

Right here too, AI is being utilized in a bunch of the way… like teaching instruments to assist individuals get higher at taking part in… and (as soon as once more), researchers are additionally aiming to make use of e-sports to make their AI programs extra clever…  

David Farhi: We’re imagining that in some unspecified time in the future there will be basic synthetic intelligence programs that may actually remedy issues shortly, can study perhaps on the stage of people. 

Jennifer: David Farhi is a lead researcher at Open AI… The analysis lab based by Elon Musk and a bunch of different Silicon Valley luminaries.

It created the primary system to beat world champions at an e-sports recreation. 

That recreation is named Protection of the Ancients 2, which everybody calls Dota 2… and there’s a brand new documentary about this win… known as Synthetic Gamer.

[Clip from Artificial Gamer trailer]

[Dramatic music and sounds from Dota 2 gameplay] 

Speaker 1: If you have a look at the sport of Dota, there’s 10,000 plus variables in each second that your system has to soak up.

Speaker 2: The AI learns in a really completely different approach than people. 

Speaker 3: It performs in opposition to copies of itself. Many, many instances off within the cloud..

Jennifer: Fahri oversaw the Dota 2 undertaking, known as the Open A-I 5… and he demonstrated the way it works at Tech Overview’s A-I convention, EmTech Digital… 

[Sounds of Dota 2 gameplay via YouTube. [00:03 – 00:15] Fade in, then mattress below the next Farhi choose. *Sword combating, footsteps, and dramatic battle music.*]

David Farhi: Within the higher proper nook of this display. We see a really large, zoomed out, view of the entire world of Dota, Within the decrease left nook there’s one workforce’s base. Within the higher proper nook is one other workforce’s base. Every workforce is making an attempt to maneuver their characters round, forged spells with their characters, assault the enemies and so forth to in the end invade and destroy the opposite workforce’s base.

David Farhi: These extra sophisticated programs like robotics and video video games have a special really feel to them since you get an commentary of the state of the sport, and you then select an motion to take. After which the state of the sport adjustments in a roundabout way, relying on the motion you took. And you then’ve obtained a brand new commentary and you’ll select a brand new motion and this loop occurs over and time and again. And so you must make selections which have long-term penalties down the highway. So the way in which we do that is comparatively easy. Conceptually not less than. We now have brokers that begin out taking part in completely randomly. And we simply need to play them in opposition to themselves, a clone of themselves over and time and again.

Jennifer: And in the event you’re considering this may take a very very long time with such a sophisticated recreation? You’re not flawed… however Open AI’s capability to run it on 200-thousand machines without delay… helps. 

Principally… it’s in a position to achieve about 250 years of expertise per day.

And if the system does one thing that works… it’s up to date to do this factor extra… and if one thing dangerous occurs that doesn’t work, it does that factor much less. 

David Farhi: We began out with a restricted model of the sport. We have been finally in a position to beat our developer workforce, which was very enjoyable. After which we added extra items of the sport. We went again and skilled for longer. And we have been in a position to beat some amateurs after which some semi-professional people. Ultimately we determined to go to a big match that this recreation has..

[Sounds from The International 3 (Dota tournament) via YouTube. *Crowd cheering, sports commentators shouting excitedly, Dota gameplay.*] 

Sportscaster: It might be their final stand. [inaudible]

Sportscaster: He is gonna attempt to focus all people however there’s a lot stuff. 

Sportscaster: There isn’t any extra clips out there. Right down to about half HP. 

Sportscaster: 1 / 4 HP. A lion surrounding from all sides! EKB! Sportscaster: They gained the spherical! They’re gonna do it! 

Sportscaster: The kings of the north! Alliance wins! They win TI 3. 

Sportscaster: The Alliance simply gained 1.4 million {dollars}! 

Sportscaster: They’re your Worldwide 3 champions! 

David Farhi: So this recreation has thousands and thousands of human customers who compete in these  tournaments for big prizes, which ensures that we all know there are people who’re taking part in at a really, very excessive stage of talent. In August of 2018, we took our agent to this match. 

Jennifer: Their AI performed in opposition to two skilled groups that had already been eradicated from the match… and narrowly misplaced. However the next 12 months, with extra coaching, the AI was in a position to beat the previous world champions 2 – 0.

David Farhi: So OpenA-I 5 is skilled with no people within the coaching course of, so it simply performs in opposition to itself in these cloud servers again and again and time and again. After which after we wish to play it in opposition to a human, we take a snapshot out of the cloud and play it in opposition to the human, however we by no means feed that information again into the coaching course of.

[Music] 

Jennifer:  However there’s nonetheless this query of whether or not video games might help us prepare AI to be extra helpful. 

Proper now, we have now programs which are extraordinarily good at one factor. However we do not but have fashions that may do a number of issues without delay. 

As soon as once more, my colleague Will Douglas Heaven.

Will Douglas-Heaven: The trick goes to be, I feel stepping again from constructing AI’s that, excel at particular methods or strategies, or have an excellent workaround for this specific rule or transfer, you realize, the type of factor that we have been seeing in these AIs that may study to play video games. 

Jennifer: To essentially perceive the subsequent stage of this analysis… It may be useful to consider the way in which youngsters play on a playground. 

Will Douglas-Heaven: They don’t seem to be taking part in a recreation that has any form of actual set guidelines. I imply, they might make them up as they go alongside, however, you realize, they’re simply exploring, making an attempt stuff in and out a really form of pure and open-ended approach. And there is no particular aim that they are working in the direction of. And I feel it is this sort of approach, which remains to be a type of play, that we will see, you realize, actually push issues ahead after we discuss basic intelligence. Deepmind, for instance, a couple of months in the past launched a digital playground. It is form of like a online game world known as X Land. And it is populated by a bunch of little bots. And the neat factor right here is that X Land itself is managed by an AI or form of like a video games grasp that rearranges the surroundings, rearranges the obstacles and the blocks and the balls the little bots get to play with, and in addition comes up with completely different guidelines on the fly. So, easy video games like tag or conceal and search, and the bots simply need to work out, you realize, how you can play these. You realize what objects in that digital world will assist them to do it. They usually study basic abilities like exploring, simply making an attempt stuff out And I feel this sort of open-ended exploration goes to be key for the subsequent technology of AI. And it is type of thrilling that the [00:09:00] subsequent wave of AI, the AIs which are going to be good at a number of issues, [00:09:03] We // nonetheless may get there by way of video games once more. So video games aren’t going anyplace. Video games have been with AI for the reason that starting. And you realize, it is good to see that play remains to be maybe the easiest way of studying. 

[CREDITS]

Jennifer: This episode was reported by me and Will Douglas-Heaven… and produced by Anthony Inexperienced, Emma Cillekens and Karen Hao. We’re edited by Niall Firth, Michael Reilly and Mat Honan. Our combine engineer is Garret Lang… with sound design and music by Jacob Gorski. 

Thanks for listening, I’m Jennifer Sturdy. 
[TR ID]



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