**Winning MONEY with AI – Understanding Algorithms & Predicting March Madness with Neil deGrasse Tyson — Transcript & Summary | SozAI**
Source: https://sozai.app/transcript/winning-money-ai-algorithms-predicting-march-madness/

Explore how AI and algorithms are used to predict March Madness brackets and the challenges of achieving a perfect bracket.

## Key Takeaways

- A perfect March Madness bracket is nearly impossible to achieve, even with AI.
- AI can improve your chances of making better predictions than average bettors or odds makers.
- Game theory and chance play significant roles in sports outcomes.
- Data quality and understanding player conditions are crucial for AI predictions.
- AI is a tool to gain an edge, not to predict the future perfectly.

## What the video covers

- Introduction to March Madness and the difficulty of predicting a perfect bracket.
- Discussion of Warren Buffett's Berkshire Hathaway bracket challenge and the improbability of winning.
- Introduction of AI expert Matt Ginsberg, aka Dr. Phil, and his background in AI and crossword puzzle solving.
- Explanation of AI's role in improving bracket predictions but the impossibility of perfect prediction due to chance.
- Overview of game theory and its application to athletic contests and betting.
- Details on the structure of NCAA March Madness as a single-elimination tournament with 64 teams.
- Discussion on how AI can make bettors better than average opponents but not omniscient.
- Insights into the use of data, player conditions, and external factors in AI-driven predictions.
- Exploration of the limits of AI in predicting outcomes perfectly due to randomness and unknown variables.
- Emphasis on AI's potential to improve betting strategies rather than guarantee perfect results.

## Chapters

1. 00:00 Introduction and March Madness Overview
2. 03:51 AI Expert Matt Ginsberg and AI Background
3. 07:36 Game Theory and AI in Sports Betting
4. 11:16 Understanding Brackets and Tournament Structure
5. 14:38 Limits of AI in Perfect Predictions
6. 18:20 Data and Player Factors in AI Predictions
7. 22:04 Conclusion: AI's Role in Improving Betting

Answers

## Questions about this video

Can AI create a perfect March Madness bracket?

No, AI cannot create a perfect bracket because predicting every game outcome perfectly involves too much chance and unknown variables.

How does AI improve bracket predictions?

AI uses large datasets, player stats, and game theory to make more informed predictions, improving chances against average bettors and odds makers.

What is the structure of the NCAA March Madness tournament?

The tournament features roughly 64 teams in a single-elimination format where each game eliminates one team until a champion is crowned.

## Full Transcript — Download SRT & Markdown

00:02

Speaker A

[Music] This is StarTalk Sports Edition, and of course, I've got Gary O'Reilly. Gary, hi. Neil, Gary is our only street cred we have for this programming, having been a professional athlete himself and a professional sportscaster over in the UK.

00:22

Speaker A

Uh, in the soccer realm, yes. And Chuck Nice, always good to have you here, man. Always a pleasure. Yeah, the one person who has done no organized sports in his entire life. I mean, actually, you could have just said has done nothing and just left it there, and you would have been spot on.

00:35

Speaker A

Gary, March is looming, and so what do you have in store for us today? All right, um, perfect, a little bit of March Madness. The NCAA's March Madness college basketball is approaching. Um, and if you work, and I'll say this in an English way and then again in America, and if you work for Berkshire Hathaway or Berkshire Hathaway, right, you nail a bracket because it's all about brackets, brackets, brackets.

00:51

Speaker A

You get some of Warren's money, really? Yes. Who, who he said this? Mm-hmm. Yeah, so you have to be a company employee. Sometimes they open it up to the public, but generally it's a close shop for Berkshire Hathaway employees only. You can get up, you can get a hundred thousand if you do a decent job, or if you nail a perfect bracket, you get a million dollars a year for life, right? In other words, in other words, play the lottery.

01:07

Speaker A

People just, just go with your state lottery. Chuck, I think, I think, uh, I think he knows nobody's going to win that, so he's letting you do it, and he ends up with more money at the end.

01:24

Speaker A

Anyway, yeah, that's my point. It's like you got a better chance of winning your state lottery than you do of picking a perfect bracket, so that's just it. How do you pick a perfect bracket now if it's beyond our human brains to achieve that?

01:38

Speaker A

And we know Warren's a very, very wealthy man because he doesn't give his money away, so he's holding on to his money. But is there a way, is there a way to break the system, break the bank, and get Warren's dough? Possibly, but for someone, we need an AI expert. I know only one person for that, and he's a friend of StarTalk, has appeared before, and that's one and only Dr. Phil. Have to explain that in a moment. Matt Ginsberg, Matt, welcome back to StarTalk, dude.

01:52

Speaker A

Thank you. It's always a blast to be here.

02:06

Speaker A

Yeah, so we call you Dr. Phil because those in the know know that you programmed a computer to solve crossword puzzles, and you named that program Dr. Phil. That was just Bro Phil, F-I-L-L. Brilliant. And so you've got, how's that working out for you?

02:18

Speaker A

I see you making crossword puzzles just fine. Um, and actually, Dr. Phil beat all humans, and, uh, it, and I retired from crosswords.

02:36

Speaker A

Well, once you've beaten every single human, it's time to go on to something else, right? So let me get this category out here. Let me finish the man's pedigree, please.

02:54

Speaker A

Okay, he's got a PhD in mathematics from none other than Oxford University, and I don't think that's Oxford, Mississippi. I think it's Oxford, UK. A scientist, entrepreneur, author, and, uh, your specialist in AI, especially when it comes to solving hard problems rather than just sort of taking over the world, and now gainfully employed at Google. So what do they have you doing at Google?

03:15

Speaker A

Okay, oh well, you know, I'm building Chromebooks. Terrible misallocation of resources, that's all I can tell you. They brought me in, I'm an AI specialist, and they were like, all right, we need you to build some Chromebooks.

03:31

Speaker A

Yeah, because everyone at Google is brilliant. He's at the low end. So I actually, I repair Chromebooks. I don't get to build Chromebooks. I'm aspiring, so that a few years from now moving up, actually building Chromebooks. I, and in my spare time at Google, I work for Google X, which is a moonshot factory. We basically try and solve incredibly hard problems, any one of which is likely to fail, but between them all, we expect to deliver a reasonable amount of useful technology to the real world.

03:51

Speaker A

So that's a name inspired, presumably, by the X Prize, which is money given to, uh, impossible tasks solved by brilliant people. I, I, they haven't told me where it came from.

04:06

Speaker A

Okay, it may have been around for a long time. I do, I bet, I don't know. Trust me, I think I got that one squared out.

04:21

Speaker A

Okay, I think you probably did, and I just want to say that all of this disclaiming, you know, Chuck saying I have never played a sport. I mean, he sounded like he's never even watched a sport. When I was at Oxford, I was the captain of the bridge team, and we actually tried to get bridge recognized as a real sport so that we could get Oxford blues and put them on our shirts and be official athletes. They were having none of it. Chuck, you and I are in the same boat here.

04:40

Speaker A

Okay, well then I'm in very good company. I feel better.

04:58

Speaker A

All right, so tell me then about game theory broadly, AI specifically invoked to predict brackets in athletic events, and the most famous of all brackets, as Gary said, is the March Madness with college basketball. You know, when I think of game theory, I think of elements of chance and how you can sort of maximize those to your favor. But how much do we think of athletic contests as exercises in chance? As Gary introduced this topic, and he said, you know, can we use AI to build a perfect bracket? And I can say I can just save a lot of time here. No, that's it. No, and okay, that's the end of the show.

05:11

Speaker A

Thank you very much. This has been a real blast. I think, I think what you have to understand when you're betting, whether you're betting against Berkshire Hathaway or you're betting against Vegas or you're betting against your buddy who lives down the street, you have an opponent, and AI can make you better. But when you try and make a perfect bracket, your opponent at some level is like God. You're actually trying to predict the future, not better than the next guy, but perfectly. AI can't make you better than God or as good as God as anything. But what it can do is it can make you potentially better than the guy who lives down the street, so that you rate to make money. It can make you maybe better than the guys in Vegas who are quoting the odds. So you go to Vegas, and you rate to make money, and I think that's where we can potentially add value. I don't know if this counts as value. We can make a difference.

05:26

Speaker A

That, okay, very important point to distinguish there, just being better than your opponent versus having all knowledge of all of creation. You just want to make some money tomorrow, and that's all. So could you explain just in, just in as few words as possible, what do brackets mean? Just, I don't know why someone who would be listening to this program would not know about brackets, but just, I'm an educator. I just want to make sure we're all on the same page. Describe the concept of brackets.

05:40

Speaker A

So the NCAA, the March Madness tournament, they're roughly speaking, 64 teams, and it's a single elimination. So every game, one team is eliminated. If you want to get down to a winner, you got to play.

06:00

Speaker A

march, madness, with college, basketball, you, know, when, i, think of game, theory, i, think, of elements, of, chance, and, how, you, can, sort of, maximize, those, to, your, favor but how, much, do, we, think, of athletic, contests, as, exercises, and

06:16

Speaker A

chance as, gary, introduced, this, topic, and, he said, you, know, can, we, use, ai to build, a, perfect, bracket and, i, can, say, i, can, just, save, a, lot, of time, here, no that's, it, no and, okay, that's, the, end, of, the, show

06:32

Speaker A

thank, you, very, much this, has, been, a, real, blast i, think, i, think, what, you, have, to understand when, you're, betting, whether, you're betting, against, berkshire, hathaway, or you're, betting, against, vegas, or, you're betting, against, your, buddy, who, lives

06:50

Speaker A

down, the, street you, have, an, opponent and ai, can, make, you better but, when, you, try, and, make, a, perfect bracket, your, opponent, at, some, level, is like, god you're, actually, trying, to, predict, the future, not, better, than, the, next, guy, but

07:08

Speaker A

perfectly ai, can't, make, you, better, than, god, or, as good, as, god, as, anything but what, it, can, do, is, it, can, make, you potentially, better, than, the, guy, who lives, down, the, street, so, that, you, rate to, make, money, it, can, make, you

07:23

Speaker A

maybe, better, than, the, guys, in, vegas, who are, quoting, the, odds, so, you, go, to, vegas and, you, rate, to, make, money and, i, think, that's, where we, can, potentially, add, value i, don't, know, if, this, counts, as, value, we

07:36

Speaker A

can, make, a, difference, that, okay, very important, point, to, distinguish, there just, being, better, than, your, opponent versus, having, all, knowledge, of, all, of creation you, just, want, to, make, some, money tomorrow, and, that's, all, so, could, you

07:50

Speaker A

explain, just, in, just, in, as, few, words, as possible what what, do, brackets, mean just i, don't, know, why, someone, who, would, be listening, to, this, program, would, not, know about, brackets, but, just, i'm, an, educator i, just, want, to, make, sure, we're, all, on

08:05

Speaker A

the, same, page, describe, the, concept, of brackets so the, the, ncaa the, march, madness, tournament, they're roughly, speaking, they're, 64, teams and, it's, a, single, elimination, so, every game, one, team, is, eliminated, if, you, want to, get, down, to, a, winner, you, got, to, play

08:25

Speaker A

63, games, to, eliminate, 63, of, the, 64, teams so, they, divide, it, and, they, try, and, set it, up so, that, better, teams, are, playing, worse teams, at, least, initially and, that, way, the, better, team, sort, of having, the, easier, path, and, they, get, to

08:40

Speaker A

the, end, and, the, better, teams, keep playing, and, if, you, can, predict, who's going, to, win, each, of, these, 63, games you've, nailed, the, bracket, in, gary's terms if, you, get, one, wrong a, team, that, you, thought, was, going to, be

08:54

Speaker A

eliminated, plays, on and, you, didn't, get, the, black, bracket right so, if, every, game, were, a, coin, toss they're, asking, you, to, predict, 63, coin tarsas in, a, row, correctly and, your, chances, of, doing, that, are, you know, two, coin, tosses, it's, one, and, four

09:14

Speaker A

three, it's, one, and, eight 63, it's, one, in, some, giant, number, that i'm, not, even, going, to, try, and, compute you, can, say, it, it's, astronomical, say, it say, it, it's, astronomical thank, you, so, if, they, have, 64, teams, you

09:32

Speaker A

know, normally, we, see, it, like, as, a diagram, there's, like, 32, teams, on, one half, 32, on, the, other, half, and, then, they whittle, down, and, then, you, have, 16, and, 16 eight, and, eight, four, and, four, two, and

09:42

Speaker A

two, one, and, one, that, so, these, are, this is, the, bracketing, is, that, how, we, can think, about, it, it, is, and, people, people think, of, it, as, the, first you're, going, to, play, 63, games, the, first 32, games, are, the, first, round, they, sort

09:56

Speaker A

of, happen, simultaneously, after, those, 32 games, 32, teams, have, been, eliminated, so you've, gone, from, 64, teams, to, 32 the, second, round, you, can, play, 16, games simultaneously, that, brings, you, down, to 16, teams the, sweet, 16, then, the, elite, eight, and

10:13

Speaker A

then, the, final, four, and, then, the, finals and, then, the, winner but, if, you, know, that, one, team, is, going to, win, you, don't, care, about, who, else loses, right, so, why, do, you, have, to predict, all, 64, games, correctly

10:25

Speaker A

that's, the, only, way warren, will, give, you, his, money is, if, you, get, them, all, right, so, picking who's, going, to, win that's, not, so, bad, i, mean, at, worst, that's 1, in, 64., if, it's, random, you, have, a, 1, in

10:38

Speaker A

64, chance, but, picking, who's, going, to, win every, game that's, 63, coin, tosses, which, is what, i, think, it's, called, astronomical okay, i, just, calculated uh the, odds, if, all, each, were, a, coin, flip what, it, would, take, to, predict, 60

10:56

Speaker A

for, outcomes, 63, so, i, get, uh, basically uh, 2, times, 10, to, the, 19th, power, so that's, uh, a, lot, a, lot the, answer, is, that's, a, lot that's, that's, uh, that's sorry, so, that's, uh, 20 let, me, get, a, uh

11:16

Speaker A

uh, 20, quintillion is, what, that, is, wanting, 20, quintillion so, i'm, on, the, right, page, i'm, on, a, good page, here, now, so, chuck, gary, you, got, a good, page, yes, all, right, so, if, we, say that, 20, quintillion, is, just, too, much, for

11:31

Speaker A

us, to, really, grapple, with what, what, would, we, need, matt, to, to, to understand, and, comprehend, to, build, a, bra you, know, a, system, to do, really, well, at, brackets is, there, are, there, some, fundamentals that, you, have, to, bake, into, an, algorithm

11:49

Speaker A

to, be, able, to bring, forward something, that, would, have, some, success so, my, question, is, what, does, really, well mean, right, and, this, is, why, your, opponent matters, if, really, really, well, means getting, it, all, right, and, getting

12:04

Speaker A

buffett's, money the, answer, is pick, another, project, yeah, it's, just, too hard, if, doing, really, well, means getting, enough, of, them, right, that, you win, money, in, vegas now, we, can, talk because, now, there's, all, sorts, of, stuff, i

12:19

Speaker A

can, tell, you, about so, in, terms, of, why, it's, so, hard imagine, you've, got, two, reasonably, evenly matched, teams, playing, and, you, can, really predict, it, you, can, look, at, the individual match-ups, and, you, can, say, oh, this, is

12:34

Speaker A

actually, going, to, go, really, well, for these, guys, you, look, at, who's, injured but, what, you, don't, know is, that, halfway, through, the, second quarter somebody, is, going, to, slip on, a, on, a, little, bit, of moisture, on, the, floor, and, twist, their

12:50

Speaker A

ankle, and, be, out you, can't, predict, that, but, the, game, can easily, hinge, on so, there, is, just, stuff, that, makes, this more, like, a, coin, flip, that, you, just can't, figure, out, in, advance, now, the, good news, is

13:06

Speaker A

both, teams, are, probably, equally, likely to, slip, on, that, moisture so, if, you, conclude, team, one, is, 80, to, win the, game, then, team, one, probably, is, about 80, to, win, the, game, but, if, you, have, to get, 63, right, in, a, row

13:20

Speaker A

80, isn't, good, enough, in, a, minute, i'm going, to, ask, you, what, an, algorithm, is because, i, think, we've, we, all, i, me, if, i look, at, it, from, my, own, personal, point, of view, i, can, say, algorithm, i, know, they're

13:30

Speaker A

used, they're, in, my, smartphone, they, can dictate, trends, from, on, a, youtube, channel all, those, things, but, what, is, an algorithm we, we, talk, about, it, but, i, talk, about, it but, i, don't, know, exactly, what, one, is

13:43

Speaker A

what, you, would, bake, into, an, algorithm, do you, have, to, have, the, outcome set, in, your, mind, in, advance, and, then build, it, backwards, from, there, so, i, mean if, it, sort, of, dismantled, it, like, a, car engine, what, do, we, get, with, an, algorithm

13:56

Speaker A

so an, out, an, album, algorithms, are, simple right, they're, just telling an, idiot a, computer, but, fundamentally, an, idiot telling, an, idiot, a, sequence, of, steps, to pay get, the, answer, to, some, problem, a, really competent, idiot, yes

14:15

Speaker A

well, it's, a, it's, i, don't, know, the company, they're, not, computers, aren't really, actually, that, competent, you, can't ask, them, anything, sort, of, coherent, but they're, really, fast, my, favorite, line, for computers, from, decades, ago, was, a computer, doesn't, do, what, you, want, it, to

14:29

Speaker A

do, it, does, what, you, tell, it, to, do, tell it, to, do, yeah, what, you, program, it, to, do and, that's, not, always, what, you, wanted, to do, yeah, that's, what, they, used, to, say garbage, and, garbage, out, yeah, yeah

14:39

Speaker A

so, john, mccarthy, um was, one, of, the, people, who, invented, ai and, he, said, ai, was, the, attempt, to, get machines, to, do, badly, what, people, do, well so guys, you, got, to, take, a, quick, break, but when, we, come, back, we'll, pick, up, that

14:58

Speaker A

conversation, on, algorithms, but, we, also want, to, know, in, what, detailed, way, is, ai operating, to, make, these, decisions, when star, talk, sports, edition, returns back, star, talk, sports, edition, we're talking, about, bracketology, if, there, is even, such, a, word, we, have, friend, of, star

15:19

Speaker A

talk, matt, ginsberg, who's, all, about, ai and, betting, and, winning, bets, not, against god, apparently, this, was, first, disclosed in, this, episode, but, against, your opponents, so if, you, beat, god, that's, a, whole, other kind, of, what, else, you, got, cooking, in

15:34

Speaker A

your, in, your, basement, there, so let's, pick, up, the, algorithm, question gary, where, were, you, where, did, we, leave off well from, my, own, point, of, view, i, mean i, look, at, it, i, say, i, i'm, familiar, with

15:46

Speaker A

algorithms, but, i, don't, actually, know what, one, does, how, it, works, why, it, works um, so, i, just, wondered, if, we, had, that seeing, as, how, it's, difficult, to, play, god with, an, as, an, algorithm, and produce, perfect, brackets

16:00

Speaker A

maybe, we, could, get, matt, to, just, break down, a, little, bit, of, what, an, algorithm can, do, and, what, why, it, does, it, and, how it, does, it, and, and, how, can, it, be predictive it's, one, thing, to

16:12

Speaker A

have, the, machine, do, what, you, tell, it, to do, but, how, do, you, tell, it, to, predict something, that, maybe, has, not, happened so, the, thing, the, thing, to, remember, here is, that like, i, said, algorithms, are, incredibly

16:28

Speaker A

simple, they're, just doing, what, you, tell, them, to, do i, could, say i, want, you, to, predict, the, weather tomorrow and, if, i lived, in the, sahara, desert i, could, write, an, algorithm, it, would, say sunny, and, hot

16:46

Speaker A

yeah, every, day, just, say, stunning you'll, be, fine but, if, i, live, in, pittsburgh, where, it's notoriously, difficult, to, predict, the weather you, need, much, more, sophistication and, somebody, else, decides, i, want, to, use this, algorithm, to, predict, the, weather

17:06

Speaker A

the, algorithm, is, just, a, series, of, steps the, fact, that, it, happens, to, predict, the weather, is, sort, of magical, it's, what, makes, one, algorithm better, than, the, other, if, you, decide, i want, to, predict, who's, going, to, win, the

17:19

Speaker A

super, bowl you, need, an, algorithm, you're, going, to put, in, all, these, steps and, at, the, end, of, the, day it's, going, to, generate, an, answer, if, the algorithm, is good it'll, tend, to, predict, the, super, bowl winner, if, the, algorithm, is, bad, it'll

17:37

Speaker A

predict randomly, but, they're, too, surprising the, two, elements, of, this, one, of, them, is uh, are, you, doing, the, right, calculations with, the, available, data, another, one, is do, you, have, all, the, data, you, need, in order, to, predict

17:51

Speaker A

with, accuracy, so do, you, know, at, any, given, time, if, you have, all, the, proper, information, you're just, not, smart, enough, to, stitch, it together, to, make, the, prediction you, always, know, that, you, don't, have, all of, the, information, okay, so, if, you, go

18:05

Speaker A

back, to, my, example, that's, that's, very humble yes you you, don't, know, that, there's, moisture, on the, floor you'd, love, to, know, about, those, moisture on, the, floor, you'd, love, to, know, where, it is, but, you, don't, know, that

18:18

Speaker A

because, depending, upon, where, it, is, on the, court, one, team, is, going, to, be significantly, more, likely, to, get, hurt than, the, other, i, would, love, to, know, that i, would, love, to, know, that, so, and was, out, partying, last, night, and, didn't

18:29

Speaker A

tell, the, coach i'm, not, going, to, know, that, so, there's always, a, ton, of, information, that, is inaccessible and, the, question, is, how, good, a, job, can you, do, with, the, information that, you, do, have and, as, ai, has, gotten, more, sophisticated

18:46

Speaker A

it, has, become, the, algorithms, that, the, ai scientists, produce, have, become, more capable, at drawing, effective, conclusions, from, the data, to, which, they, had, access but, they're, still, just, doing, a, bunch, of specific, steps they, have, no, idea, what's, actually, going

19:06

Speaker A

on they're, just add register, 5, to, memory, location, 37, and, put the, result, in, memory, location, 84., don't forget, to, carry, the, two, you, got, to, carry the, two an, astronomical, number, of, steps, like this, that, they're, executing, sequentially

19:26

Speaker A

and, at, the, end, of, the, day, one, of, the steps, says report, the, answer, so, they, report, the answer, and, then, the, next, step, probably says, wait, until, something, happens, and you're, asked, another, question, but they're, just running

19:40

Speaker A

steps, now, one, of, the, interesting questions, is, whether, we're, actually doing, the, same, can, you, take, the, view that, our, brains are, actually, just, neurons, firing, and, the neurons, don't, know, what's, going, on, so it's, very, curious, you, know

19:55

Speaker A

i'm, distinguishing, what, you, just, said for, an, algorithm, duly, answering, gary's question, from, what, i, think, of, at, least in, my, romanticized, view, of, ai, where, the ai, writes, his, own, damn, algorithm, and don't, even, need, you uh-oh, talking, about, sentience, now

20:12

Speaker A

this, is, when, they, take, over so, a, division, of, google called, deepmind has, just, produced code, that, will, write, code and on, the, internet, there, are, these programming, competitions, where, people, go and they, they, write, some, code, to, solve, a

20:33

Speaker A

problem, that's, described, in, english, and these, guys, at, deepmind, have, written, the program, that, actually, reads, the, english description, and, produces, code and, it's, about, average in, terms, of, how, good, it, is, for, the people, entering, these, programming

20:46

Speaker A

competitions, it's, about, average i, don't, again, it, doesn't, know, what, it's doing, right does, that, matter, well, then, it's, not intelligent, it's, just, a, fast, human, brain doing, calculations let's, go, back, to, warren, buffett's, money if, we're, not, getting, our, hands, on

21:03

Speaker A

warrant, this, is, all, about, the, dough all, right, if, we, don't, get, our, hands, on warren's, money, what, if, we, take, a, trip, to vegas, with, our, nicely, polished, algorithm are, we, going, to, fare, any, better, rather than, try, and, predict, the, 63, coin, tosses

21:20

Speaker A

why, don't, we, just, go, in, there, and, have, a little, bit, of, a, smart, move on, that, part, of, the, world, um, because they'll, break, your, knees you, know, what, chap here's, my, thought, if, i my, algorithm, right, i've, invented, my

21:35

Speaker A

algorithm, in, the, garage, and, i'm, really proud, of, it, and, i'm, gonna, take, it, to vegas, and, i'm, gonna, be, really, clever do, you, think, the, guys, in, vegas, don't have, their, own, garages, and, their, own algorithms and, so, here, we, go, matt, if, i, started, to

21:49

Speaker A

use, an, algorithm to, win against, the, bookies will, they, do, they, have, their, own sentinels, their, own, ai, sentinels, waiting for, guys, like, me, to, turn, up they, certainly if chuck, is, sort, of, right, if, you, start winning, money, regularly, and, in, large

22:11

Speaker A

quantities yes, they, will, notice they, absolutely, will, notice and, they, will be, very, concerned i'm, not, saying, they'll, break, anybody's knees, or, they, won't, but, they, certainly will, notice, i'm, going, to, chuck, on, this one, they're, going, to, break, your, house

22:31

Speaker A

yeah, yeah, i'm, i'm, pretty, sure casinos, right, not, not, even, right, now because, now, they're, using, auto, shufflers to, uh, make, it, almost, impossible, for, you to, count, cards, because, they, shuffle after, every, hand, uh, with, with, eight

22:45

Speaker A

decks, in, the, shoe, but, before, that even, card, counters they, knew, you, were, counting, cards because, the, eye, in, the, sky, was, like, that guy, right, there, keeps, winning, all, right now, let's, go, and, focus, on, him, even

23:01

Speaker A

tighter, and, uh, let's, give, him, more scrutiny, and, so, you, would, have, to, be kind, of, a, a, manipulative, genius, to, win enough, and, then, lose, enough, and, then, win enough, and, then, over, a, period, of, time you, walk, out, with, the, money, and, and, who

23:17

Speaker A

can, really, do, that so, there's, a, distinction, here, that, i think, is, incredibly, important, that we're, not, making and, one, is, and, it's, the, difference between beating, blackjack where, you, are, taking, money, from, the house and, going, in, and, playing, poker, where, the

23:36

Speaker A

house, is, just, taking, they're, raking, you know, they're, taking, a, small, rake, off every, hand and, if, you, win, money, you're, winning, it not, from, the, house, but, from, the, other players, opm, other, people other, people's, money, and, sports, is, in

23:49

Speaker A

this, weird, limbo, because let's, say, that, for, some, reason everybody, and, i, literally, mean, everybody wants, to, bet, on, the, bengals, in, the, super bowl the, odds, are, going, to, change, because, the house, doesn't, want, to they, want, to, just, they, want, to, make

24:05

Speaker A

their, rake, they, don't, want, to, be, taking a, strong, position, on, who's, going, to, win the, super, bowl, so, if, you, at, some, level to, win, in, sports, betting you, don't, have, to, be, so, much, smarter, in the, house, you, have, to, be, smarter, than

24:17

Speaker A

the, other, people, who, are, betting, on sports, betting, they're, never, going, to find, out, you're, winning, they're, not going, to, come, and, break, your, knees so, in, sports, there, is, an, element, of, both vegas, does, set, the, line

24:29

Speaker A

and, if, they, get, the, line, wrong, and, you come, running, in, and, you're, constantly beating, them, because, they, set, the, line in, their, make, a, mistake, they'll, notice but, at, some, but, they're, also, setting, the line, based, on, everybody, else's, bet, and

24:41

Speaker A

at, some, point, you're, betting, against the, other, players, as, well, and, it, becomes a, little, safer okay in, in, march, madness, and, in, you, know football, as, well, but, any, of these, sports betting you, know, the, the, common, ones, that, you

24:53

Speaker A

find, in, the, office, place uh, it, is, a, redistribution, of, wealth right uh, right, i, bet, and, i, lose, but, that, goes to, chuck, right, and, chuck, and, i, bet, and we, both, lose, and, it, goes, to, gary, so

25:06

Speaker A

so, i, guess, there's, there's, no bad, will there, because, everyone, is, participating in, this, with, this, understanding, but, if, i learned, that, you, used, ai, and, the, rest, of us, are, just, sort, of, reading, the, paper yeah, we're, going, to, break, your, knees

25:20

Speaker A

right, so, matt what parameters, are, people, putting, in, other than, hunches to, beat, their, opponent, in, bracketology well, fundamentally, what, you, put, in, is all, of, the, play, records, from, all, of, the previous, games, wow, and, that's, basically

25:38

Speaker A

all, the, information, that's, available, and maybe, you, can, put, in, that, somebody, got hurt but, mostly, it's, just, all, of, them, play records, for, all, the, previous, games, so then, you, actually, can, find, out if, these, two, people, are, on, the, floor

25:51

Speaker A

together surprising, things, happen, well, then, you know, that, going, forward, you, can, find, out this, guy he, hasn't, gotten, any, rest, the, last, two weeks, and, historically, if, he, doesn't, get any, rest, he, plays, terribly, so, now, you

26:04

Speaker A

know, that, so, you're, looking, mostly, for patterns, in, data, that, you, have, that, you sort, of, the, community, has, agreed, is, sort of, the, starting, point, and, that, would include, what, teams, not, just, simply whether, they, won, but, what, teams, they

26:18

Speaker A

beat right, that's, got, to, be, in, there, too, no it, includes, it, includes, everything, it includes, that, this, guy made, a, three-point, shot at two, minutes, and, 22, seconds, left, in, the second, quarter it, includes, absolutely, everything, and

26:34

Speaker A

these, are, the, other, players, second, half and, these, are, the, other, players, who, are on, the, floor, at, the, time and it, includes, every, you, know, this, guy committed, a, foul, at, this, point, this, is who, else, was, on, the, court, this, guy, was

26:48

Speaker A

absolutely, everything, and, this, date, is available, so, you, can, actually, get, every everything, about every, play and, so, forth, and, so, on, now one, of, the, things, that, typically, people work, with, play, records, these, days there's, also, video

27:06

Speaker A

so, you, can, potentially, look, at, the, video and, see, where, does, somebody, choose, from and, and, but, man, there's, a, difference between, information, out, there, there's, a difference, there's, a, difference, between data and, knowledge so, what, you, do, with, that, information

27:20

Speaker A

might, be, different, from, what, someone else, does i, guess, that's, the, magic, of, who, whose algorithm, is, who's, right that's, the, magic, so, the, algorithms process, the, data, to, make, predictions roughly, speaking, we're, all, working, with the, same, data

27:37

Speaker A

but, you'll, have, some, people, with, better algorithms, and, some, people, with, worse algorithms, if, people, are, using, vastly different, data, that's, when, people, start getting, upset because, they, feel, like, they've, been cheated, because, i, didn't, know, so, and, so

27:50

Speaker A

twisted, his, ankle, and, you, did, that's, not fair but, when, you, work, with, the, same, data, it somehow, sort, of, seems, fair, and, now, it's really, just, a, matter, of who's, smart, enough, to, create, the, best algorithms, who, has, the, computational

28:03

Speaker A

horsepower, to, run, those, algorithms because, they're, becoming, very computationally, intensive and, thereby, making, better, predictions, so the, raw, material, for, this, neil, to, my mind is, the, quality, of, data because, if, you've, got, access, to, some, of the, random, things, that, can, happen, like

28:21

Speaker A

for, instance, someone, was, partying, the night, before, when, they, shouldn't, have been, someone, is, carrying, an, injury, that you, don't, know, about, that, hasn't, come out, into, the, public, domain, that, quality of, knowledge is, what, will enable, an, algorithm, and, a, builder, to, to

28:37

Speaker A

make, a, better, algorithm, am, i, right, there matt i, think, there, are two, ways, you, can, win one, is, you, can, have, better, data that, sort, of, feels, a, little, unethical the, other, is, to, have, a, better, algorithm

28:53

Speaker A

that, does, a, better, job, of, processing, the shared, data a, better, algorithm, means, you're, now maybe i'm, a, scientist, so, maybe, i, just, like, it when, smart, people, win, a, better, algorithm means, you, were, smarter, than, the, guy, with

29:07

Speaker A

the, worse, algorithm okay, better, data, means you, know, you, followed, the, basketball players, the, night, before, to, see, what they, were, actually, up, to, and, that somehow, just, doesn't seem, right, it, seems, like, that's, an unlevel, playing, field, and, this

29:22

Speaker A

you, know, but i, like, it, when, better, algorithms, work because, i, like, making, good, algorithms we're, going, to, take, a, quick, break, when we, come, back, to, our, third, and, final segment, we'll, finish, up, on, that, topic but, then, we're, going, to, you, know, chew

29:34

Speaker A

the, fat and, just, get, into, some, of, the, more philosophical, dimensions, of, this, topic applying, ai, to, predicting, sports brackets, on, star, talk, sports, edition we're, back, star, talk, sports, edition, we have, a, friend, of, star, talk, ai, expert

29:52

Speaker A

mathematics all, around, math, guy matt, ginsberg, matt, great, to, have, you back, on, star, talk, how, do, we, find, out would, you, hang, out, anywhere, on, on, social media i, have, a, website matt, ginsberg.com and, that, is, practically, it, i, have, a

30:08

Speaker A

twitter, account, that, i, never, use, i, don't belong, to, facebook i'm, really, as, quiet, as, possible, well that, means, you, probably, read, and, do things, with, your, spare, time i, do transitioning, out, of, the, last, segment let, me, just, ask, matt, before, we, get, into

30:33

Speaker A

our, more, philosophical, questions isn't, there, this force, operating, on, who, wins, that, doesn't show, up, in, the, data, such, as how, badly, do, they, want, to, win i, wanted, it, more exactly, and, for, equal, talent, that, could elevate, someone's, performance, why, is, it

30:55

Speaker A

that you, can, do, this, best, in, track, and, field that in, big, events, many, people, have, their personal, best whether, or not, it's, a, world, record, they just, perform, better, in, that, moment, under those, circumstances, than, they, ever, have

31:08

Speaker A

in, their, entire, life and, so, something, was, going, on, within them, that, didn't, show, up, in, their previous, data, so, the, last, nba, finals, uh the, milwaukee, bucks, giannis whatever, his, name, is, because, i, can't, say it, but

31:24

Speaker A

uh, it's, widely, held, that, he just, rose, above, his, game, and, above, his team's, performance, to, carry, them, almost single-handedly, to, a, championship and, you, look, at, bob, beeman's, world record, setting long, jump, in, the, 1968, mexico, olympics

31:44

Speaker A

beating, the, previous, record, by, over, a foot and, and, no, one, came, near, that, for, for decades so, so i, don't, see, how, that, shows, up, in, your, ai algorithms, it's, it, is, totally, in, the data, it, is, totally, in, the, data, oh, this

32:01

Speaker A

is, fascinating throw, down, throw, down, here, you, go, go, on so, if, you you, can, look, at the, previous, performance, of, athletes, as a, function, of whether, or, not, it, was, a, clutch, situation and, if, there, are, athletes, who, reliably

32:21

Speaker A

perform, better, when, the, pressure, is, on that's, totally, in, the, data, and, if, there are, athletes, who, reliably, perform, worse when, the, pressure's, on, because, they choke that's, in, the, data, and, if, there, are people, who, just, perform, the, same

32:34

Speaker A

independent, pressure that's, in, the, data so, it's, it, now, it, is, the, case that, being, in, the, olympics, is, special being, in, the, super, bowl, is, special, but you, can, also, look, at, for, somebody for, a, generic, player, who, performs, five

32:51

Speaker A

percent, better, in, a, clutch, situation how, does, he, perform, how, much, does, he perform, better, in, his, first, super, bowl that's, in, the, data not, this, guy, who's, about, to, play, in, his first, super, bowl, but, i, know, how, this, guy

33:04

Speaker A

responds, to, pressure, and, i, have, data telling, me, how, much, pressure, the, super bowl, really, is, put, it, all, together, and all, now, this, guy's, likely, to, play, in, the super, bowl, wow, some, people, are, gonna have, good, days, some, people, are, gonna

33:14

Speaker A

have, bad, days, but but, all, the, stuff, you've, been, talking about it's, all, in, the, data, so, how, about, the fact, that, some, coaches, give better, pep, talks, at, halftime, than, others do right, all, right, guys, listen to, me, 212, to, nothing

33:33

Speaker A

but, i'm, telling, you, right, now, you, gotta reach, inside, yourself okay so, what's, not, in, the, data are, there's, a, there's, a, wet, spot, on, the floor okay or this, bit, of, astroturf, was, replaced, badly that's, not, in, the, data

34:03

Speaker A

all, right, chuck, you, had, an, interesting philosophical, question, back, a, couple, of segments, ago, what, was, that i'm, saying, like, if, you if, if, you, look, at, the, question, of whether, or, not, a algorithm, or, computer is, doing, pretty, much, the, same, thing, we

34:19

Speaker A

do, i'm, trying, to, figure, out, how, it's, not when if, you, look, at, somatic, memory, episodic memory, aren't, we, just, taking, the collection, of, all, of, our knowledge, making, associations, coming, to a, conclusion, then, making, a, decision that's, exactly, what, matt's, been, saying

34:41

Speaker A

so, why, so, matt, why, are, you, better, at this, is, it, because, you, can, handle, more variables, but, so, are, we, right, i, can think, of, you, know, what, is, tom, brady thinking, when, he, he's, hiked, the, ball

34:52

Speaker A

he's, got, the, whole, field, in, his, head, the history, and, the he's, got, it, all and, no, one, is, talent, there's, no, adding machine, that, you, can, point, to, it's almost, at, an, intuitive, level, going, on, in his, head, so, in, the, same, way, he's, he's

35:07

Speaker A

looking, for, patterns, he, knows, how, to read, defenses, he's, seeing, that, certain guys, going, in, motion, or, being, out, of position, means, certainly, left, or, moving right right, why, is, that, any, different, matt, and why, should, we, trust, you, and, not, chuck's

35:21

Speaker A

intuition i, don't, that's, not, the i, don't, think, it, is, different and, i, think, you, know, one, of, the things you, said, neil, earlier, on, you, said, well then why, is, it, intelligence and, i, don't, know, what, i, don't

35:38

Speaker A

i, don't, know, that, intelligence, has, a meaning other, than, sort, of, a performance, if, you, can, do, smart, stuff you're, intelligent, and, i, don't, care, how you, got, there if, you, can always, throw, to, the, right, place, you're, a

35:53

Speaker A

good, quarterback, and, i, don't, care, what the, processing, that, happened, inside, your brain, to, make, it, happen is now, there, are, some, people, i, think probably, the, best, known, is, roger, penrose who, actually, believe, that, there, is, stuff

36:08

Speaker A

going, on, inside, of, us that, is, not, computable that, it, depends, on, quantum, mechanics, and it, depends, on, this, magical, relationship between, our, minds, and, the, world, of mathematics, that, a, machine, can, never duplicate, but, just, a, quick, it, could, be

36:22

Speaker A

right, a, quick, bio, and, roger, penrose, is, a physicist, at, the, university, of, oxford who in, fact, just, got, the, nobel, prize, a couple, of, years, ago, for, his, early, work showing, that, einstein's, general, theory of, relativity, has, to, give, you, black

36:36

Speaker A

holes, like, is, it, it's, a, necessary prediction, from, the, foundational, physics that's, there, and, he's, long, respected, in physics, and, in, astrophysics, then, he stepped, into, the, world, of, consciousness and, into, a, world, where, we, really, don't have, good, explanations, so, you, wanna

36:54

Speaker A

those, are, the, kind, of, places, that attract, smart, people, and, he, was, just imagining, that, you, know, we, can, think, of the, brain, as, electrochemical, but, let's go, a, step, deeper, is, it, also, quantum mechanical, and, if, that's, the, case, then

37:06

Speaker A

you're, then, all, bets, are, off, because, you you're, not, predict, the, quantum, physics creates, a, an, unpredictable, randomness, to it, that, um, may, be, the, source, of, all, of our, wisdom is, that, a, fair, way, to, think, about, his

37:20

Speaker A

contributions, to, consciousness, matt it, is, i, mean, he, was, my, thesis, advisor and, he, and, i, have, argued, about, this, and you, have, described, his, position, fairly and, what's, interesting, is, i, mean, when, we argued, about, this it, didn't, take, long, for, us, to, realize

37:37

Speaker A

that, we, had, this, fundamental disagreement, is, what's, going, on, in, your head quantum, mechanics, or, is, it, sort, of classical, mechanics, that, a, machine, can duplicate and, we, realized, we, were, on, different sides, we, realized, neither, would, convince

37:50

Speaker A

the, other, i, believe, chuck, appears, to believe, that, what's, going, on, in, your head, you, could, capture, as, a, process if, somebody, eventually, makes, a, real, ai an, actually, intelligent, artifact then, roger, will, be, wrong if we, keep, trying, and, never, get, there, maybe

38:09

Speaker A

he's, going, to, turn, out, to, be, right, but right, now, nobody, nobody, knows matt, mentioned, classical, physics, so, what he, means, there, is, if, everything, that's happening, in, your, head, is, classical then, it, means, you, can, point, to, all

38:22

Speaker A

causes, of, all, effects, and, trace, it, back and, how, they, interact, with, each, other, if there's, a, quantum, domain, going, on, then the, cause, and, effect, gets, disrupted, and then, you, can't, then, classically, describe it, but, so, matt, then, what, about, i, mean

38:37

Speaker A

you're, at, google, what, about, the, future i'm, pie, in, the, sky, here, what, about quantum, computing will, that, be, able, to, mimic what, might, be, quantum, influence, in, our ability, to, predict, the, future so, i, don't, know and, the, right, person, to, ask, is, roger

38:53

Speaker A

because i, actually, think, we, don't, need, quantum computing, because, i, think, we, are classical artifacts, what's, going, on, our, head, is classical i, don't, know, where he, is, on, that, question, um, i, know, you know, google does, quantum, computing

39:09

Speaker A

everybody's, doing, quantum, computing these, days, it's, exciting, it, can, break encryption um maybe, they're, afraid, to, put, you, on, that topic, because, then, you, might, take, over the, work yeah at, least, take, over, google they're, watching, the, chromebook, assembly

39:26

Speaker A

line, just, just, to, keep, you, out, of trouble, i, know, i, know, they, um the, chromebook, repair, line um sorry, to, cut, across, you, if, it's, data driven, this, whole, thing, about, and, if, we don't, know, it, we, don't, know, it

39:48

Speaker A

do, we, then, not, point, ai, in, the, opposite direction, and, say, go, and, find, what, we don't, know bring, it, back, and, then, we'll, build, even better is, am, i, am, i, seeing, this, in, the, wrong way, completely

40:01

Speaker A

i, think that's, a, great, question, and, by, the, way let, me, interject, here, what, we, do, when, we send, robots, to, other, planets there, often, have, a, serendipity, mode where, it, looks, around, and, if, there's something, it, doesn't, recognize, that

40:16

Speaker A

we've, programmed, it, into, it then, that, is targeted, for, extra, curiosity and, so, but, you, have, to, be, able, to, notice something, that, you, don't recognize that's, an, important, step, and, not, and, not otherwise, just, look, right, past, it, so

40:32

Speaker A

just, pick, up, matt, i, just, want, to, put that, out, there the, consensus, these, days is, that there, is, a, huge, amount, of, scope, for improving, our, ability, to, draw conclusions, from, the, data, we, have so, when, you, look, at, all, the, stuff, about

40:50

Speaker A

big, brother, and, tracking, terrorists, with data, it's, and, amazon, predicting, which book, you're, going, to, want, to, buy, next, if you, read, books netflix, predicting, which, tv, show, you're going, to, want, to, watch, next it's, amazing, how, well, these, systems

41:06

Speaker A

perform it, was, a, huge, surprise all, they're, doing, is, they're, doing, a better, job, of, exploiting, the, data, we already, have, and, the, consensus, is we, should, be, focusing, on improving, our, ability, to, use, the, data we've, got

41:22

Speaker A

rather, than, looking, for, more, data when, we're, not, even, using, our, existing data, as, well, as, we, could, by, and, large acquiring, more, data, is, expensive, it's hard, it's intrusive and, and, i, think, it's, the, consensus, of the, ai, community, that, there's, still, so

41:39

Speaker A

much, scope, for, doing, more, with, what, we know, with, what, we, have that, that's, where, we, should, be, focusing interesting, that's, very, interesting and, and, and, so, when, you, say, it's, is, it just, the, amount, of um work, that, it, takes, to, get, more, data

41:57

Speaker A

is, that, why, it, just, gets, more, invasive it's, you, know it's, like it's, like, the, way, netflix, always, keeps trying, to, get, me, to, say, please, rate, this so, that, we, can, better, understand, how, you and, i'm, like, screw, you

42:14

Speaker A

i'm, not, giving, you, any, more, information about, me, than, you, already, have, right sell, something, to, you, better, yes chuck, do, you, have, do, you, have an, alexa i, do, i, have, an, alexa, i, have, a, google home, and, i, have, um, an, amazon, or, whatever

42:29

Speaker A

the, other, thing, is, i, don't, use, any, of them, because, the, first, time, i, use, it, so you, think, so, you, think, oh, no, they're unplugged so, you're, fake well, played, sir, well, played they're, tapping, into, the, electromagnetic

42:47

Speaker A

energies, of, the, universe yeah, but, the, first, time, i, used, one, it scared, the, hell, out, of, me, because it, it, immediately, started, to, as, they, say learn and, that, was, frightening, to, me so, that, is, amazon, or, google, or, whomever

43:06

Speaker A

do, you, use, your, cell, phone, chuck unfortunately, yes, and, i, see, it, every time, i, use, it, i, see, the, results, i, see, it come, up, with, the, ads, that, i, never, looked for and, then, all, of, a, sudden, i'm, like, i

43:20

Speaker A

should, buy, diapers, i, don't, even, have, a baby but, then, a chuck, you, should, move, your, bowels, about now, you, have, done, so, in, the, last, three days, at, this, time and, by, the, way, you, know, uh, here's, a

43:35

Speaker A

great, product, to, help, you, do, that but, go, ahead, i'm, sorry, this, is, the length, that, that, these, companies, and, i would, now, work, for, one will, go, to, get, more, data, so, matt, from march, madness, are, you, are, you, entering

43:47

Speaker A

that, contest, because, somebody's, going, to have, out, of, 20 quintillion possibilities somebody, will, come, in, ahead, of, everybody else because, that's, how, it, works, and, but they're, not, going to, get, all, 20, 20 continues to, be, someone, who, does, better, than

44:06

Speaker A

everybody, else, if, anyone, say, well, how did, they, do, it, and, then, they, you, get, a peek, at, their, ai, will, everyone, focus around, them, or, we're, gonna, say, it's, it's random, dumb, luck hard, to, know, right, if, they, win, by, a, lot

44:20

Speaker A

if, they're, like, way, better, than whoever's, second, people, are, going, to, pay attention if, they, just, edge, out, the, guy, who's right, behind, them, then, it, was, going, to have, enough, of, a, luck, element, that there's, probably, not, something, to, learn

44:32

Speaker A

but, i, think, it's, it, is it, is, the, case, that, if, somebody, fails, to get, warren's, money, because, they, only predict, 62, of, the, 63, games, correctly that, person, will, get, a lot, of, attention right, if, it's, marginal, then, it's, just

44:47

Speaker A

like, emily, down, in, shipping, who, pick, who wins, the, pool, because, she, was, like, i like, the, teams, with, the, bright, colors and, then, it's, like and, she, beat, everybody, you're, getting, an email, from, emily [Laughter] so, i, think, we, this, came, up, in, a, previous

45:04

Speaker A

episode, matt, with, you, as, a, guest where if if, everything, you, say and, if, you're, as, good, as, you, say, you, are why, isn't, this, podcast, filming, you, at your, villa you, know, what, matt's, going, to, say, right

45:23

Speaker A

now, because, this, is, an, actual screensaver, that, i, have why, aren't, we, on, your, yacht why, why, why, are, we, in, some corner why, what, what i, have, made, my, life, about, solving, hard problems, and, not, about, making, money

45:45

Speaker A

and, that, is, a, choice, that i, regret, absolutely, no, immensely that's, a, choice absolutely, okay, it's, a, choice, that, is, a choice, that, makes, my, wife, extremely upset, with, me i, have, i, have, had, a, better, life, and, i

46:03

Speaker A

have, healthier, children, because, of, it yeah, that's, probably, true, unfortunately definitely, yeah that's, pretty, special, this, stuff, yeah you, know, what, though, i, will, say, uh, as, a as, a, point, of, admiration, matt, that um that, and, that, is, um, philosophically, a

46:22

Speaker A

much, higher, position, to, take, no, blair it's, a, nobler, position, oh, yeah thank, you, but, mostly, it's, fun, it's, just fun, you, like, to, solve, the, unsolvable, you know, the, hard, problems, are, we, pointing enough, ai, at, the, problems, this, planet

46:39

Speaker A

has, right, now why, are we, finding, brackets, to basketball solutions, that's, okay, let's, go, make, some money, or, let's, go, solve, some, really, big gigantic, problems are, we, doing, enough, the, first, the, first project, i, worked, on, at, x

46:58

Speaker A

was to, use, ai, to, help, decarbonize, the electricity, grid, okay, generate electricity, distribute, electricity without, burning, fossil, fuels, yeah that's, as, important, as, it, gets, that's really, important and you, failed, that, and, so, then, you, went, to basketball, okay

47:18

Speaker A

um i, think, that i, think, that, there, is a, significant amount, of, work, spent, on, these, on, these incredibly, important, problems, okay, it, is also, the, case, that if, you, look, at, getting, a, computer, to play, chess that, doesn't, save, anybody's, life

47:41

Speaker A

but the, work, on, computer, chess, moved, ai forward, an, enormous, amount and, allowed, people, to, take, what, they learned, from, chess and, apply, it, to, problems, that, actually matter, so, a, lot, of, the, a, lot, of, the magic, i, think, is, probably, the, right, word

47:58

Speaker A

of, being, a, scientist, is, about, finding problems that, are, hard, but, still, just, barely tractable and, have, the, property, that, when, you solve, them, you, will, learn, something, that you, can, take, elsewhere to, make, the, world, a, better, place, yeah, i

48:15

Speaker A

mean, you, look, at, the, medical, industry which, is, now, where, chuck, that, was he, just, he, just, composed, a, beautiful ending, sentence, and, now, you, got, to, keep talking yeah okay, all, right i, was, just, agreeing, with, matt, but, that's

48:28

Speaker A

okay, this, sentence, was, like, you, could belongs, on, a, statue, somewhere okay, just, go, on, no, no, it's, just, not just i, was, just, agreeing, with, him, like, you know, the, fact, that, it, is, it's, becoming increasingly, expansive, and, it's, making

48:44

Speaker A

life, better, for, so, many, people, and many, other, branches, beyond, and, this, is this, is, what, mathematicians, have, known forever that, they're they're, an, engine, of, so, much, uh, advance in, culture, and, civilization, in, ways, that people, don't, really, appreciate, because

49:00

Speaker A

the, advance, is, somebody, else's, invention based, on, what, they, did, and, the, other person, gets, the, credit, not, matt, but, we love, you, matt we, got, you, we, got, your, message we're, gonna, start, a, gofundme, mat so, something, you, said, about, ai, playing

49:16

Speaker A

chess, right, and that, that, then, inspired, people, to, think in, a, certain, way is, this, the, legacy, that, we're, finding, ai is, leaving, us, it's, it's, making, us, think better think, differently, and, improv, is, it, is actually, teaching, us

49:34

Speaker A

there's, so, many, things, i, could, say, i mean, one, of, the, things, that, people, have often, joked, about, in, ai, is, that, as, soon as, anything, actually, becomes, successful it, leaves, ai, and, it, becomes, part, of autonomous, driving, or, some, other

49:45

Speaker A

discipline, right, ai, is, teaching, us, about ourselves, certainly, um we, are, we, are, learning, about, what, we, can do, and, what, we, can't, do my, belief, has, always, been, that, computers solve, problems, differently, than, we, do and, they, always, will

50:03

Speaker A

and, that's, going, to, mean, that, we, can solve, more, problems, with, machines, at, our side than, we, could, solve, by, ourselves, or, they could, solve, by, ourselves, by, themselves and, it's, tremendously positive, it's, tremendously, optimistic they're, tools, they, are, tools

50:20

Speaker A

and, we, will, be, able, to, do, more, with, them than, we, could, ever, have, done, without them and, we, should, all, be, ecstatic, about, that it's, not, going, to, be, like, the, terminator right, it's, going, to, be, like

50:31

Speaker A

figuring, out, how, to, get, carbon, out, of the, electricity, grid on, that, note, we, got, to, land, this, plane we, got, to, land, this, plane, oh, i, had, oh, i just, wanted, one, more, thing, to, know it's, not, no, okay

50:45

Speaker A

chuck, go, make, it, fast, really, fast, uh back, to, it's, in, the, data, is, it, possible with, all, the, data, of, every, war, ever fought on, this, planet to, be, able, to, predict, when, we, might, be going, to, war, and, if, that, war, will, lead

51:00

Speaker A

to, our, ultimate, destruction probably okay, here, we, go and, with, that thank, you, matt, for, that succinct, reply, to, chuck's doomsday, question, we, got, to, call, it quits, there, uh, matt, always, good, to, have you, um, chuck, gary

51:20

Speaker A

pleasure, making this, has, been, star, talk, sports, edition uh, what, do, we, call, this, we, call, it bracketology, if, there's, even, such, a, word is, now there, it, is, now, you've, got, it, i've, been neil, degrasse, tyson, you're, a, personal

51:34

Speaker A

astrophysicist, keep, looking, up [Music]

Topics: March Madness AI algorithms sports betting game theory NCAA basketball bracket prediction Neil deGrasse Tyson Matt Ginsberg StarTalk

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