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The Father of AI Was a Black Scientist 🤯 · Earn Your Leisure

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  Speaker 1: This episode is brought to you by P and C Bank.
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  Speaker 2: This is a very important segment. So can we bring
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  Speaker 2: our guests up?
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  Speaker 3: Hey, hey, how are you now?
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  Speaker 4: We are good?
• 0:59
  Speaker 5: How you feel it?
• 1:01
  Speaker 6: I'm feeling great. I'm just a pleasure to be here
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  Speaker 6: and so much fun to listen to you guys. This
• 1:07
  Speaker 6: is great. Not only is it good stuff, it's interesting
• 1:11
  Speaker 6: and fun. I love the way you present it and
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  Speaker 6: I'm like, yes, okay, I'm right, I'm taking notes right here,
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  Speaker 6: thank you.
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  Speaker 7: Thank you.
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  Speaker 2: So this is finally important. So okay, Lisa Blackwell. So,
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  Speaker 2: all right, some backstory. If you following video, you know
• 1:26
  Speaker 2: that they every year they come out with a new
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  Speaker 2: chip and they named the chip after a historical figure,
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  Speaker 2: like one of the top scientists in the world, somebody
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  Speaker 2: that has contributed to artificial intelligence, somebody that you know,
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  Speaker 2: like a pioneer in the space. Last year chip was
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  Speaker 2: named Blackwell. So Blackwell before Ruben is this year. Ruben
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  Speaker 2: hasn't come out yet, So currently Blackwell is the most
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  Speaker 2: advanced chip EVE ever created. Now, the interesting thing is
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  Speaker 2: that Blackwell was named after David Blackwell. David Blackwell is
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  Speaker 2: Lisa's grandfather. Correct, this is a very interesting story, and
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  Speaker 2: we're gonna play a vision. We're gonna play a visual
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  Speaker 2: to talk about it in that week. But before we
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  Speaker 2: played a visual, can you just queue up? Can you
• 2:17
  Speaker 2: cute this up for us?
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  Speaker 6: Sure? So you're about to see ten minutes of what
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  Speaker 6: is a concept reel for the documentary that we're creating
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  Speaker 6: about my grandfather's story. And it really has a little
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  Speaker 6: bit of the sort of lynch pin that everything turned
• 2:38
  Speaker 6: around on, like when I start digging into the story
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  Speaker 6: and what I discovered and you guys are getting ready
• 2:43
  Speaker 6: to see sort of what that looks like. And again
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  Speaker 6: this is the concept reel for the documentary.
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  Speaker 2: Let's play it? Shall We?
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  Speaker 8: Thanks?
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  Speaker 5: Do it?
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  Speaker 3: Okay?
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  Speaker 4: National Medal of Science too. David Blackwell, University of California, Berkeley.
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  Speaker 5: I would like to introduce you to a very very
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  Speaker 5: big GPU named after David Blackwell.
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  Speaker 4: For fundamental contributions to probability theory, mathematical statistics, information theory,
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  Speaker 4: mathematical logic, and Blackwell games.
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  Speaker 8: David Blackwell was it a great amongst greats. He was
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  Speaker 8: the great, great, great mathematician among great mathematicians.
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  Speaker 9: Blackwell was a pioneer who was ahead of its time.
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  Speaker 7: I thought, I knew my grandfather Eggs had done. My
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  Speaker 7: team is at dusk in a five percent dividend man
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  Speaker 7: all the way. Years later, Nvidia named their platform Blackwell.
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  Speaker 7: That's when I started digging and discovered my grandfather. Professor Blackwell,
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  Speaker 7: architect of the mathematics behind artificial intelligence.
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  Speaker 9: A lot of his ideas really cause people to rethink
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  Speaker 9: how do we interpret data?
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  Speaker 8: There are many many standard tools that people use all
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  Speaker 8: the time that are named after David. You know Blackwell
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  Speaker 8: spaces and the raw Blackwell theorem.
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  Speaker 9: Blackwell nowadays is known for what's called the Blackwell rawl theorem,
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  Speaker 9: sort of like saying, if something happens frequently enough, you
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  Speaker 9: should be able to kind of predict what's going to
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  Speaker 9: happen next. However, there might be some bias in some
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  Speaker 9: of that data. That's essentially what the Blackwell Rowl theorem
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  Speaker 9: tells you is that there's a way you can kind
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  Speaker 9: of estimate what should happen, but then minimize the bias
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  Speaker 9: that you would have there in the data. And this
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  Speaker 9: is an amazing approach to doing statistics. If black men
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  Speaker 9: were alive today, he would certainly be the one to
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  Speaker 9: raise up his hand and say, you know, look, there's
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  Speaker 9: bias in AI, there's bias in the training data that
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  Speaker 9: we're using, and we really need to think about minimizing
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  Speaker 9: these as more and more people use these models.
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  Speaker 10: I was very clear that I was going to be
• 5:25
  Speaker 10: a school teacher. My father had a friend who was
• 5:29
  Speaker 10: on the school board, and before I finished high school,
• 5:33
  Speaker 10: he already told my father that if I went to
• 5:36
  Speaker 10: college and got a degree, he would get me a
• 5:39
  Speaker 10: job teaching. And this was in the depression, and it
• 5:42
  Speaker 10: was a great relief to me and everybody else when
• 5:46
  Speaker 10: it was clear what my future was going to be.
• 5:50
  Speaker 10: After I got my bachelor's degree in three years, I
• 5:55
  Speaker 10: decided to spend my fourth year getting a master's degree.
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  Speaker 10: But then at the end of my fourth year I
• 6:01
  Speaker 10: was encouraged to apply for a fellowship to go on
• 6:05
  Speaker 10: for a PhD. And I did, and then of course
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  Speaker 10: my objective changed. There were perhaps twenty five awards, twenty
• 6:15
  Speaker 10: two of them required teaching assistant responsibilities. Three of them
• 6:21
  Speaker 10: were pure fellowships, and everybody applied for both things, and
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  Speaker 10: the lucky three got the fellowships. And one of my
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  Speaker 10: colleagues who also applied, told me that I was going
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  Speaker 10: to get one of the fellowships, and I said, how
• 6:42
  Speaker 10: do you know? And he said, well, they're good enough
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  Speaker 10: to be supported, and they're not going to put you
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  Speaker 10: in front of a classroom.
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  Speaker 9: He was right, they were not going to put you
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  Speaker 9: in front of a classroom because because I'm black.
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  Speaker 8: David, you know the I he he was s he
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  Speaker 8: was a black mathematician. And there are no BA black
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  Speaker 8: mathematicians that w would that it were, but I but
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  Speaker 8: they they, they they are very few. Anyway, what was
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  Speaker 8: it like to be David Blackwell? I never could get
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  Speaker 8: him to talk about that, uh, anything about what his
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  Speaker 8: experiences were in Berkeley. He had the problems of not
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  Speaker 8: being hired in the nineteen fifties because the wife of
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  Speaker 8: the chairman of the Berkeley Math Department said, well, I
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  Speaker 8: wouldn't wanna h see us hire somebody that I couldn't
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  Speaker 8: invite to my home yet Jersey name and realized that
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  Speaker 8: David Blackwell was David Blackwell, and did hire 'em these
• 8:01
  Speaker 8: awful people's dead bodies. But to try to get David
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  Speaker 8: to tell any story of that sort, he just wasn't
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  Speaker 8: a negative person.
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  Speaker 6: My grandfather came to UC Berkeley in nineteen fifty four.
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  Speaker 6: That was the same year that the Brown versus the
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  Speaker 6: Board of Education came down, nineteen fifty four, and my
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  Speaker 6: grandparents are driving across the country with their seven kids
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  Speaker 6: with the Green Book. There was this book that they
• 8:40
  Speaker 6: had to use to get across the country, so they
• 8:44
  Speaker 6: knew where they could sleep, safe places that they could sleep.
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  Speaker 6: Then when he got here, he wasn't offered the customary hospitality,
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  Speaker 6: and so he went and they didn't have housing. They
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  Speaker 6: slept in park for two months well and he would
• 9:02
  Speaker 6: go commute and teach at the school. Seven children.
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  Speaker 11: When we traveled, and we did travel a lot in
• 9:11
  Speaker 11: the car, in the station wagon. When we would travel,
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  Speaker 11: he would have a map and he would give each
• 9:16
  Speaker 11: of us a map, and he would have gasoline estimates,
• 9:20
  Speaker 11: time estimates for how long I was going to take us,
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  Speaker 11: estimates for how long we go to the bathroom, estimates
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  Speaker 11: for what the traffic was going to be. But along
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  Speaker 11: the way he kept us all engaged at our own level.
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  Speaker 12: And it was.
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  Speaker 11: Remarkable to have children ten years apart, one is very young,
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  Speaker 11: the other one is much more mature, and still keep
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  Speaker 11: them all engaged. They somehow felt equal to the challenge.
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  Speaker 11: It was just reflective of his considerate manner of teaching.
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  Speaker 7: Your grandfather was the most delightful, friendly, warmest person.
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  Speaker 4: I just remember him with a smile in his face.
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  Speaker 9: All the years I had heard people talk about David Blackwell,
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  Speaker 9: they never talked about him being angry or bitter. Most importantly,
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  Speaker 9: they never talked about him saying anything negative about anyone else.
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  Speaker 9: And that I think truly is a testament to his character.
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  Speaker 9: That's what I strive to do, is to really say,
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  Speaker 9: maybe things have happened negatively, but let me not try
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  Speaker 9: to dwell on that and let me try to move
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  Speaker 9: forward to say what are positive things that are happening
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  Speaker 9: and what are ways that I can make this world
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  Speaker 9: a better place.
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  Speaker 5: You have arrived at a developer's conference. There will be
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  Speaker 5: a lot of science described algorithms, computer architecture, mathematics.
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  Speaker 12: In March last year, Nvidia unveiled its most ambitious GPU architecture.
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  Speaker 12: We named it Blackwell in honor of doctor Blackwell. Today
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  Speaker 12: we're witnessing the dawn of the AI era, and the
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  Speaker 12: Blackwell architecture is the engine that's powering this new industrial revolution.
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  Speaker 12: We strive each day to honor doctor Blackwell's remarkable legacy
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  Speaker 12: by bringing the promise of AI to industries, developers, and researchers.
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  Speaker 10: Worldwide, specifically through African Americans. I would say, don't consider
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  Speaker 10: your race as a handicap. If you want to go
• 11:42
  Speaker 10: in a direction, go in that direction. In other words,
• 11:47
  Speaker 10: make decisions on the same basis as if you were Chinese, right,
• 11:52
  Speaker 10: or anything else. I don't worry so much about race.
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  Speaker 10: It's going to be a factor. Let other people worry
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  Speaker 10: about it. Don't you worry about it.
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  Speaker 9: David Blackwell was the epitome of excellence. We had a
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  Speaker 9: booth at a math conference, an individual walked by. He
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  Speaker 9: wasn't a black mathematician. He pauses at the table, looks
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  Speaker 9: at the picture of Blackwell and is very confused and
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  Speaker 9: then says, you know, I'm a statistician, but that picture
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  Speaker 9: can't be right. David Blackwell wasn't black. So I asked him, so,
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  Speaker 9: how are you convinced that he wasn't black? And he said, well,
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  Speaker 9: there's this Blackwell Ralph theorem, and it's an amazing theorem.
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  Speaker 9: It just never crossed my mind that Blackwell could be black.
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  Speaker 6: So imagine if David Blackwell didn't have to be hidden
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  Speaker 6: fifty years ago, if he wasn't hidden fifty years ago,
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  Speaker 6: what would stim look like today? What's it going to
• 13:02
  Speaker 6: look like tomorrow? We don't uphold his face and those.
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  Speaker 3: Like him, Yes, Wow, there, you're wow.
• 13:29
  Speaker 1: Amazing is incredible watching it, Talking to you, getting to
• 13:35
  Speaker 1: know you over the past few months has just been incredible.
• 13:39
  Speaker 1: H The chat is going crazy. You know, we don't
• 13:41
  Speaker 1: need a month, so we don't need a day to
• 13:43
  Speaker 1: celebrate our history. We make history every day. And I'm
• 13:46
  Speaker 1: so happy that you've put this peeple together.
• 13:49
  Speaker 2: And just for full context for people like, you know,
• 13:52
  Speaker 2: it's interesting because we talked about AI so much and
• 13:54
  Speaker 2: who really knew that one of the forefathers of artificial
• 13:58
  Speaker 2: intelligence was black and held in such high regard in
• 14:04
  Speaker 2: the world of science that the largest company in the
• 14:07
  Speaker 2: history of the world, which is in Vidia, named their
• 14:12
  Speaker 2: most advanced piece of software ever after a black man.
• 14:18
  Speaker 2: And you know, once again, it just goes back to
• 14:20
  Speaker 2: I think you said this had in video, like if
• 14:22
  Speaker 2: he was well known, would what would that do to
• 14:25
  Speaker 2: stem in our community? Because we aspire to be things
• 14:28
  Speaker 2: that we see success in. So we aspire to be
• 14:31
  Speaker 2: athletes and entertainments because we see success in that. It's
• 14:34
  Speaker 2: not just because we're talented in athletics and entertainment. We are,
• 14:38
  Speaker 2: but we're also talented in math and science. But we
• 14:40
  Speaker 2: don't see we don't. We haven't we haven't been exposed
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  Speaker 2: to that. So that's not something that we aspire to be.
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  Speaker 2: But what if what if his story was so well known?
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  Speaker 2: How would that potentially change the trajectory of young people
• 14:53
  Speaker 2: wanting knowing that artificial intelligence was practically started by somebody
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  Speaker 2: that was black.
• 15:01
  Speaker 1: Yeah, Lisa, it you know, we had this call and
• 15:05
  Speaker 1: just I mean, when we talked about relationships earlier in
• 15:07
  Speaker 1: the show. This is just one of these relationships that
• 15:09
  Speaker 1: was kind of just like God right, Like I remember
• 15:11
  Speaker 1: we had a call and it got emotional for a
• 15:14
  Speaker 1: sec because unbeknownst to you, we are already going to
• 15:18
  Speaker 1: in Vidio. Shout out to our brother too, and I
• 15:20
  Speaker 1: know Noel's on the check in. They were like, Hey, Troy,
• 15:22
  Speaker 1: this this person that you guys should meet. I think
• 15:24
  Speaker 1: should be incredible. I'm like, who is this person? I
• 15:27
  Speaker 1: saw the deck, I'm like, oh, this is this is
• 15:28
  Speaker 1: a great story. But when we connected, it was fresh
• 15:32
  Speaker 1: off in invest fast and I was like, there was
• 15:34
  Speaker 1: this message that I got from my brother Marcus Rose
• 15:37
  Speaker 1: about you know, being who you're going to be so
• 15:39
  Speaker 1: somebody else can be who they're going to be. And
• 15:41
  Speaker 1: when I relayed that message to you, I said, yes.
• 15:44
  Speaker 1: Jensen and Chris, the co founders of Nvidio named the
• 15:48
  Speaker 1: chip Blackwell, they did their part. They may not have
• 15:51
  Speaker 1: told his story, but they did their part so that
• 15:54
  Speaker 1: we could now do our part. I want to know
• 15:57
  Speaker 1: what this moment feels like for you. I've see being
• 16:00
  Speaker 1: on the campus, being there meeting the co founder. What
• 16:04
  Speaker 1: was this moment like for you.
• 16:10
  Speaker 6: You know, I want to say that this moment right
• 16:13
  Speaker 6: now is bigger to me than that moment. This moment
• 16:18
  Speaker 6: to me is bigger because this is my community, this
• 16:22
  Speaker 6: is what this is who my grandfather cared about, and
• 16:27
  Speaker 6: these are the people I care about, and so this
• 16:29
  Speaker 6: is bigger. And to see their excitement about this that
• 16:33
  Speaker 6: this moves me in a way I cannot express, But
• 16:38
  Speaker 6: to answer your question directly, it was interesting. It's a
• 16:46
  Speaker 6: full circle moment in so many ways. Because I just
• 16:50
  Speaker 6: want to put a finer point on something you said earlier,
• 16:53
  Speaker 6: where Nvidia named has a history of naming their products
• 16:58
  Speaker 6: after accomplished scientists and things like that. Well, Vera Ruben,
• 17:03
  Speaker 6: who's the next one, she's actually an astronomer, and then
• 17:07
  Speaker 6: another person like they're just different people who are who
• 17:11
  Speaker 6: have made profound contributions to science. He's the only one
• 17:16
  Speaker 6: who's really done something in AI specifically, And part of
• 17:21
  Speaker 6: the reason is there are only a few of them,
• 17:24
  Speaker 6: and most of them just like Claude Shannon is one
• 17:29
  Speaker 6: and I think that's what Claude is named after. But
• 17:33
  Speaker 6: so we came in there and saw what they had,
• 17:39
  Speaker 6: what they're creating with his work. It's just so powerful.
• 17:42
  Speaker 6: But it's also something else because nobody knows that he
• 17:47
  Speaker 6: was there doing it, you know, So it's two things
• 17:51
  Speaker 6: at once.
• 17:52
  Speaker 10: Ernest, what's up?
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