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Speaker: Picture a dirt road.

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You are walking forward.

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Someone is walking toward you.

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You each have a gun.

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One bullet each.

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If you shoot too early, you
miss.

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If you wait too long, though,
they shoot first.

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In a normal duel, if they fire
and miss, you hear it.

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You know.

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You walk forward.

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Take your time and you win.

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But what if the guns make no
sound?

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If you fire and miss, they
don't know you're empty.

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And you don't know about them.

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You keep walking, step by step,
not knowing if the person

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coming toward you is holding
their fire or has already spent

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their one shot.

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In 2024, the most powerful
piece of artificial intelligence

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hardware ever built was named
after the man who spent his life

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thinking about this problem.

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I'm Daina Bouquin, and this is
Lore in the Machine.

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Santa Monica, California.

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1950. Noon.

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Every day in one office at the
Rand Corporation, a group of men

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sits down to play Kriegsspiel.

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It's chess, but you can't see
your opponent's pieces.

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The referee sits between the
two boards.

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He tells you only whether a
move you want to make is legal

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or illegal.

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That's all.

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Otherwise, nothing.

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You are playing a game you can
only have see against an

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opponent you cannot read, one
decision at a time.

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The man who hosts this game is
David Blackwell.

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He is one of the most gifted
mathematicians in the country.

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He is also one of very few
black men walking these

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particular halls.

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And he is completely
fascinated, not by the weapons

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being modeled in adjacent
offices, but by the shape of not

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knowing, by what it means to
act wisely without full

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information.

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This is not idle curiosity.

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It is his research, and it
leads him eventually to the

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silent duel.

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The math for a normal duel
turns out to be straightforward.

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Blackwell and his colleagues
solve it in a day.

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But the silent version, the one
where a missed shot is

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invisible, where you cannot
distinguish a patient opponent

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from an empty one.

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That problem is something else.

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It sits in the middle of
everything he cares about.

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How do you make decisions when
the signals you need simply

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don't exist?

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Blackwell knew this problem
from the inside.

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He had been the seventh African
American to earn a PhD in

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mathematics.

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Brilliant enough that when a
position opened at UC Berkeley,

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the math department had wanted
him and the university president

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agreed.

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But there was a catch no one
said out loud until the offer

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just quietly disappeared.

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The department head's wife
hosted faculty dinners, and she

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refused to have a black man in
her home.

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David Blackwell spent his
career making high-stakes moves

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in a game where the rules were
hidden, where the obstacles were

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invisible until the moment they
stopped him.

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He understood in a way that was
not abstract at all what it

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meant to walk forward without
knowing where the shots were

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coming from.

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He also had an unusual
relationship with the work that

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he'd been hired to do.

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He had grown up in Centralia,
Illinois, with a picture of

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hand-to-hand combat on his
uncle's wall, listening to his

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father and uncle describe what
the First World War had actually

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cost them.

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He believed quietly and without
apology that war was stupid.

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He once stopped an entire line
of research, just abandoned it

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completely, when he realized the
math could lead somewhere

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harmful.

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One afternoon, an economist
comes to his office.

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He needs a number.

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The probability of a major war
in the next five years.

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And he explains why.

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Long-term resource allocation.

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The question is entirely
reasonable.

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Blackwell gives a textbook
answer.

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Probability only applies to
repeatable events.

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A war is not repeatable.

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You can't run the next five
years a thousand times and track

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the outcomes.

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The probability is either zero
or one, and we won't know for

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five years.

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The economist thanks him and
leaves.

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He mentions on his way out that
every statistician he'd spoken

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to gave him exactly the same
answer.

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Blackwell is left alone with
that.

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And it gets worse the longer he
thinks about it.

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A man had come to him with
perhaps the most important

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question in the world at that
moment.

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A reasonable question asked in
good faith.

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Every mathematician Blackwell
knew had handed him the same

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useless, technically correct,
but completely unhelpful answer.

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The field had failed him.

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And so had Blackwell.

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A few weeks later, a
mathematician named Jimmy Savage

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comes through Rand.

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Blackwell tells him about the
economist, and Savage shows him

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something.

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Probability does not have to be
a frequency.

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It can be a degree of belief.

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A best current guess, held
loosely, revised as new

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information arrives.

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This changes everything.

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Not gradually.

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Like opening a door.

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Because this is how people
actually navigate the world.

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You don't wait for enough
information to draw a frequency

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distribution.

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You walk into a situation with
everything you currently know.

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You make your best call.

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And when something changes, you
update.

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Keep walking.

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This is what the silent duel
had been about all along.

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In 1956, Blackwell published a
paper that would eventually find

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its way into machine learning
textbooks.

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The core idea is
this. In a repeated game, you don't need a perfect strategy. You measure the distance between where you are and where you want to be.

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You correct your next move to
close the gap.

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Over time you converge.

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Not by knowing the answer in
advance, but by never stopping

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the process of adjustment.

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Sit with that for a moment.

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Not certainty, not omniscience,
just a method for moving

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through a game you can only half
see.

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In 2024, Jensen Huang, CEO of
NVIDIA, stands on a stage and

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announces their newest chip
architecture.

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208 billion transistors.

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The most powerful piece of AI
hardware they had ever built.

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They named it Blackwell.

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These systems, the ones now
woven into search engines and

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writing tools and medical
diagnostics, are not programmed

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with answers.

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They are trained on human
writing.

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Enormous quantities of it,
until they develop something

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that functions like intuition
about what comes next.

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Not knowledge, just pattern,
probability.

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Best current guess.

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Which means every time an LLM
generates a response, it is

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doing what Blackwell described
in that RAND office.

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Walking forward with everything
it currently knows, measuring

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the gap between where it is and
where it needs to be, adjusting

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and advancing.

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It doesn't know what it doesn't
know.

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It can't see the whole board.

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And neither can we.

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We have spent years arguing
about whether these systems are

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on a path towards something that
surpasses us, some kind of

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intelligence that transcends
human limits.

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We talk about them as if they
arrived from somewhere else.

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As if they are a different kind
of thing entirely.

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But they come from us.

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From the full written record of
everything we have ever said

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online, from all of our
digitized documents, every

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argument and letter and
explanation and story, they move

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through uncertainty exactly the
way we do.

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Just at a scale we can't hold
in our heads.

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Blackwell formalized this.

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He built his entire life's work
on top of it.

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Not a puzzle he encountered in
a book, but as something he had

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lived in a game where the rules
were hidden and the obstacles

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were invisible until the moment
they stopped him.

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He could not have known what he
was describing.

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He could not have seen it.

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He spent his life walking the
silent duel.

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And then, without knowing it,
he taught us how to build things

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that walk it too.

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We didn't build an oracle.

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We built a mirror. And then we
were surprised when it couldn't

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see what we couldn't see.

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The guns are still silent, and
we're all still walking.

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I'm Daina Bouquin, and this is
Lore in the Machine.

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Now this is the point where the
music usually starts playing,

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but I haven't done the thing yet
that seems obvious, and that's

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to ask you to rate and subscribe
to this podcast if you enjoy

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it.

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It'll really help others find
the show, and it'll give me

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something to smile about too.

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Thanks for listening.