Kind: captions
Language: en
the following is the conversation with
scott anderson his second time on the
podcast
he is a professor at ut austin director
of the quantum information center
and previously a professor at mit
last time we talked about quantum
computing this time
we talk about computation complexity
consciousness
and theories of everything i'm recording
this intro
as you may be able to tell in a
very strange room in the middle of the
night
i'm not really sure how i got here or
how i'm going to get out but
hunters thompson saying i think applies
to today and the last few days and
actually
the last couple of weeks life
should not be a journey to the grave
with the intention of arriving safely in
a pretty and well-preserved body
but rather to skid and broadside in a
cloud of smoke
thoroughly used up totally worn out
and loudly proclaiming wow
what a ride so i figured whatever i'm up
to here
and yes lots of wine is involved i'm
gonna have to improvise
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friedman
and now here's my conversation with
scott
erinson let's start with the most absurd
question but i've read you write some
fascinating stuff about it so uh let's
go there
are we living in a simulation what
difference does it make lex
i mean i'm serious what difference
because if we are
living in a simulation it raises the
question
how real does something have to be in
stimulation for in it to be
sufficiently immersive for us humans but
i mean even in principle how could we
ever know if we were in one
right a perfect simulation by definition
is something that's indistinguishable
from the real thing well we didn't say
anything about perfect it could be
no no that's that's right well if it was
an imperfect simulation if we could hack
it
you know find a bug in it then that
would be one thing right if
if this was like the matrix and there
was a way for me to
you know do flying kung fu moves or
something by hacking the simulation
well then you know we would have to
cross that bridge when we came to it
wouldn't we
right i mean at that point you know i
it's
it's uh hard to see the difference
between that and just uh
uh what people would ordinarily refer to
as a world with miracles
you know uh what about from a different
perspective thinking about the universe
as a computation like a program running
on a computer
that's kind of a neighboring concept it
is it is an interesting and reasonably
well-defined question to ask
is the world computable you know you
know does the world satisfy
what we would call in cs the the church
touring thesis
yeah that is you know uh could we take
any physical system
and simulate it to uh you know any
desired precision by a touring machine
you know given the appropriate input
data right and
so far i think the indications are
pretty strong that
our world does seem to satisfy the
church-touring thesis
uh at least if it doesn't then we
haven't yet discovered why not
uh but now does that mean that our
universe is a simulation
well you know that word seems to suggest
that there is some other
larger universe in which it is running
right right
and the problem there is that if the
simulation is perfect
then we're never going to be able to get
any direct evidence
about that other universe you know we
will only be able to see
uh the effects of the computation that
is running in this universe
well let's imagine an analogy let's
imagine a pc a personal computer a
computer
is it possible with the advent of
artificial intelligence
for the computer to look outside of
itself to see
to understand its creator i mean that's
a simple is that is that a ridiculous
connection well i mean with the
computers that we actually have
i mean first of all uh we we all know
that uh humans have done an imperfect
job of you know
enforcing the abstraction boundaries of
computers
right like you may try to confine some
program to a playpen
but you know as soon as there's one uh
uh
memory allocation error in in the c
program
then the program has gotten out of that
play pen and it can do whatever it wants
right this is how most hacks work you
know
viruses and worms and exploits and you
know you would have to imagine that
an ai would be able to discover
something like that
now you know of course if we could
actually discover some
exploit of reality itself then you know
then this whole
i mean we we then in some sense we we
wouldn't have to philosophize about this
right this would no longer be a
metaphysical conversation
right this would just but that's
the question is what is what would that
hack look like yeah well i have no idea
i mean
uh uh peter shore uh you know the
you know very famous person in quantum
computing of course has a joked
that uh maybe the reason why we haven't
yet
you know integrated general relativity
in quantum mechanics
is that you know the part of the
universe that depends on both of them
was that
was actually left unspecified and if we
ever tried to do an experiment
uh involving the singularity of a black
hole or something like that
then you know the universe would just uh
generate an overflow error
or something right yeah we would just
crash the universe
now um you know the the the universe you
know has seemed to hold up pretty well
for you know 14 billion years right so
you know my uh you know uh
occam's razor kind of guess has to be
that you know it will continue to hold
up you know that the fact that we don't
know the laws of physics
governing some phenomenon is not a
strong sign
that probing that phenomenon is going to
crash the universe
right but you know of course i could be
wrong but do you think
on the physics side of things you know
there's been uh
recently a few folks eric weinstein
and stephen wolfram that came out with a
theory of everything i think there's a
history of physicists dreaming and
working on
the unification of all the laws of
physics do you think it's possible that
once we understand
uh more physics not necessarily the
unification of the laws but just
understand physics more deeply at the
fundamental level
we'll be able to start you know uh
i mean part of this is humorous but uh
looking
to see if there's any bugs in the
universe that can be exploited for
uh you know traveling at uh
not just speed of light but just
traveling faster than our current
uh spaceships can travel all that kind
of stuff
well i mean to travel faster than our
current spaceships
could travel you wouldn't need to find
any bug in the universe right the known
laws of physics
you know let us go much faster up to the
speed of light
right and you know when people want to
go faster than the speed of light
well we actually know something about
what that would entail
namely that you know according to
relativity
that seems to entail communication
backwards in time
okay so then you have to worry about uh
close time like curves and all of that
stuff so you know in some sense we
we sort of know the price that you have
to pay for these things
right understanding of physics that's
right that's right we can't
you know say that they're impossible but
we you know we know that
sort of a lot else in physics breaks
right so uh now regarding uh eric
weinstein and stephen wolfram like i
wouldn't say that either of them has a
theory of
everything i would say that they have
ideas that they hope
you know could someday lead to a theory
of everything is that a worthy pursuit
well i mean certainly let's say by
theory of everything
you know we don't literally mean a
theory of cats and
of baseball and you know but we just
mean it in the
in the more limited sense of everything
a fun
a fundamental theory of physics right of
all of the
fundamental interactions of physics of
course such a theory
even after we had it uh you know would
would leave
the entire question of all the emergent
behavior right
you know to uh to be explored uh so it's
so it's only everything for a specific
definition of everything
okay but in that sense i would say of
course that's worth pursuing
i mean that is the entire program of
fundamental physics
right all of my friends who do quantum
gravity who do string theory who do
anything like that
that is what's motivating them yeah it's
it's funny though but
i mean eric weinstein talks about this
it is i don't know much about the
physics world but i know about the
ai world it is a little it is a little
bit taboo
uh to talk about agi for example on the
ai
side so really to talk about
uh the big dream of the community i
would say
because it seems so far away it's almost
taboo to bring it up because
uh you know it's seen as the kind of
people that dream about creating a truly
superhuman level intelligence that's
really far out there
people because we're not even close to
that and it feels like the same thing is
true for the physics
community i mean stephen hawking
certainly talked uh constantly about
theory of everything
right uh uh uh you know i mean i mean
people you know used those terms who
were you know some of the most respected
people in the
in the in the whole world of physics
right but i mean i think that
the distinction that i would make is
that people
might react badly if you use the term in
a way that suggests
that that you you know thinking about it
for five minutes have come up with this
major new insight about it yeah
right it's it's difficult stephen hawk
is
is a not a great example because i think
you can do whatever the heck you want
when you get to that level
and i certainly see like seeing your
faculty you know
that you know at that point that's the
one of the nice things about getting
older is you
stop giving a damn but community as a
whole
they tend to roll their eyes very
quickly at stuff that's outside the
quote-unquote mainstream well well let
me let me put it this way i mean if you
asked you know ed whitton let's say
who is you know you might consider the
leader of the string community
and thus you know very very mainstream
in a certain sense but
he would have no hesitation in saying
you know of course
you know they're looking for a you know
uh uh you know a
a a unified description of nature of
you know of general relativity of
quantum mechanics of all the fundamental
interactions of nature
right now you know whether people would
call that a theory of everything whether
they would use that
that term that might vary you know lenny
suskin would definitely have no problem
telling you that you know if that's what
we want right
for me who loves human beings in
psychology
it's kind of ridiculous to say
a theory that unifies the laws of
physics gets you to understand
everything i would say you're not even
close to understanding everything
yeah right well yeah i mean the word
everything is a little ambiguous here
right because you know and then people
will get into debates about
you know reductionism versus emergentism
and blah blah blah
and so in in not wanting to say theory
of everything people might just be
trying to short-circuit that debate
and say you know look you know yes we
want a fundamental theory of
you know the particles and interactions
of nature let me bring up the next topic
that people don't want to mention
although they're getting more
comfortable with it it's consciousness
you mentioned that you have a talk on
consciousness
that i watched five minutes of but the
internet connection was really bad
was this my talk about you know uh
refuting the integrated information
theory
yes which is a particular account of
consciousness that yeah i think
one can just show it doesn't work right
so let me much harder to say what does
work what doesn't work yeah yeah
let me ask maybe it'd be nice to uh
comment on
you talk about also like the semi hard
problem of consciousness or like almost
hard pro or kind of hard pretty pretty
hard pretty hard one i think i call it
so maybe can you uh talk about that uh
their idea of um
of the approach to modeling
consciousness and why you don't find it
convincing
what is it first of all okay well so so
what what what i called the pretty hard
problem of consciousness this is my
term although many other people have
said something equivalent to this okay
uh but uh it's just you know the the
problem of you know giving an account of
just which physical systems are
conscious and which are not
or you know if there are degrees of
consciousness then quantifying how
conscious
a given system is oh awesome so that's
the pretty hard
yeah that's what i mean that's it i'm
adopting it i love it that's a good
a good ring to it and so you know the
infamous hard problem
of consciousness is to explain how
something like consciousness could arise
at all you know in a material universe
right or you know why does it ever feel
like anything
to to experience anything right and
you know so i'm trying to distinguish
from that problem right
and say you know no okay i am i would
merely settle for an account
that could say you know is a fetus
conscious you know if so at which
trimester you know is a uh
is a dog conscious you know what about a
frog
right or or even as a precondition you
take that both these things are
conscious
tell me which is more conscious yeah for
example yes
yeah yeah i mean if consciousness is
some multi-dimensional vector well just
tell me in which respects these things
are conscious and in which respect they
aren't
right and you know and have some
principled way to do it where you're not
you know carving out exceptions for
things that you like or don't
like but could somehow take a
description of an arbitrary physical
system
and then just based on the physical
properties of that system
or the informational properties or how
it's connected or something
like that just in principle calculate
you know its degree of consciousness
right i mean this this this would be the
kind of thing that we would need
you know if we wanted to address
questions like you know
what does it take for a machine to be
conscious right or when or
you know when when when should we regard
ais as being conscious
um so now this iit
this integrated information theory uh
which has been put forward by uh
giulio tanoni and a bunch of his uh
uh collaborators over the last
decade or two uh this is noteworthy i
guess
as a direct attempt to answer that
question
to you know answer the to address the
pretty hard problem
right and they give a uh a criterion
that's just based on how a system is
connected so you so it's up to you
to sort of abstract the system like a
brain
or a microchip as a collection of
components that are connected to each
other by some
pattern of connections you know and and
to specify how the components can
influence each other
you know like where the inputs go you
know where they affect the outputs but
then once you've specified that
then they give this quantity that they
call fee you know the greek letter
phi and the definition of phi is
actually changed over
time it changes from one paper to
another
but in all of the variations it involves
something about
what we in computer science would call
graph expansion
so basically what this means is that
they want it uh
in order to get a large value of fee uh
it should not be possible to
take your system and partition it into
two components
that are only weakly connected to each
other
okay so whenever we take our system and
sort of
try to split it up into two then there
should be lots and lots of connections
going between the two components
okay well i understand what that means
on a graph do they formalize
what uh how to construct such a graph or
data structure whatever
uh or is this well one of the criticism
uh
i i've heard you kind of say is that a
lot of the very interesting specifics
are usually communicated through
like natural language like like through
words
so it's like the details aren't always
well they well it's true i mean they
they they they have nothing even
resembling a derivation
of this fee okay so what they do is they
state a whole bunch of postulates
you know axioms that they think that
consciousness should satisfy
and then there's some verbal discussion
and then at some point
fee appears right right and this this
was one the first thing that really made
the hair stand on my neck to be honest
because
they are acting as if there is a
derivation they're acting as if you know
you're supposed to think that this is a
derivation and there's nothing even
remotely resembling
a derby they just pull the fee out of a
hat completely is one of
the key criticisms to you is that
details are missing or is that exactly
more fun
that's not even the key criticism that's
just that's just a side point
okay the the core of it is that i think
that the you know that they want to say
that a system is more conscious the
larger its value of fee
and i think that that is obvious
nonsense okay as soon as you think about
it for like a minute
as soon as you think about it in terms
of could i construct a system
that had an enormous value of fee like
you know even larger than the brain has
but that is just implementing an error
correcting code you know doing nothing
that we would
associate with you know intelligence or
consciousness or any of it
the answer is yes it is easy to do that
right
and so i wrote blog posts just making
this point that yeah it's easy to do
that
now you know tanoni's response to that
was actually kind of incredible
right i mean i i admired it in a way
because
instead of disputing any of it he just
bit the bullet
in the sense you know he was one of the
the uh the most
uh audacious bullet bitings i've ever
seen in my career
okay he said okay then fine
you know this system that just applies
this error correcting code it's
conscious
you know and if it has a much larger
value of fee then
you or me it's much more conscious than
you want me
you know you we just have to accept what
the theory says because
you know science is not about confirming
our intuitions it's about challenging
them
and you know this is what my theory
predicts that this thing is conscious
and
you know or super duper conscious and
how are you going to prove me wrong see
i would
so the way i would argue against your
blog post
is i would say yes sure you're right in
general but
for naturally arising systems developed
through the process of evolution on
earth
the this rule of the larger fee being
associated being associated with more
consciousness is correct
yeah so that's not what he said at all
right right because he wants this to be
completely general
right so we can apply to even computers
yeah i mean i mean the whole interest of
the theory
is the you know the hope that it could
be completely general apply to aliens to
computers to uh
uh animals coma patients to any of it
right yeah and uh uh so so so he just
said well
you know uh scott is relying on his
intuition but you know i'm relying on
this theory
and you know to me it was almost like
you know are we being serious here
like like like you know like like okay
yes in science we try to learn highly
non-intuitive things but what we do is
we
first test the theory on cases where we
already know the answer
right like if if someone had a new
theory of temperature right
then you know maybe we could check that
it says that boiling water is hotter
than ice
and then if it says that the sun is
hotter than anything you know you've
ever
experienced then maybe we we trust that
extrapolation right
but like this this theory like if if you
know
it it's now saying that you know a
a gigantic grit like regular grid of
exclusive or gates
can be way more conscious than a you
know a person
or than any animal can be you know even
if it
you know is you know is is is is so
uniform that it might as just well just
be a blank wall
right and and so now the point is if
this theory is sort of getting wrong
the question is a blank wall you know
more conscious than a person
then i would say what is what is there
for it to get right
so your sense is a blank wall uh
is not more conscious than a human being
yeah i mean i mean i mean
you could say that i am taking that as
one of my axioms
i'm saying i'm saying that if if a
theory of consciousness
is is get getting that wrong then
whatever it is talking about at that
point i
i i'm not going to call it consciousness
i'm going to use a different word you
have to use a different word i mean yeah
it's all
it's possible just like with
intelligence that us humans conveniently
define these very difficult to
understand concepts
in a very human-centric way just like
the touring test
really seems to define intelligence as a
thing that's human-like
right but i would say that with any uh
concept
you know there's uh uh uh
you know like we we we first need to
define it right and a definition
is only a good definition if it matches
what we thought we were talking about
you know
prior to having a definition right yeah
and i would say that you know
uh fee as a definition of consciousness
fails that test that is my argument
so okay let's so let's take a further
step so you mentioned that the universe
might be
uh the touring machine so like it might
be computational or simulatable by one
anyway
simulated by one so yeah do you what's
your sense
about consciousness do you think
consciousness is computation
that we don't need to go to any place
outside of the computable universe
to uh you know to to understand
consciousness to build consciousness to
measure consciousness all those kinds of
things i don't know
these are what uh you know have been
called the the vertigonous
questions right there's the questions
like like uh you know
you get a feeling of vertigo and
thinking about them right
i mean i certainly feel like uh i
am conscious in a way that is not
reducible to computation
but why should you believe me right i
mean
and and if you said the same to me then
why should i believe you
but as computer scientists yeah i feel
like
a computer could be intel could achieve
human level intelligence
but and that's actually a feeling and a
hope
that's not a scientific belief it's just
we've built up enough intuition the same
kind of intuition you use in your blog
it's you know that's what scientists do
they i mean some of it is a scientific
method but some of it is just damn good
intuition
i don't have a good intuition about
consciousness yeah i'm not sure that
anyone does or or has
in the you know 2500 years that these
things have been discussed lex
uh but do you think we will like one of
the i got a chance to
attend i can't wait to hear your opinion
on this but attend the neuralink event
and uh one of the dreams there is to uh
you know basically push neuroscience
forward and the hope with neuroscience
is that we can inspect the machinery
from which
all this fun stuff emerges and see we're
going to notice something
special some special sauce from which
something like consciousness or
cognition emerges
yeah well it's clear that we've learned
an enormous amount about neuroscience
we've learned an enormous amount about
computation you know about machine
learning about you'll know
ai how to get it to work we've learned
uh an enormous amount about the
underpinnings of the physical world you
know and
you know it from one point of view
that's like an enormous distance that
we've traveled along the road to
understanding consciousness
from another point of view you know the
distance still to be traveled on the
road
you know maybe seems no shorter than it
was at the beginning yeah
right so it's very hard to say i mean
you know these are
questions like like in in in sort of
trying to have a theory of consciousness
there's sort of a problem where it feels
like
it's not just that we don't know how to
make progress it's that it's hard to
specify
what could even count as progress right
because no matter what scientific theory
someone proposed
someone else could come along and say
well you've just talked about the
mechanism you haven't said anything
about
what breathes fire into the mechanism
right really makes there's something
that it's like to be
it right and that seems like an
objection that you could always raise
yes no matter you know how much someone
elucidated
the details of how the brain works okay
let's go touring tests and love the
prize i have this intuition
call me crazy but we
that a machine to pass the touring test
and is full
whatever the spirit of it is we can talk
about how to formulate
the perfect touring test that that
machine has to
be conscious or we at least have to uh
i have a very low bar of what
consciousness is a dentist
i tend to think that the emulation of
consciousness is as good as
consciousness
so like consciousness is just a dance a
social
a social uh shortcut like a nice useful
tool
but i tend to connect intelligence
consciousness together so by
by that do you uh maybe just
to ask what uh what role does
consciousness play do you think in
passing the touring test well look i
mean it's almost tautologically true
that if we had a machine that passed the
turing test then it would be emulating
consciousness
right so if your position is that you
know emulation of consciousness is
consciousness
then so you know by by definition any
machine that passed the touring test
would be conscious
but it's uh uh but i mean we know that
you could say that you know that that is
just a way to rephrase the original
question you know is an emulation of
consciousness
you know necessarily conscious right and
you can you know
i hear i'm not saying anything new that
hasn't been
debated ad nauseum in the literature
okay but
you know you could uh imagine some very
hard cases like imagine a machine
that passed the touring test but it did
so just
by an enormous cosmological sized
look-up table
that just cached every possible
conversation that could be had the old
chinese room
well well yeah yeah but but this is uh
uh i mean i mean the chinese room
actually would be doing some computation
at least in searle's version right
here i'm just talking about a table
lookup okay now
it's true that for conversations of a
reasonable length this
you know lookup table would be so
enormous that wouldn't even fit in the
observable
universe okay but supposing that you
could build a big enough look-up table
and then just you know pass the touring
test just by looking up what the person
said
right are you going to regard that as
conscious okay
let me try to make this yeah yeah formal
and then you can shut it down
i think that the emulation of something
is that something if there exists in
that system a black box
that's full of mystery so like
uh full of mystery to whom to uh human
in inspectors
so does that mean that consciousness is
relative to the observer like could
something be conscious for us
but not conscious for an alien that
understood better what was happening
inside the black box
yes so that if inside the black box is
just a look-up table
the alien that saw that would say this
is not conscious to us
another way to phrase the black box is
layers of abstraction
which make it very difficult to see to
the actual underlying
functionality of the system and then we
observe just the abstraction
and so it looks like magic to us but
once we understand the
inner machinery it stops being magic and
so like
that's a prerequisite is that you can't
know
how it works some part of it because
then there has to be in our human mind
uh entry point for the magic
so that that's that's a formal
definition of the system
yeah well look i mean i i explored a
view and this essay i wrote
called the ghost and the quantum touring
machine uh seven years ago
that is uh related to that except that i
did not want to
have consciousness be relative to the
observer right because i think that
you know if consciousness means anything
it is something that is experienced by
the entity that is conscious
right you know like i don't need you to
tell me that i'm conscious right
nor do you need me to to to
to tell you that you are right so uh
so but but basically what i explored
there is you know are there uh
aspects of a of a system like uh like a
brain
that uh that just could not be predicted
even with arbitrarily advanced future
technologies
yes because of chaos combined with
quantum mechanical uncertainty
you know and things like that i mean
that that actually could be a
a property of the brain you know if true
that would distinguish it in a
principled way
at least from any currently existing
computer not from any possible computer
but from yeah yeah
let's do a thought experiment so yeah if
i gave you
information that you're in the entire
history of your life
basically explain away free will with a
look-up table say that
this was all predetermined that
everything you experienced has already
been predetermined
wouldn't that take away your
consciousness wouldn't you yourself that
wouldn't
experience of the world change for you
in a way that's
you you can't well let me put it this
way if you could do like in a greek
tragedy where you know you would just
write down a prediction for what i'm
going to do
and then maybe you put the prediction in
a sealed box
and maybe you know you you uh open it
later and you
show that you knew everything i was
going to do or you know
of course the even creepier version
would be you tell me the prediction
and then i try to falsify it and my very
effort to falsify it makes it come true
right but let's let's you know let's
even forget that you know that version
is as convenient as it is for fiction
writers right let's just
let's just do the version where you put
the prediction into a sealed envelope
okay but uh if you could reliably
predict everything that i was going to
do
i'm not sure that that would destroy my
sense of being conscious
but i think it really would destroy my
sense of having free will
you know and much much more than any
philosophical conversation could
possibly do that
right and so i think it becomes
extremely interesting to ask
you know could such predictions be done
you know even in principle
is it consistent with the laws of
physics to make such predictions
to get enough data about someone that
you could actually generate such
predictions without having to kill them
in the process to you know
slice their brain up into little slivers
or something i mean
theoretically possible right well um i
don't know i mean i mean it might be
possible but only at the cost of
destroying the person
right i mean it depends on how low you
have to go
in sort of the substrate like if there
was a nice
digital abstraction layer if you could
think of each neuron as a kind of
transistor
computing a digital function then you
could imagine
some nanorobots that would go in and we
just scan the state of each transistor
you know of each neuron
and then you know make a a good enough
copy
right but if it was actually important
to get down to the molecular
or the atomic level then you know
eventually you would be up against
quantum effects you would be up against
the unclonability of quantum states
so i think it's a question of uh how
good of a replica
how good does the replica have to be
before you're going to count it as
actually a copy of you
or as being able to predict your actions
uh that's a totally open question then
yeah yeah yeah and
and especially once we say that well
look maybe there's no way to pre
you know to make a deterministic
prediction because you know there's all
there you know we know that there's
noise buffeting the brain around
presumably even quantum mechanical
uncertainty
you know affecting the sodium ion
channels for example whether they open
or they close
um you know there's no reason why
over a certain time scale that shouldn't
be amplified just like we imagine
happens with the weather
or with any other you know chaotic
system uh
so um so if if that stuff
is is important right then uh
then then you know we would say uh well
you know you
you you can't uh uh you know you're
you're never going to be able to make an
accurate enough copy
but now the hard part is well what if
someone can make a copy
that sort of no one else can tell apart
from you right
it says the same kinds of things that
you would have said
maybe not exactly the same things
because we agree that there's noise
but it says the same kinds of things and
maybe you alone would say no
i know that that's not me you know it's
it doesn't share my
i haven't felt my consciousness leap
over to that other thing
i still feel it localized in this
version right
then why should anyone else believe you
what are your thoughts
i'd be curious you're a good person to
ask which is uh
penn rose's roger penrose's work on
consciousness
saying that there you know there is some
with axons and so on there might be some
biological places where quantum
mechanics can come into play
and through that create consciousness
somehow yeah
okay well um uh familiar with his work
of course you know i read
penrose's books as a teenager they had a
huge impact on me
uh uh five or six years ago i had the
privilege to actually talk these things
over with penrose you know at some
length at a conference in minnesota
and uh you know he is uh uh you know an
amazing uh
personality i admire the fact that he
was even raising such uh audacious
questions at all
uh but you know to to to answer your
question i think the first thing we need
to
get clear on is that he is not merely
saying that quantum mechanics is
relevant to consciousness
right that would be like um you know
that would be tame
compared to what he is saying right he
is saying that
you know even quantum mechanics is not
good enough right if because if
supposing for example that the brain
were a quantum computer
maybe that's still a computer you know
in fact a quantum computer can be
simulated by an ordinary computer it
might merely need
exponentially more time in order to do
so right so that's simply not good
enough for him
okay so what he wants is for the brain
to be a quantum gravitational computer
or or uh he wants the brain to be
exploiting
as yet unknown laws of quantum gravity
okay which would which would be
uncomputable
that's the key point okay yes yes that
would be literally uncomputable
and i've asked him you know to clarify
this but uncomputable
even if you had an oracle for the
halting problem
or you know and and or you know as high
up as you want to go and the sort of
high
the usual hierarchy of uncomputability
he wants to go beyond all of that okay
so
so you know just to be clear like you
know if we're keeping count of how many
speculations
you know there's probably like at least
five or six of them right
there's first of all that there is some
quantum gravity theory that would
involve this kind of
uncomputability right most people who
study quantum gravity would not agree
with that
they would say that what we've learned
you know what little we know about
quantum gravity from the
this ads cft correspondence for example
has been very much consistent with the
broad idea of nature being computable
right um but uh but all right but but
supposing that he's right about that
then you know
what most physicists would say is that
whatever
new phenomena there are in quantum
gravity you know they might be relevant
at the singularities of black holes they
might be relevant at the big bang
uh they are plainly not relevant
to something like the brain you know
that is operating at ordinary
temperatures
you know with ordinary chemistry and
you know the the the physics underlying
the brain they
would say that we have you know the
fundamental physics of the brain they
would say that we've
pretty much completely known for for
generations now
right uh because you know quantum field
theory lets us sort of
parametrize our ignorance right i mean
sean carroll has made this case and you
know in great detail right
that sort of whatever new effects are
coming from quantum gravity
you know they are sort of screened off
by quantum field theory
right and this is this bring you know
brings us to the whole idea of effective
theories
right but that like we have you know
that in like in the standard model of
elementary particles
right we have a quantum field theory
that seems totally adequate for all of
the terrestrial phenomena
right the only things that it doesn't
you know explain
are well first of all you know the
details of gravity
if you were to probe it like at a uh you
know extremes of you know
curvature or like incredibly small
distances
it doesn't explain dark matter it
doesn't explain black hole singularities
right but these are all very exotic
things very you know far removed from
our life on earth
right so for penrose to be right he
needs
you know these phenomena to somehow
affect the brain he needs the brain to
contain
antenna that are sensitive to the black
hole
to this as yet unknown physics right and
then he needs
a modification of quantum mechanics okay
so he needs
quantum mechanics to actually be wrong
okay he needs
uh uh what what he wants is what he
calls an objective reduction mechanism
or
an objective collapse so this is the
idea that once quantum states get large
enough
then they somehow spontaneously collapse
right that uh uh um you know and and
this is an idea that lots of people have
explored
uh you know there's uh something called
the grw
proposal that tries to uh you know
say something along those lines you know
and these are theories that actually
make testable predictions
right which is a nice feature that they
have but you know the very fact that
they're testable may mean that in the
uh you know in the in the coming decades
we may well be able to test these
theories and show that they're they're
they're wrong
right uh you know we may be able to test
some of penrose's ideas
if not not his ideas about consciousness
but at least his ideas that about an
objective collapse of quantum states
right and people have actually
like dick balmester have actually been
working to try to do these experiments
they haven't been able to do it yet to
attest penrose's proposal
okay but penrose would need more than
just an objective collapse of quantum
states
which would already be the biggest
development in physics for a century
since quantum mechanics itself okay he
would need
for consciousness to somehow be able to
influence
the direction of the collapse so that it
wouldn't be completely random
but that you know your dispositions
would somehow influence the quantum
state
to collapse more likely this way or that
way
okay finally penrose you know says that
all of this
has to be true because of an argument
that he makes based on girdle's
incompleteness theorem
okay right now like i would say the
overwhelming majority of computer
scientists and mathematicians
who have thought about this i don't
think that girdles and completeness
theorem can do what he needs it to do
here right i don't think that that
argument is sound okay
but that is you know that is sort of the
tower that you have to ascend to if
you're going to go where penrose goes
and the
intuition uses with uh yeah the
completeness theorem is that basically
that there's important stuff that's not
computable
it's not just that because i mean
everyone agrees that there are problems
that are uncomputable right that's a
mathematical theorem
right that but what penrose wants to say
is that uh
uh you know the um you know for example
there are statements
uh you know for you know given any uh
formal system
you know for doing math right there will
be true statements of arithmetic
that that formal system you know if it's
adequate for math at all
if it's consistent and so on will not be
able to prove
uh a famous example being the statement
that that system itself is consistent
right no you know good formal system can
actually prove its own consistency
that can only be done from a stronger
formal system which then can't prove its
own consistency
and so on forever okay that's gurdle's
theorem
but now why is that relevant to uh
consciousness right uh uh well you know
i mean i mean the the idea that it might
have something to do with consciousness
as an old one
girdle himself apparently thought that
it didn't really um you know uh
lucas uh uh um um
thought so i think in the 60s and
penrose is really just you know sort of
updating what what uh uh what what they
and others had said
i mean you know the idea that girdle's
theorem could have something to do with
consciousness was
you know um in in 1950 when alan turing
wrote his article
uh about the touring test he already you
know
was writing about that as like an old
and well-known idea and as one that he
was as a wrong one that he wanted to
dispense with okay but
the basic problem with this idea is you
know penrose wants to say
that uh and and all of his predecessors
your you know want to say
that you know even though you know this
given formal system cannot
prove uh its own consistency we
as humans sort of looking at it from the
outside
can just somehow see its consistency
right
and the you know the rejoinder to that
you know from the very beginning has
been well can we really
yeah i mean maybe or maybe maybe you
know maybe maybe he
penrose can but you know can the rest of
us
right uh and you know i i noticed that
that um
you know i mean it is perfectly
plausible to imagine
a computer that could say you know it
would not be limited to working within a
single formal system
right they could say i am now going to
adopt the hypothesis
that this that my formal system is
consistent right and i'm now going to
see what can be done from that stronger
vantage point
and and so on and you know when i'm
going to add new axioms to my system
totally plausible there's absolutely
gerdle's theorem has nothing to say
about
against an ai that could repeatedly add
new axioms
all it says is that there is no absolute
guarantee
that when the ai adds new axioms that it
will always be right
right okay and you know and that's of
course the point that penrose pounces on
but the reply is obvious and you know
it's one that that alan turing made 70
years ago
name we we don't have an absolute
guarantee that we're right when we add a
new axiom
right we never have and plausibly we
never will
so on alan turing you took part in the
lobner prize
uh uh not really no i didn't i mean
there was this
uh uh kind of ridiculous claim that was
made uh
some almost a decade ago about an
a chat bot called eugene goose
i guess you didn't participate as a
judge in the lobner prize i didn't
but you participated as a judge in that
i guess it was an
exhibition event or something like that
or was eugene uh
eugene gusman that was just me writing a
blog post because some journalists
called me to ask about it did you ever
chat with him i thought
i did chat with eugene gooseman i mean
it was available on the web the chat
oh interesting i didn't so yeah so all
that happened was that uh
so you know a bunch of journalists
started writing breathless articles
about you know an a you know first uh
chatbot that passes the touring test
right and it was this thing called
eugene guzman
that was supposed to simulate a 13 year
old boy
and um you know and apparently someone
had done
some tests where you know people
couldn't you know
you know were less than perfect let's
say distinguishing it from a human
and they said well if you look at
touring's paper
and you look at you know the percentages
that he that he talked about then you
know it seemed like we're past that
threshold
right and you know i had a sort of
you know different way to look at it
instead of the legalistic way
like let's just try the actual thing out
and let's see what it can do with
questions like you know is mount everest
bigger than a shoebox
okay or just you know like the most
obvious questions right and then and you
know and the answer is
well it just kind of parries you because
it doesn't know what you're talking
about right
so just clarify exactly in which way
they're obvious they're obvious
in the sense that you convert the
sentences
into the meaning of the objects they
represent and then do some basic
obvious we mean your common sense
reasoning
with the objects that the sentences
represent uh right right it was not able
to answer
you know or even intelligently respond
to basic common sense questions but let
me say something stronger than that
there was a famous chatbot in the 60s
called eliza
right that you know that managed to
actually fool
you know a lot of people right or people
would pour their hearts out
into this elisa because it simulated a
therapist
right and most of what it would do is it
would just throw back at you whatever
you said
right and this turned out to be
incredibly effective
right maybe you know therapists know
this this is you know one of their
tricks
but uh it um um you know it it really
had some people convinced
uh but you know this this thing was just
like i think it was literally just a few
hundred lines
of lisp code right it was not only was
it not intelligent it wasn't
especially sophisticated it was like a
it was a simple little hobbyist program
and eugene gusman from what i could see
was not a significant advance compared
to
uh eliza right so so this is and and
that was
that was really the point i was making
and this was
you know you didn't in some sense you
didn't need a like
a computer science professor to sort of
say this like
anyone who was looking at it and who
just had
you know an ounce of sense could have
said the same thing
right well but because you know these
journalists were call you know
calling me you know like the first thing
i said was
uh well you know no you know i i'm a
quantum computing person i'm not an ai
person you know you shouldn't ask me
then they said look you can go here and
you can try it out i said all right
all right so i'll try it out um but now
you know
this whole discussion i mean it got a
whole lot more interesting in just the
last few months
yeah i'd love to hear your thoughts
about gpt yeah yeah yeah
in the last few months we've had you
know we've we've
the world has now seen a chat engine or
a text engine
i should say called gpt-3 um
that you know i think it it's still you
know it does not pass
a touring test you know there are no
real claims that it passes the touring
test
right you know this is comes out of the
group at open ai
and you know they're you know they've
been relatively careful and what they've
claimed about the system
but i think this this this
uh as clearly as eugene gusman was not
in advance over eliza
it is equally clear that this is a major
advance over over
over eliza or really over anything that
the world has seen before
uh this is a text engine that can
come up with kind of on topic you know
reasonable sounding completions to just
about anything that you ask
you can ask it to write a poem about
topic
x in the style of poet y
and it will have a go at that yeah and
it will do you know
not a perf not a great job not an
amazing job
but you know a passable job you know
definitely you know as as good as you
know
you know in in many cases i would say
better than i would have done
right uh you know you can ask it to
write you know an
essay like a student essay about pretty
much any topic and it will get something
that i am pretty sure
would get at least a b minus you know in
my most you know
high school or even college classes
right and you know in some sense
you know the way that it did this the
way that it achieves this
um you know scott alexander of the you
know the much
mourned blog slate star codex had a
wonderful way of putting it he said that
they basically just ground up the entire
internet into a slurry
okay yeah and you know and i i to tell
you the truth i had wondered for a while
why nobody had tried that
right like why not write a chat bot by
just doing deep learning over a corpus
consisting of the entire web
right and and so so so uh now they
finally have done that
right and you know the results are are
very impressive
you know it's not clear that you know
people can argue about whether this is
truly a step
toward general ai or not but this is an
amazing capability
uh that you know uh we didn't have a few
years ago
that you know if a few years ago if you
had told me that we would have it now
that would have surprised me
yeah and i think that anyone who denies
that is just not engaging with what's
there
so their model it takes a large part of
the internet
and compresses it in a small number of
parameters
relative to the size of the internet and
is able to
without fine-tuning uh
do a basic kind of a quarrying mechanism
just like you described where you
specify a kind of poet and then
you want to write a poem and somehow i
was able to do basically a lookup on the
internet
well of relevant things i mean that's
what i mean i mean i mean
how else do you explain it well okay i
mean i mean the the training
involved you know massive amounts of
data from the internet and actually took
lots and lots of computer power lots of
electricity
right you know there are some some very
prosaic reasons why this wasn't done
earlier
right right but um you know it costs
some tens of millions of dollars i think
you know that's just for
approximately like a few million dollars
oh okay okay oh really okay
you know oh all right all right thank
you i mean as they as they scale it up
you know it will
cost but then the hope is cost comes
down and all that kind of stuff
but um basically you know it is a
neural net you know so i mean i mean or
what's now called a deep net but you
know they're basically the same thing
right so it's a
it's a form of you know uh algorithm
that people
have known about for decades right uh
but
it is constantly trying to solve the
problem
predict the next word right so it's just
trying to
predict what comes next it's not trying
to decide
what what it should say what ought to be
true
it's trying to predict what someone who
had said all of the words
up to the preceding one would say next
although to push back on that that's how
it's trained
but that's right no but it's arguable
arguable yeah
that our very cognition could be a
mechanism as that simple
of course of course i never said that it
wasn't right but right
but yeah i mean i mean and sometimes
that that is
you know if there is a deep
philosophical question that's raised by
gpt3 then that is it
right are we doing anything other than
you know this predictive processing just
trying to
constantly trying to fill in a blank of
what would come next
after what we just said up to this point
is that what i'm doing right now
it's impossible so the intuition that a
lot of people have will
look this thing is not going to be able
to reason the mountain everest
question do you think it's possible that
gbt5
6 and 7 would be able to with this exact
same process begin to
do something that looks like is
indistinguishable to us humans from
reasoning
i mean the truth is that we don't really
know what the limits are
right because exactly because you know
what we've seen so far
is that you know gbt3 was basically the
same thing as gpt-2
but just with you know a much larger uh
uh network you know more training time
bigger training corpus right and it was
you know very noticeably better right
than its immediate predecessor
so uh we you know we don't know where
you hit the ceiling here right i mean
that's the
that's the amazing part and maybe also
the scary part
right that uh you know now my guess
would be that that you know at some
point
like there has to be diminishing returns
like it can't be that simple
can it right right but i i i i wish that
i had more to base that guess on
right yeah i mean some people say that
there will be a limitation on the
we're going to hit a limit on the amount
of data that's on the internet
yes yeah yeah so sure so so there's
certainly that limit
i mean there's also um you know like if
you are looking for questions that will
stump gpt3 right you can come up with
some without you know
like you know even getting it to learn
how to balance parentheses
right like it can you know it doesn't do
such a great job
right uh you know like like you know and
you know and
its failures are are are ironic right
like like basic arithmetic
right and you think you know isn't that
what computers are supposed to be best
at
yeah isn't that where computers already
had us beat a century ago yeah right
and yeah and yet that's where gpt-3
struggles right but it's
it's amazing you know that it's almost
like a young child in that way
right that uh uh um but
but uh somehow you know because it is
just trying to predict
what what uh comes next it doesn't know
when it should stop
doing that and start doing something
very different like some
more exact logical reasoning right and
so
so you know the uh uh you know you one
one is naturally led to guess
that our brain sort of has some element
of predictive processing
but that it's coupled to other
mechanisms right that it's coupled to
you know first of all visual reasoning
which gpt3 also doesn't have
any of right although there's some
demonstration that there's a lot of
promise there
oh yeah it can complete images that's
right and using the exact same kind of
transformer mechanisms to like watch
videos on youtube
and uh so the same uh the same
self-supervised mechanism to be able to
look it'd be fascinating to think what
kind of completions you could do oh yeah
no absolutely although like
if we ask it to like you know a word
problem that involve
reasoning about the locations of things
in space i don't think it does such a
great job on those
right to take an example and so so the
guess would be
well you know humans have a lot of
predictive processing a lot of just
filling in the blanks but we also have
these other mechanisms that we can
couple to or that we can sort of call
the subroutines when we need to
and that maybe maybe you know uh to go
further that one would one would want to
integrate other forms of reasoning
let me go on another topic that is
amazing
uh which is complexity uh
what uh and then start with the most
absurdly romantic question of what's the
most beautiful idea in
computer science or theoretical computer
science to you like what just
early on in your life or in general i've
captivated you and just grabbed you
i think i'm gonna have to go with the
idea of universality
uh you know if you're really asking for
the most beautiful
i mean uh so universality
uh is the idea that you know you put
together a few
simple operations like in the case of
boolean logic that might be the and gate
the or gate the not gate right and then
your first
guess is okay this is a good start but
obviously
as i want to do more complicated things
i'm going to need more complicated
building blocks to express that
right and and that was actually my guess
when i first learned what programming
was
i mean when i was you know an adolescent
and i someone showed me
uh uh apple basic and then you know
uh gw basic if any any anyone listening
remembers that
okay but uh you know i thought okay well
now you know i mean i
i thought i felt like um this is a
revelation you know it's like
finding out where babies come from it's
like that level of you know why didn't
anyone tell me this before
right but i thought okay this is just
the beginning now i know how to write a
basic program
but to you know really write a an
interesting program like a you know a
video game which had always been my my
dream as a kid to you know
create my own nintendo games right that
you know but
you know obviously i'm going to need to
learn some way more complicated form of
programming than that
okay but you know eventually i learned
this incredible idea of universality
and that says that no you throw in a few
rules
and then you can you already have enough
to express
everything okay so for example the and
the or and the not
gate uh can all or in fact even just the
and in the not
gate or even just even just the nand
gate for example
uh is already enough to express any
boolean function
on any number of bits you just have to
string together enough of them because
you can build a universe with nand gates
you can build the universe out of nand
gates yeah
uh you know the the simple instructions
of basic
are already enough at least in principle
you know if we ignore details like how
much memory can be accessed and stuff
like that
that is enough to express what could be
expressed by any programming language
whatsoever
and the way to prove that is very simple
we simply need to show
that in basic or whatever we could write
a
an interpreter or a compiler for
whatever is
other programming language we care about
like c or
or java or whatever and as soon as we
had done that then ipso facto
anything that's expressible in c or java
is also expressible and basic
okay and so this idea of universality
you know goes back at least to alan
turing in the 1930s
when you know he uh uh um wrote down
this incredibly
simple pared down model of a computer
the touring machine
right which uh you know he pared down
the instruction set
to just read a symbol you know go to
write a symbol move to the left move to
the right
uh halt change your internal state right
that's it
okay and anybody proved that um
you know this could simulate all kinds
of other things
uh you know and so so in fact today we
would say
well we would call it a touring
universal model of computation
that is you know just as it has just the
same expressive power
that basic or uh java or c
plus plus or any of those other
languages have
uh because anything in those other
languages could be compiled down
to touring machine now touring also
proved a different related thing
which is that there is a single touring
machine
uh that can simulate any other touring
machine
if you uh uh just describe that other
machine on its tape
right and likewise there is a single
touring machine
that will run any c program you know if
you just put it on its tape
that's that that's a second meaning of
universality
first of all that he couldn't visualize
it and that was in the 30s
30s that's right before computers really
i mean um i don't know how i wonder
what that felt like uh you know learning
that there's no santa claus or something
uh
uh because i i don't know if that's
empowering or paralyzing
because it it doesn't uh give you any
ins it's uh
like you can't write a software
engineering book and make that
the first chapter and say we're done
well i mean i mean right i mean i mean
in one sense it was this enormous
flattening of the universe
yes right i had imagined that there was
going to be some infinite hierarchy
of more and more powerful programming
languages
you know and then i kicked myself for
you know for having such a stupid idea
but apparently girdle had had the same
conjecture in the 30s
and then you know you're in good company
well yeah and then and then and then
tori
and then girdle read toring's paper and
he kicked himself and he said yeah i was
completely wrong about that
okay but um but you know i had thought
that you know
maybe maybe where i can contribute will
be to invent a new more powerful
programming language
that lets you express things that could
never be expressed in basic
yeah right and you know and then you
know how would you do that obviously you
couldn't do it itself in basic
right but uh uh but you know there is
this incredible
flattening that happens once you learn
what is universality
but then it's also um uh like
um an opportunity because it means once
you know these rules
then you know the sky is the limit right
then you have kind of the same
weapons at your disposal that the
world's greatest programmer has
it's now all just a question of how you
wield them right
exactly but so every problem is
solvable but some problems are harder
than others
and well yeah there's the question of
how much time you know
well of how hard is it to write a
program and then there's also the
questions of
what resources does the program need you
know how much time how much memory
those are much more complicated
questions of course ones that we're
still struggling with today
exactly so you've uh i don't know if you
created complexity zoo or
i did create the complexity zoo what is
it what's complexity
oh all right all right complexity theory
is the study of
sort of the inherent resources needed to
solve
uh computational problems okay so uh uh
it's easiest to give an example uh like
uh let's say we want to um um add two
two numbers right if i want to add them
uh
um you know if the numbers are twice as
long then it only
it will take me twice as long to add
them but only twice as long
right it's no worse than that for a
computer or
or for a person we're using pencil and
paper for that matter if you have a good
algorithm
yeah that's right i mean even if you
just if you just use the elementary
school
algorithm of just carrying you know then
it it takes time that is linear in the
length of the numbers
right now multiplication if you use the
elementary school algorithm
is harder because you have to multiply
each digit of the first number by each
digit of the second one
yeah and then deal with all the carries
so that's what we call a quadratic time
algorithm right if um the numbers become
twice as long now you need four times as
much time
okay so now as it turns out we
uh people discovered much faster ways to
multiply numbers using computers
and today we know how to multiply two
numbers that are n digits long
using a number of steps that's nearly
linear in n
these are questions you can ask but now
let's think about a different thing that
people
uh you know they've encountered in
elementary school uh factoring a number
okay take a number and find its prime
factors
right and here you know if i give you a
number with 10 digits
i ask you for its prime factors well
maybe it's even so you know that two is
a factor
you know maybe it ends in zero so you
know that ten is a factor right but
you know other than a few obvious things
like that you know if
the prime factors are all very large
then it's not clear how you even get
started
right you know you it seems like you
have to do an exhaustive search
among an enormous number of factors now
um and and as many people might know uh
the uh for for for better or worse the
uh
security you know of most of the
encryption that we currently use to
protect the internet
is based on the belief and this is not a
theorem
it's a belief that uh that factoring is
an inherently hard problem
uh for our computers we do know
algorithms that are better than just
trial division and just trying all the
possible divisors uh but they are still
basically exponential exponential is
hard
yeah exactly so this so the the fastest
algorithms that anyone has discovered
at least publicly discovered you know
i'm assuming that the nsa doesn't know
something better
yeah okay but they they take time that
basically grows
exponentially with the cube root of the
size of the number that you're factoring
right so that cube root that's the part
that takes all the cleverness okay but
there's still an exponential
there's still an exponentiality there
but what that means is that like
when people use a thousand bit keys for
their cryptography
that can probably be broken using the
resources of the nsa
or the world's other intelligence
agencies you know people have done
analyses that say
you know with a few hundred million
dollars of computer power they could
totally do this
and if you look at the documents that
snowden released
you know it it it look it looks a lot
like they are doing that or something
like that
it would kind of be surprising if they
weren't okay but
you know if that's true then in in some
ways that's reassuring
because if that's the best that they can
do then that would say that they can't
break two thousand bit numbers
right exactly exactly right then two
thousand bit numbers would be
would be beyond what even they could do
they haven't found an efficient
algorithm that's where
all the worries and the concerns of
quantum computing came in that there's
some kind of shortcut around that right
so complexity theory
is a you know is is a huge part of let's
say the theoretical core of computer
science
you know it it started in the 60s and
70s
as you know sort of a you know
autonomous field so it was
you know already you know i mean you
know it was
well developed even by the time that i
was born
okay but uh um uh i in 2002 i made a
website called the complexities zoo
uh to answer your question uh where i
just tried to catalog
the different complexity classes which
are classes of problems that are
solvable with different kinds of
resources
right okay so these are kind of um you
know you could think of complexity
classes
as like being almost to to to
theoretical computer science like what
the elements are to chemistry
right they're sort of you know there are
our most basic
objects in in a certain way i feel like
the elements
have uh have a characteristic to them
where you can't just add
an infinite number well you could but
beyond a certain point they become
unstable
right right so it's like you know in
theory you can have atoms with
yeah and look look i mean i mean i mean
a neutron star you know is a nucleus
with you know
uncalled billions of of of of nuke of
of uh of of of of neutrons in it of of
hadrons in it okay but
uh um you know for for sort of normal
atoms right probably you can't get
much above 100 you know atomic weight
150 or so
or sorry sorry i mean i mean beyond 150
or so protons without it
you know very quickly fissioning uh with
complexity classes well yeah you
you can have an infinity of complexity
classes uh but you know maybe
there's only a finite number of them
that are particularly interesting
right just like with anything else you
know you uh
uh you care about some more than about
others so what kind of interesting
classes are there
yeah i mean you could have just maybe
say what are the
if you you take any kind of computer
science class what are the classes you
learn
good let me let me tell you sort of the
the the biggest ones the ones that you
would learn
first so you know first of all there is
p
that's what it's called okay it stands
for polynomial time
and this is just the class of all of the
problems
that you could solve with a conventional
computer
like your iphone or your laptop uh you
know by a completely deterministic
algorithm right using a number of steps
that grows only like the size of the
input
raised to some fixed power okay so
uh if your algorithm is linear time like
you know for adding numbers
okay that that problem is in p if you
have an algorithm that's quadratic time
like the uh elementary school algorithm
for multiplying two numbers that's also
in p
even if it was the size of the input to
the 10th power
or to the 50th power well that wouldn't
be very uh
good in practice but you know formally
we would still count that that would
still be in p
okay but if your algorithm takes
exponential time
meaning like if every time i add one
more
uh data point to your input if the
time that needed by the algorithm
doubles if you need time like
2 to the power of the amount of input
data
then uh that is that we call an
exponential time algorithm
okay and that is not polynomial okay so
p
is all of the problems that have some
polynomial time algorithm
okay so that includes most of what we do
with our computers on a day-to-day basis
you know
all the you know sorting basic
arithmetic
you know whatever is going on in your
email reader or in angry birds
okay it's all in p then the next uh
super important class
is called np uh that stands for
non-deterministic polynomial
okay does not stand for not polynomial
which is a
common confusion um but np was basically
all of the problems
where if there is a solution then it is
easy to check the solution
if someone shows it to you okay so
actually a perfect
example of a problem in np is uh
factoring the one i told you about
before like if i
gave you a number with thousands of
digits and i told you
that you know i i asked you does this
uh does this have at least um three
non-trivial divisors
right that might be a super hard problem
to solve right might take you millions
of years
using any algorithm that's known at
least running on our existing computers
okay but if i simply showed you the
divisors
i said here are three divisors of this
number
then it would be very easy for you to
ask your computer
to just check each one and see if it
works just divide it in
see if there's any remainder right and
if they all go in
then you've checked well i guess there
were right
so um so any problem
where you know wherever there's a
solution there is a short witness
that can be easily like a polynomial
size
witness that can be checked in
polynomial time
that we call an np problem okay
beautiful
and uh yeah so so every problem that's
in p
is also in np right because you know you
could always just
ignore the witness and just you know if
a problem is in p you can just solve it
yourself
right okay but now the influence is the
central
you know mystery of theoretical computer
science
is is every np problem in p so
if you can easily check the answer to a
a computational problem does that mean
that you can also easily find the answer
even though there's all these problems
that appear to
be very difficult to find the answer
it's still an open question whether
a good answer exists so what's yours no
one has proven that there's no way to do
it it's
arguably the most uh
i don't know the most famous the most
maybe interesting maybe disagree with
that
problem in theoretical computer science
so what's your most famous for sure
p equals np yeah if you were to bet all
your money
where do you put your money that's an
easy one p is not equal to np okay so i
like to say that if we were physicists
we would have just declared that to be a
law of nature
you know just like just like
thermodynamics it's hilarious
giving ourselves nobel prizes for its
discovery yeah you know and look
if later if later it turned out that we
were wrong we just give ourselves
more more nobel prizes yeah
i mean no i mean i mean i mean it's it's
really just because we are
mathematicians or descended from
mathematicians you know
we have to call things conjectures that
other people would just call empirical
facts or discoveries
right but one shouldn't read more into
the difference in in language
you know about the underlying truth so
okay so you're a good investor and good
spender money so then let me
i don't know that let me ask another way
is it possible at
all and what would that look like if p
indeed equals np well i do think that
it's possible i mean in fact you know
when people really pressed me on my blog
for what odds would i put
like well you know two or three percent
odds wow that's pretty good that p
equals np yeah just speak well um
because you know when p
i mean i mean you you really have to
think about like if there were
50 you know mysteries like p versus np
and if i made a guess about every single
one of them
would i expect to be right 50 times
right and the truthful answer is no
okay yeah so you know and and and and
and that's what you really mean in
saying that you know you have
you know better than 98 odds for
something
okay but um so so yeah you know i mean
there could certainly be surprises and
look if p
equals np well then there would be the
further question
of you know is the algorithm actually
efficient in practice
right i mean don knuth who i know that
you you've interviewed as well
right he uh likes to conjecture that p
equals np but that the algorithm is so
inefficient that it doesn't matter
anyway right now i i don't know i've
listened to him say that i don't know
whether he says that just because he has
an actual reason for thinking it's true
or just because it sounds cool
yeah okay but um but you know that
that's a logical possibility right that
the algorithm could be
n to the 10 000 time or it could even
just be n
squared time but with a leading constant
of a it could be a google times n
squared or something like that and in
that case the fact that p equals np
well it would it would uh you know
ravage the whole theory
of uh complexity we would have to you
know rebuild from the ground up
but in practical terms it might mean
very little right
if the algorithm was too inefficient to
run if the algorithm
could actually be run in practice like
if if it had small enough constants
you know to or if you could improve it
to where it had
small enough constants that it was uh
efficient in practice
then that would change the world okay
you think it would have like what kind
of impact
well okay i mean i mean here's an
example i mean you could well okay
just for starters you could break
basically all of the encryption that
people use to protect the internet first
you could you could break bitcoin and
every other cryptocurrency or you know
uh mine as much bitcoin as you wanted
right
uh you know become a you know become a a
super duper billionaire right and then
and then plot your next move
right okay that's just for starters
right right now your next move might be
something like
you know you now have like a
theoretically optimal way
to train any neural network to find
parameters for any neural network right
so you could now say like is there any
small neural network that generates the
entire content of wikipedia
right if you know and now the question
is not can you find it
the question has been reduced to does
that exist or not yes
if it does exist then the answer would
be yes you can find it
okay if if if you had this algorithm in
your hands
okay you could ask your computer you
know i mean i mean
p versus np is one of these seven
problems that carries this million
dollar prize from the clay foundation
you know if you solve it uh you know and
others are the riemann hypothesis
uh the punk array conjecture which was
solved although the solver turned down
the price
right and uh and and four others but
what i like to say
the way that we can see that p versus np
is the biggest of all of these questions
is that if you had this fast algorithm
then you could solve all seven of them
okay you just ask your computer you know
is there a short proof of the riemann
hypothesis
right you know that a machine could in a
language where a machine could verify it
and provided that such a proof exists
then your computer finds it
in a short amount of time without having
to do a brute force search
okay so i mean i mean those are the
stakes of what we're talking about
but i hope that also helps to give your
listeners some intuition
of why i and most of my colleagues would
put our money on p not equaling np
is it possible i apologize this is a
really dumb question but is it possible
to
that proof will come out that p equals
np
but an algorithm that makes p
equals np is impossible to find
um is that like crazy okay well well if
p equals np
it would mean that there is such an
algorithm that it exists yeah
but um um you know it would it would
mean that it exists
now you know in practice normally the
way that we
would prove anything like that would be
by finding the algorithm by finding that
one algorithm
but there is such a thing as a
non-constructive proof
that an algorithm exists you know this
is really only reared its head i think a
few times
in the history of our field right but
you know it is
it is theoretically possible that that
that
that such a thing could happen but you
know there are so even here there are
some amusing observations that one could
make
so there is this famous observation of
leonid levin
who is you know one of the original
discoverers of np completeness right and
he said
well consider the following algorithm
that like i i guarantee
we'll solve the np problems efficiently
just as provided that p
equals np okay here is what it does it
just
runs you know it enumerates every
possible algorithm
in a gigantic infinite list yeah right
from like in like alphabetical order
right
you know and many of them maybe won't
even compile so we just ignore those
okay but now
we just you know run the first algorithm
then we run the second algorithm we run
the first one a little bit
more then we run the first three
algorithms for a while we won the first
four for a while
this is called dovetailing by the way
this is a known trick
in um uh um theoretical computer science
okay but
we do it in such a way that you know
whatever is the algorithm
out there in in in our list that solves
np-complete you know the np problems
efficiently will eventually hit that one
right and now the key is that whenever
we hit that one
you know it you know by assumption it
has to solve the problem that's to find
the solution
and once it claims to find a solution
then we can check that ourself
right because these are increasing
problems then we can check it
now this is utterly impractical all
right you know you'd have to do this
enormous exhaustive search among all the
algorithms
but from a certain theoretical
standpoint that is merely a constant
prefactor
that's merely a multiplier of your
running time so there are tricks like
that one can do to say that
in some sense the algorithm would have
to be uh constructive
but you know in in in the human sense
you know it is possible that
you know it's conceivable that one could
prove such a thing uh via a
non-constructive method is is that
likely i don't think so first no no
no not personally so that's p and and p
but the complexities it was full of
wonderful creatures well it's got about
500 of them 500.
so how do you get uh yeah
yeah how do you get more how do you yeah
well yeah well okay i mean i mean
i mean just for starters there is
everything that we could do
with a conventional computer with a
polynomial amount of memory
okay but possibly an exponential amount
of time because we get to reuse the same
memory over and over again
okay that is called p space okay and
that's actually a
uh we think an even larger class than np
okay well p is contained in np which is
contained in p space
and we think that those containments are
strict and
the constraint there is on the memory
the memory has to grow
polynomially with the size of the
product that's right that's right but in
p space
we now have interesting things that were
not in in np
like uh as a famous example you know
from a given position
in chess you know does white or black
have the win
let's say assuming provided that the
game lasts only for a
a reasonable number of moves okay or or
or likewise for go okay and
you know even for the generalizations of
these games to arbitrary
size boards because with an eight by
eight board you could say that's just a
constant size problem you just
you know in principle you just solve it
in o of one time right but
so we really mean the uh the
generalizations of
you know games to uh arbitrary size
boards here
or um another thing in p space would be
uh
like i give you some really hard um
constraint satisfaction problem
like you know a you know traveling
person
or you know packing boxes into the trunk
of your car or something like that
and i asked not just is there a solution
which would be an np problem
but i ask how many solutions are there
okay
that you know count the number of of
solu of valid solutions
that that that actually gives those
problems lie in a complexity class
called
sharp p or like it looks like hashtag
like hashtag p you got it okay which
sits between
np and p space um there's all the
problems that you can do in exponential
time
okay that's called x so um
and by the way uh it it was proven in
the 60s
that x is larger than p okay so we know
that much
we know that there are problems that are
solvable in exponential time
that are not solvable in polynomial time
okay
in fact we even know more we know that
there are problems that are solvable in
n cube time that are not solvable in n
squared time
and that those don't help us with a
controversy between p and m
unfortunately it seems not or certainly
not yet
right the the the techniques that we use
to establish those things
they're very very related to how touring
proved the unsolvability of the halting
problem
but they seem to break down when we're
comparing two different
resources like time versus space
or like you know p versus np okay but
you know i mean there's there's what you
can do with a randomized algorithm
right that can sometimes you know with
some has some probability of making a
mistake
that's called bpp bounded our
probabilistic polynomial time
and then of course there's one that's
very close to my own heart
what you can efficiently do during
polynomial time
using a quantum computer okay and that's
called bqp
right and so you know what's understood
about that class
okay so p is contained in bpp
which is contained in bqp which is
contained in p
space okay so anything you can in fact
in in like
in something very similar to sharp p bqp
is basically
you know well it's contained in like p
with the magic power to solve sharp p
problems okay why why is bqp
contained in uh p space oh that's an
excellent question
uh so uh there there is um
well i mean one one has to prove that
okay but uh
the proof um uh you could you could
think of it
as uh using uh richard feynman's picture
of quantum mechanics
which is that you can always you know we
haven't really talked about uh
quantum mechanics in this in this
conversation we we did in our previous
yeah
yeah we did last time but yeah we did
last time okay but uh
uh but basically you could always think
of a quantum computation
as uh like a branching tree of
possibilities
where each pos each possible path that
you could take
through you know your the space has a
complex number attached
to it called an amplitude okay and now
the rule is you know when you make a
measurement at the end
well you see a random answer okay but
quantum mechanics is all about
calculating the probability that you're
going to see one potential answer versus
another one
right and the rule for calculating the
probability that you'll see some answer
is that you have to add up the
amplitudes for all of the paths that
could have led to that answer
and then you know that's a complex
number so that you know
how could that be a probability then you
take the squared absolute value of the
result
that gives you a number between zero and
one okay
so um yeah i just i just summarized
quantum mechanics in like 30 seconds
okay but uh but now you know what what
this
already tells us is that anything i can
do with a quantum computer
i could simulate with a classical
computer if i
only have exponentially more time okay
and why
is that because if i have exponential
time
i could just write down this entire
branching tree
and just explicitly calculate each of
these amplitudes
right you know that will be very
inefficient but it will work
right it's enough to show that quantum
computers could not
solve the halting problem or you know
they could never do anything that is
literally
uncomputable in touring sense okay but
now
as i said there is even a stronger
result which says that bqp
is contained in p space the way that we
prove that
is that we say if if all i want is to
calculate
the probability of some particular
output happening
we know which is all i need to simulate
a quantum computer really
then i don't need to write down the
entire quantum state
which is an exponentially large object
all i need to do
is just calculate what is the amplitude
for that final state
and to do that i just have to sum up
all the amplitudes that lead to that
state okay so that's an exponentially
large sum
but i can calculate it just reusing the
same memory over and over
for each term in the song hence the p in
the pieces
yeah yeah so what uh
out of that whole complexity zoo and it
could be bqp what do you find is the
most uh
uh the class that captured your heart
the most
is the most beautiful class there's just
yeah
i i used uh as my email address uh
bqpqpali gmail.com
yes because uh bqp slash q poly
well you know amazingly no one had taken
it amazing
but you know but th this is a class that
i was involved in sort of uh
defining proving the first theorems
about uh in 2003 or so
so it was kind of close to my heart but
this is like if we extended
um bqp which is the class of everything
we can do efficiently with a quantum
computer
uh to allow quantum advice which means
imagine that you had some special
initial state
okay that could somehow help you do
computation and maybe
um such a state would be exponentially
hard to prepare
okay but you know maybe somehow these
states were formed in the big bang or
something and they've just been sitting
around ever since right if you found one
and if this state could be like ultra
power
there are no limits on how powerful it
could be
except that this state doesn't know in
advance which
input you've got right it only knows the
size of your input
you know and then that that's bqp slash
q probably
so that's that's one that i just
personally happen to love
okay but um you know if you're asking
like what's the
you know there's there's there's a class
that i think is is
is way more beautiful than you know or
fundamental
that a lot of people even within uh this
this field realize that it is
that class is called sck or statistical
zero knowledge
um and you know there's a very very easy
way to define this class which is to say
suppose that i have two algorithms that
each sample from probability
distributions
right so each one just outputs random
samples
according to you know possibly different
distributions
and now the question i ask is you know
you know let's say distributions over
strings of n bits
yeah so over an exponentially large
space now i ask
are these two distributions close or far
as probability distributions okay any
problem that can be reduced to that
you know that can be put into that form
is an sdk
problem and the way that this class was
originally discovered was completely
different from that
and was kind of more complicated it was
discovered as the class of all of the
problems
that have a certain kind of what's
called zero knowledge proof
zero knowledge proofs are one of the
central ideas in cryptography
um you know shafi goldwasser and silvio
mccauley won the touring award
for you know inventing them and they're
at the core of even some some
cryptocurrencies that you know
people people use nowadays but
um there are zero knowledge proofs or
ways of proving to someone that
something is true
like you know that there is a a solution
to this
you know uh optimization problem or that
these two graphs are
isomorphic to each other or something
but without revealing why it's true
without revealing anything about why
it's true
okay sdk is all of the problems
for which there is such a proof uh that
doesn't rely on any cryptography
okay and if if you wonder like how could
such a thing possibly exist
right well like imagine that i had two
graphs and i wanted to convince you that
these two graphs are not
isomorphic meaning you know i cannot
permute one of them so that it's the
same as the other one
right you know that might be a very hard
statement to prove like i might
you know you might have to do a very
exhaustive enumeration of you know all
the different
permutations before you were convinced
that it was true but what if there were
some
all-knowing wizard that said to you look
i'll tell you what
just pick one of the graphs randomly
then randomly permute it
then send it to me and i will tell you
which graph you started with
okay and i will do that every single
time
right and load that in
and let's say that that wizard did that
a hundred times and it was right every
time yeah right
now if the graphs were isomorphic then
you know it would have been flipping a
coin each time
right it would have had only a one in
two to the 100
power chance of you know of guessing
right each time
but you know so so if it's right every
time then now you're statistically
convinced that these graphs are not
isomorphic
even though you've learned nothing new
about why they aren't so fascinating so
yeah so so
sdk is all of the problems that have
protocols like that one
but it has this beautiful other
characterization it's shown up again and
again
in my in my own work in you know a lot
of people's work
and i think that it really is one of the
most fundamental classes
it's just that people didn't realize
that when it was first discovered
so we're living in the middle of a
pandemic currently yeah how has
your life been changed or no better to
ask like how is your perspective of the
world change
with this uh world-changing event of a
pandemic overtaking the entire world
yeah well i mean i mean all of our lives
have changed you know like
i guess as with no other event since i
was born you know you would have to go
back to world war
ii for something i think of this
magnitude you know uh
on you know the way that we live our
lives as for how it has changed my world
view i think that the the failure of
institutions
you know like uh like like the cdc
like you know other institutions that we
sort of thought were were
trustworthy like a lot of the media uh
was
uh staggering was was absolutely
breathtaking
uh it is something that i would not have
predicted right i think i
i uh wrote on my blog uh uh that you
know
you know it it's it's abs it's
fascinating to like re-watch the movie
uh contagion
from a decade ago right that correctly
foresaw
so many aspects of you know what was
going on
you know a uh an airborne you know virus
originates in china
spreads to you know much of the world
you know shuts everything down
until a vaccine can be developed uh you
know everyone has to stay at home you
know
you know it gets uh um you know an
enormous number of things right
okay but the one thing that they could
not imagine you know is that like
in this movie everyone from the
government is like
hyper comp competent hyper you know
dedicated to the public good
right best of the best you know yeah the
they're the best of the best
you know they could you know and there
are these conspiracy theorists
right who uh think you know you know
this is all fake news there's no there's
not really a pandemic
and those are some random people on the
internet who the hyper competent
government people have to you know
oppose right
they you know in in trying to envision
the worst thing that could happen
like you know the the there was a
failure of imagination the movie makers
did not imagine
that the conspiracy theorists and the
you know
and the incompetence and the nut cases
would have captured
our institutions and be the ones
actually running things
so you had a certain yeah i i love
competence
in all walks of life i love i get so
much energy i'm so excited but people do
amazing job and i like you
uh well maybe you can clarify but i had
maybe not an intuition but i hope that
government at his best could be ultra
com
competent what uh first of all
two questions like how do you explain
the lack of confidence
and the other maybe on the positive side
how can we build a more competent
government
well there's an election in two months i
mean you know
you have a faith that the election i uh
you know it's not gonna fix
everything but you know it's like i feel
like there is a ship that is sinking and
you could at least stop the sinking
but uh uh you know i think that there
are there are much much deeper problems
i mean i think that
uh um you know it is it is plausible to
me
that you know a lot of the the failures
you know with the cdc
with uh some of the other health
agencies even you know
you know pre-date trump you know
pre-date the you know right-wing
populism that has sort of
taken over much of the world now and
um you know i think that uh uh
you know it was is you know it is very
i'm actually
you know i've actually been strongly in
favor of
you know rushing vaccines of uh uh
you know i thought that we could have
done you know human
human challenge trials you know which
were not done
right we could have you know like i had
you know volunteers
you know to uh uh actually you know be
you know uh get vaccines get you know
exposed to covid so you know
innovative ways of accelerating what
you've done previously over a long
time i thought that you know each each
month that you that that a vaccine is
is closer is like trillions of dollars
are used for civilization
and of course lives you know at least
you know hundreds of thousands of lives
are you surprised that it's taking this
long we still don't have a plan there's
still
not a feeling like anyone is actually
doing anything in terms of uh
elite alleviating like any kind of plan
so there's a bunch of stuff this vaccine
but you could also do
a testing infrastructure where yeah
everybody's tested non-stop with contact
tracing all that kind of well i mean i
i'm as surprised as almost everyone else
i mean this is a
historic failure it is one of the
biggest failures in the 240 year history
of the united states
right and we should be you know crystal
clear about that
and you know one thing that i think has
been missing you know even
even from the more competent side is
like you know is sort of the
the world war ii mentality right the
you know the mentality of you know let's
just
you know you know if if if we can by
breaking a whole bunch of rules
you know get a vaccine and you know and
even
half the amount of time as we thought
then let's just do that
because uh you know you know like like
we have to we have to weigh
all of the moral qualms that we have
about doing that
against the moral qualms of not doing
and one key
little aspect yeah that's deeply
important to me and going that topic
next is uh the world war ii mentality
wasn't just about
you know breaking all the rules to get
the job done there was a togetherness to
it
there's yes so i would if i were
president right now it seems quite
elementary
to unite the country because we're
facing a crisis
it's easy to make the virus the enemy
and it's very surprising to me
that um the div the division has
increased as opposed to decreasing yeah
so
that that's that's heartbreaking yeah
well look i mean it's been said by
others that this is the first time
in the country's history that we have a
president who does not even pretend
to you know what want to unite the
country right
yeah and you know i mean i mean i mean
lincoln who fought a civil war
you know you know said he wanted to
unite the country
right uh you know and and and i i do
i do worry enormously about what happens
if the results of this election are
contested you know
and you know will there be violence as a
result of that
and will we have a clear path of
succession
and you know look i mean you know this
is all we're going to find out the
answers to this in
two months and if none of that happens
maybe i'll look foolish but i am willing
to go on the record and say
i am terrified about that yeah i've been
reading the the rise and fall of the
third reich this is
it so if i can this this is like one
little voice
to put out there that i think november
will be a really critical month
for people to breathe and put
love out there do not you know
anger in those in that context no matter
who wins no matter what is said
will destroy our country may destroy our
country it may destroy the world because
of the power of the country
so it's really important to be patient
loving empathetic
like one of the things that troubles me
is that even people on the left
are unable to have a love and respect
for people who voted for trump they
can't imagine
that there's good people that could vote
for the opposite side and that's
oh i know there are because i know some
of them yeah right i mean you know it's
still
you know maybe it baffles me but you
know i i know such people
let me ask you this it's also
heartbreaking to me
on the topic of cancer culture yeah so
in the machine learning community i've
seen it a little bit
that there's um aggressive
attacking of people who are trying to
have a nuanced conversation about things
and it's troubling because it feels like
nuanced conversation is the only way to
talk about difficult topics
and when there's a thought police and
speech police
on any nuanced conversation that
everybody has to like in
animal farm chant that racism is bad and
sexism is bad which is
things that everybody believes and
they're they can't possibly say anything
nuance
it feels like it goes against any kind
of progress
from my kind of shallow perspective but
you've written a little bit about
cancer culture did you have thoughts
that are well
i mean i mean i mean to say that i am
opposed to
you know the this trend of of
cancellations or of you know shouting
people down rather
than engaging them that would be a
massive understatement
right and i feel like you know i have
put my money where my mouth is you know
not as much as some people have
but you know i i've tried to do
something i mean i have
defended you know uh some unpopular
people
and unpopular you know ideas on my blog
i've you know tried to defend you know
norms of uh
of uh of of open discourse of you know
reasoning with our opponents even when
i've been shouted down for that
on social media uh you know called a
racist called a sexist
all of those things and which by the way
i should say you know i would be
perfectly happy to you know say you know
if we had time to say you know
you know ten thousand times you know my
uh hatred of
racism of sexism of homophobia
right but what i don't want to do is to
cede to uh some particular political
faction the right to define
exactly what is meant by those terms to
say well then
you have to agree with all of these
other extremely contentious
positions or else you are a misogynist
or else you are a racist
right i say that well no you know you
know don't
like don't i or you know
don't people like me also get a say in
the discussion
about you know what is racism about what
is going to be the most effective to
combat racism
right and you know this this this um
cancellation mentality i think is
spectacularly ineffective
at its own professed goal of you know
combating racism and sexism
what's a positive way out so i i try to
i don't know if you see what i do on
twitter but i on twitter i mostly and in
my whole in my life
i've actually it's who i am to the core
is like i really focus on the positive
and i try to put love out there in the
world yeah and still
i get attacked and i look at that and i
wonder like are you two
i didn't know like i haven't actually
said anything difficult
and nuanced you talk about somebody like
steven pinker
yeah who i actually don't know the full
range of
things that um that he's attacked for
but
he tries to say difficult he tries to be
thoughtful about
difficult topics he does and obviously
he just gets
slaughtered by well i mean i mean i mean
i mean yes but it's also amazing how
well steve has withstood it i mean he
just survived that attempt to cancel him
just a couple of months ago right
psychologically he survives it too which
yeah worries me he says i don't think i
can yeah i i've gotten to know steve a
bit
he is incredibly unperturbed by this
stuff uh i i admire that and i envy it
i wish that i could be like that i mean
my impulse when i'm getting attacked is
i just want to engage
every single like anonymous person on
twitter
and reddit who is saying mean stuff
about me and i wanted to say well look
can we just talk this over for an hour
and then you know
you'll see that i'm not that bad and you
know sometimes that even works the
problem is then there's the you know the
20 000 other ones
right that's not but psychologically
does that wear on you
it does it does but yeah i mean in terms
of what is the solution i mean i wish i
knew
right and so you know in a certain way
these problems are
maybe harder than p versus np right i
mean
uh you know but but i think that part of
it has to be for you know that
i think that there's a lot of sort of
silent support
for what i'll call the the the open
discourse side the you know reasonable
enlightenment side
and i think that that that support has
to become less silent
right i think that a lot of people uh
this sort of you know
like agree that oh you know a lot of
these cancellations and attacks are
ridiculous
but are just afraid to say so right or
else they'll get they'll get shouted
down as well
right that's just the standard witch
hunt dynamic which you know of course
this
uh you know this faction understands and
exploits to its great advantage
but um you know if more people just
you know said you know like we're not
going to stand for this
right uh uh you know you know this is
this is you know
where guess what we're against racism
too but you know
this you know what you're doing is
ridiculous right
um you know and the hard part is like it
takes a lot of mental energy it takes a
lot of time
you know even if you feel like you're
not going to be cancelled or you know
you're staying on the safe side
like it takes a lot of time to uh to to
phrase
things in exactly the right way and to
uh you know respond to everything people
say so
but i think that um you know the more
people speak up than uh
uh you know from from from all political
persuasions you know from like
all you know walks of life then you know
the the easier it is to move forward
since we've been talking about love can
you um
last time i talked to you about meaning
of life a little bit but
here has it's a weird question to ask a
computer scientist but
has love for other human beings for
for things for the world around you
played an important role in your life
have you um
you know it's easy for a world-class
computer scientist uh
uh yeah you could even call yourself
like a physicist
everything to be lost in the books is
the connection to other humans
love for other humans played an
important role i love my kids
uh i love my wife i love my parents
um uh you know i
um i'm probably not not different from
most people and loving their families
uh and and in that being very important
uh
in my life uh now i should remind you
that you know i am a theoretical
computer scientist
if you're looking for deep insight about
the nature of love you're probably
looking in the wrong place
to ask me but uh but sure it's been
important
but is it uh is there something from a
computer science perspective to be said
about love is there uh
or is that is that even beyond into the
realm of beyond
the realm of consciousness there was
there was this great uh
cartoon i think it was one of the
classic xkcds where it shows like a
heart
and it's like you know squaring the
heart taking the four-year transform of
the heart
you know integrating the heart you know
uh uh
you know each each thing and then it
says you know my normal approach is
useless here
i'm so glad i asked this question i
think there's no better way to uh
to end this guy i hope we get a chance
to talk again this has been an amazing
cool experiment to do it outside yeah
really glad you made it out yeah well i
appreciate it a lot it's been a pleasure
and i'm glad you were able to come out
to austin uh thanks
thanks for listening to this
conversation with scott erinson and
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at lex friedman and now let me leave you
with some words from scott ericson
that i also gave to you in the
introduction which is
if you always win then you're probably
doing something
wrong thank you for listening and for
putting up with the
intro and outro in this strange room in
the middle of nowhere
and i very much hope to see you next
time
in many more ways than one
you