Kind: captions
Language: en
talk about this you've written about it
you thought about it nature versus
nurture
so what innate knowledge do you think
we're born with and what do we learn
along the way in those early months and
years can I just say how much I liked
that question
you phrased it just right and almost
nobody ever does which is what is the
innate knowledge and what's learned
along the way so many people that Cottam
eyes it and they think it's nature
versus nurture when it is obviously has
to be nature and nurture they have to
work together you can't learn the stuff
along the way unless you have some I
need stuff but just because you have the
innate stuff doesn't mean you don't
learn anything and so many people get
that wrong including in the field like
people think if I work in machine
learning the learning side I must not be
allowed to work on the innate side what
is Cheney cheating exactly people who
said that to me and this is just absurd
so thank you but you know you could
break that apart more I've talked to
folks who study the development of the
brain and I mean the growth of the brain
in the first few days in the first few
months in the womb all of that you know
is that innate so that process of
development from a stem cell to the
growth of the the central nervous system
and so on to the the information that's
encoded through the long arc of
evolution so all of that comes into play
and is unclear it's not just whether
it's a dichotomy or not it's it's a
where most or where the knowledge is
encoded so what's your intuition about
the innate knowledge the power of it
what's contained in it what can we learn
from it one of my earlier books was
actually trying to understand the
biology of this the book was called the
birth of the mind like how is it the
genes even build a neat knowledge and
from the perspective of the conversation
we're having today there's actually two
questions one is what innate knowledge
or mechanisms or what have you people or
other animals might be endowed with I
always like showing this video of a baby
ibex climbing down a mountain that baby
ibex you know few hours after its birth
knows how to climb down a mountain that
means that it knows not consciously
something about its own body and physics
and and 3d geometry and all of this kind
of stuff
so there's one question about like what
is biology give its creatures you know
what it would has evolved in our brains
how is that represented in our brains
the question I thought about in the book
the birth of the mind and then there's a
question of what AI should have and they
don't have to be the same but I would
say that you know it's a pretty
interesting set of things that we are
equipped with it allows us to do a lot
of interesting things so I would argue
or guess based on my reading of the
developmental psychology literature
which I've also participated in
that children are born with a notion of
space time other agents places
and also this kind of mental algebra
that I was describing before no certain
of causation if I didn't just say that
so at least those kinds of things
they're they're like frameworks for
learning the other thing so are they
disjoint in your viewers is just somehow
all connected you've talked a lot about
language is it is it all kind of
connected as some mesh that's language
like if understanding concepts
altogether or I don't think we know for
people how they're represented and
machines just don't really do this yet
so I think it's an interesting open
question both for science and for
engineering some of it has to be at
least interrelated in the way that like
the interfaces of a software package
have to be able to talk to one another
so you know the the the systems that
represent space and time can't be
totally disjoint because a lot of the
things that we reason about our
relations between space and time and
cause so you know I put this on and I
have expectations about what's gonna
happen with the bottle cap on on top of
the bottle and those spans space and
time you know if the cap is over here I
get a different outcome if the timing is
different if I put this here after I
move that and you know I get a different
outcome that relates to causality so
obviously these mechanisms whatever they
are can certainly communicate with each
other so I think evolution had a
significant role to play in that
development this whole Cluj right how
efficient do you think is evolution oh
it's terribly inefficient
except that okay well can we do better
let's come down and say sure it's
inefficient except that once it gets a
good idea it runs with it so it took I
guess a billion years if I've been
roughly a billion years
to evolve to a vertebrate brain plan and
once that vertebrate playing plan
evolved it spread everywhere so fish
have it and dogs have other we have it
we have adaptations of it in
specializations of it but and the same
thing with a primate brain plan so
monkeys have a-- then apes have it and
we have it so you know their additional
innovations like color vision and those
spread really rapidly so takes evolution
a long time they get a good idea but in
the you know being anthropomorphic and
not literal here but once it has that
idea is that so to speak which caches
out into once a set of genes or in the
genome those genes spread very rapidly
and they're like subroutines or
libraries I guess the word people might
use nowadays or be more familiar with
their libraries they can get used over
and over again yeah so once you have a
library for building something with
multiple digits you can use it for a
hand but you can also use it for a foot
you just kind of reuse the library with
slightly different parameters evolution
does a lot of that which means that the
speed over time picks up so evolution
can happen faster because you have
bigger and bigger libraries and what I
think has happened in attempts at
evolutionary computation is that people
start with libraries that are very very
minimal like almost nothing and then you
know progress is slow and it's hard for
someone to get a good PhD thesis out of
it and they give up if we had richer
libraries to begin with if you were
evolving from systems that had in a rich
innate structure to begin with then
things might speed up or more PhD
students if the evolutionary process is
indeed in a meta way runs away with good
ideas you need to have a lot of ideas
pool of ideas in order for it to
discover one that you can run away with
and PG students representing individual
ideas as well yeah I mean you could
throw a billion PhD students at ya the
monkeys at typewriters with Shakespeare
yeah we'll see I mean those aren't
cumulative right that's just random and
the part of the point that I'm making is
that evolution is cumulative so if you
have a billion the monkeys independently
you know
get anywhere but if you have a billion
monk you said I think Dawkins made at
this point originally or probably other
people who Dawkins made it very nice and
either a selfish gene or blind
watchmaker if there is some sort of
fitness function it can drive you
towards something
I guess that's Dawkins point in my point
which is a variation on that is that if
the evolution is cumulative I mean
they're related points then you can
start going faster do you think
something like the process of evolution
is required to build intelligent systems
so if we don't logically so all the
stuff that evolution did a good engineer
might be able to do so for example
evolution made quadrupeds which
distribute the load across a horizontal
surface a good engineer come up with
that idea
I mean sometimes good engineers come up
with ideas by looking at biology there's
lots of ways to to get your ideas
part of what I'm suggesting is we should
look at biology a lot more we should
look at the biology of thought and
understanding and here the biology by
which creature is intuitively reason
about physics or other agents or like
how do dogs reason about people like
they're actually pretty good at it if we
could understand we my college we joked
dognition if we could understand
dognition well and how it was
implemented that might help us with our
I I so do you think do you think it's
possible that the kind of timescale that
evolution took is the kind of time scale
that we needed to build intelligent
systems or can we significantly
accelerate that process inside a
computer
I mean I think the way that we
accelerate that process is we borrow
from biology not slavish ly but I think
we look at by how biology is solve
problems and we say does that inspire
any engineering solutions here try to
mimic biological systems and then
therefore have a shortcut yeah I mean
there's a field called biomimicry and
people do that for like material science
all the time we should be doing the
analog of that for AI and the analog for
that fray I is to look at cognitive
science or the cognitive sciences which
is psychology
maybe neuroscience linguistics and so
forth look to those for insight
you