Do LLMs Understand? AI Pioneer Yann LeCun Spars with DeepMind’s Adam Brown. - part 6/15
2025-12-12_17-05 • 1h 15m 39s
Adam Brown (Research Scientist)
00:00.120
Are
you
describing
understanding
as
a
behavioral
trait
here
where
it
gives
the
right
answers
to
problems
or
whether
it
deeply
at
the
neural
level
understands?
Yeah,
Janna Levin (Professor of Physics and Astronomy)
00:08.200
I'm
I'm
I'm
completely
at
the
whims
of
the
philosophers
here.
No,
I
I
don't
know
if
I
understand
that
at
my
at
the
human
level,
right?
I
can't
tell
you
what
process
I'm
executing
at
the
moment
either,
right?
But
I'd
have
some
intuitive,
subjective
experience
that
I
understand
Janna Levin (Professor of Physics and Astronomy)
00:23.860
the
conversation.
Obviously,
not
that
well.
Um
Janna Levin (Professor of Physics and Astronomy)
00:27.540
but
but
uh
I
when
I'm
talking
to
you,
I
feel
you
are
understanding.
And
uh
when
I'm
talking
to
ChatGPT,
I
do
not.
And
you're
telling
me
I'm
mistaken.
It's
understanding
as
well
as
I
am
or
Adam Brown (Research Scientist)
00:42.060
you
are.
In
my
opinion,
it
is
understanding,
yes.
And
I
think
there's
two
different
pieces
of
evidence
for
that.
One
is
I
think
if
you
talk
to
them,
like
If
you
talk
to
them
and
ask
them
about
difficult
concepts,
I'm
frequently
surprised
and
with
every
passing
month
and
every
Adam Brown (Research Scientist)
01:00.340
new
model
that
comes
out,
I
am
more
and
more
surprised
at
the
level
of
sophistication
with
which
they're
able
to
discuss
things.
Adam Brown (Research Scientist)
01:08.140
And
so
just
just
at
that
level,
it's
it's
super
impressive.
I
would
I
would
really
encourage
everybody
here
um
to
talk
to
these
large
language
models
if
you've
not
already,
you
know,
when
the
science
fiction
writers
imagine
imagined
that
we
built
some
sort
of
touring
test
Adam Brown (Research Scientist)
01:23.820
passing
uh
machine
that
that
was
gonna
you
know
some
new
alien
intelligence
that
we'd
have
in
a
box.
Uh
they
all
imagine
that
we
sort
of
hide
it
in
a
basement
you
know
in
a
castle
surrounded
by
a
moat
with
armed
guards
and
we'd
only
have
like
a
priestly
class
who
could
be
able
Adam Brown (Research Scientist)
01:39.660
to
go
and
and
talk
to
it.
Adam Brown (Research Scientist)
01:41.420
Uh
that
is
not
not
as
not
the
way
it
worked
out.
The
way
it's
worked
out
is
the
first
thing
we
did
is
we
immediately
hooked
it
up
to
the
internet.
And
now
anybody
can
go
talk
to
it.
And
uh
I
would
highly
encourage
you
to
to
talk
to
these
things
and
explore
in
areas
that
you
know
Adam Brown (Research Scientist)
01:55.140
to
see
both
their
limitations
but
also
their
strength
and
their
their
depth
of
understanding.
Adam Brown (Research Scientist)
01:59.060
So
I'd
say
that's
the
first
piece
of
evidence.
The
second
piece
of
evidence
is
you
said
they're
a
black
box,
they're
not
exactly
a
black
box.
We
do
have
access
to
their
neurons.
In
fact,
we
have
a
much
better
access
to
the
neurons
of
these
things
than
we
do
with
a
human.
Adam Brown (Research Scientist)
02:11.340
It's
very
hard
to
get
IRB
approval
to
slice
up
a
human
while
they're
doing
a
math
test
and
see
how
their
neurons
are
firing.
And
if
you
do
do
that,
you
can
only
do
that
once
on
a
human
basis.
Whereas
these
neural
networks,
we
can
freeze
them,
replay
them,
write
down
everything
Adam Brown (Research Scientist)
02:26.700
that
happened.
Adam Brown (Research Scientist)
02:27.940
If
we're
curious,
we
can
go
and
prod
their
neurons
in
certain
ways
and
see
what
happened.
And
so
this
is
it's
still
rudimentary,
but
this
is
the
field
of
interpretability,
mechanistic
interpretability,
trying
to
understand
not
just
what
they
say,
but
why
they
say
it,
how
they
Adam Brown (Research Scientist)
02:41.980
think
Adam Brown (Research Scientist)
02:42.220
it.
And
when
you
do
that,
we
see
uh
when
you
feed
them
a
math
problem
problem,
there's
a
little
bit
of
a
a
circuit
there
that
computes
the
answer.
that
that
we
didn't
program
it
to
have
that.
It
learnt
how
to
do
that.
While
trying
to
predict
the
next
token
on
all
of
this
text,
Adam Brown (Research Scientist)
02:58.300
it
learnt
that
in
order
to
most
accurately
predict
the
next
the
next
word,
I
should
say,
in
order
to
most
accurately
predict
the
next
word,
it
needed
to
figure
out
uh
how
to
do
maths
and
it
needed
to
build
a
sort
of
proto-little
circuit
inside
it
to
do
the
mathematical
Adam Brown (Research Scientist)
03:11.460
computations.
Janna Levin (Professor of Physics and Astronomy)
03:13.260
Now,
Yann,
you
famously
through
a
slide
up
at
one
of
your
uh
keynote
lectures,
that
was
very
provocative.
Um
Um,
very
scholarly.
It
said,
um,
machine
learning
sucks,
I
believe
was
it.
And
then
that
kind
of
went
wild.
Jan
L.
Kuhn
says,
"Machine
learning
sucks."
Um,
why
are
you
Janna Levin (Professor of Physics and Astronomy)
03:31.740
saying
machine
learning
sucks?
Adam
has
just
told
us
how
phenomenal
it
is.
He
talks
to
them
and
wants
us
to
do
the
same.
Um,
why
do
you
think
it
sucks?
What's
the
problem?
Yann LeCun (Chief AI Scientist)
03:43.500
Well,
that
statement
has
been
wildly
misinterpreted,
but
the
point
the
point
I
was
making
is
It's
the
point
that
we
both
we
both
made
which
is
that
why
is
it
that
a
teenager
can
learn
to
drive
a
car
in
20
hours
of
practice.
A
10-year-old
can
clean
up
the
dinner
table
and
fill
up
Yann LeCun (Chief AI Scientist)
04:05.580
the
dishwasher
the
first
time
you
ask
the
child
to
do
it
whether
the
10-year-old
will
want
to
do
it
is
a
different
story
but
you
know
certainly
can.
Yann LeCun (Chief AI Scientist)
04:15.580
We
don't
have
robots
that
are
anywhere
near
this
and
we
don't
have
robots
that
are
even
anywhere
near
the
you
know
physical
understanding
of
of
reality
of
of
a
cat
or
a
dog.
And
so
in
that
sense
machine
learning
sucks.
It
doesn't
mean
that
the
the
deep
learning
method,
the
back
Yann LeCun (Chief AI Scientist)
04:32.700
propagation
algorithm,
the
neural
nets
suck.
Yann LeCun (Chief AI Scientist)
04:35.660
That
was
obviously
excellent.
Yes.
Obviously,
that's
great.
And
we
don't
have
any
alternative
to
this.
And
uh
I
I
certainly
believe
that
you
know
neural
nets
and
deep
learning
and
back
propagation
would
be
you
know
are
with
us
for
for
a
long
time
will
be
the
basis
of
future
AI
Yann LeCun (Chief AI Scientist)
04:54.300
systems.
Yann LeCun (Chief AI Scientist)
04:55.340
But
But
how
is
it
that
you
know
young
humans
can
can
learn
how
the
world
works
in
the
first
few
months
of
life?
It
takes
nine
months
for
human
babies
to
learn
intuitive
physics
like
gravity,
inertia,
and
things
like
this.
Baby
animals
learn
this
much
faster.
They
have
smaller
Yann LeCun (Chief AI Scientist)
05:12.660
brains
so
it's
easier
for
them
to
learn.