Do LLMs Understand? AI Pioneer Yann LeCun Spars with DeepMind’s Adam Brown. - part 7/15
2025-12-12_17-05 • 1h 15m 39s
Yann LeCun (Chief AI Scientist)
00:01.100
They
don't
learn
to
the
same
level
but
they
but
they
do
learn
faster.
And
And
so
this
type
of
learning
that
we
need
to
reproduce.
Um,
we'll
do
this
with
back
prop
with
neural
net
with
deep
learning.
It's
just
that
we're
missing
a
concept,
an
architecture.
Um,
so
I've
been
I've
Yann LeCun (Chief AI Scientist)
00:16.460
been
making
proposals
for
the
type
of
architectures
that
could
possibly
uh
learn
this
kind
of
stuff.
Yann LeCun (Chief AI Scientist)
00:22.720
You
know,
why
is
it
that
LLM's
handle
language
so
easily?
It's
because
um
as
Adam
described,
you
you
train
an
LLM
to
predict
the
next
word
or
the
next
token,
doesn't
matter.
There's
only
a
finite
number
of
words
in
the
dictionary.
So,
you
can
never
actually
predict
exactly
which
Yann LeCun (Chief AI Scientist)
00:42.640
word
comes
after
a
sequence,
but
Yann LeCun (Chief AI Scientist)
00:45.000
you
can
train
a
system
to
produce
essentially
what
amounts
to
a
score
for
every
possible
words
in
your
dictionary
or
a
probability
distribution
over
every
possible
words.
So
essentially
what
a
lemma
does
is
that
it
produces
a
long
list
of
numbers
between
0
and
1
that's
some
to
1
Yann LeCun (Chief AI Scientist)
00:59.520
which
for
each
word
in
the
dictionary
says
this
is
the
likelihood
that
this
word
appears
right
now.
You
can
Yann LeCun (Chief AI Scientist)
01:05.280
represent
the
uncertainty
in
the
prediction
this
way.
Now,
try
to
translate
it
um
the
same
principle
instead
of
training
a
system
to
predict
the
next
word
feed
it
with
a
video
and
ask
it
to
predict
what
happened
next
in
the
video.
And
this
doesn't
work.
I've
been
trying
to
do
Yann LeCun (Chief AI Scientist)
01:22.480
this
for
20
years.
And
it
it
really
doesn't
work.
Yann LeCun (Chief AI Scientist)
01:26.160
If
you
try
to
predict
at
the
pixel
level.
Uh
and
it's
because
the
real
world
is
messy.
There's
a
lot
of
things
that
that
may
happen,
plausible
things
that
may
happen.
Um
and
you
can't
really
represent
a
distribution
of
all
possible
uh
things
that
may
happen
in
the
future
because
Yann LeCun (Chief AI Scientist)
01:44.360
it's
basically
an
infinite
list
of
possibilities
and
we
don't
know
how
to
represent
this.
um
efficiently.
And
Yann LeCun (Chief AI Scientist)
01:51.040
so
those
those
techniques
that
work
really
well
for
text
or
for
sequences
of
of
symbols
do
not
work
for
real
world
sensory
data.
They
just
don't.
They
absolutely
don't.
And
And
so
we
need
to
invent
new
techniques.
So,
one
of
the
things
I've
been
proposing
in
one
in
which
the
the
Yann LeCun (Chief AI Scientist)
02:09.960
system
learns
an
abstract
representation
of
what
it
observes
and
it
makes
prediction
in
that
abstract
representation
Yann LeCun (Chief AI Scientist)
02:16.000
space.
And
this
is
really
the
way
humans
and
animals
function.
And
we
we
find
abstractions
that
allow
us
to
make
predictions
while
ignoring
all
the
detail
the
details
we
cannot
predict.
Janna Levin (Professor of Physics and Astronomy)
02:26.400
So
you
really
think
that
despite
the
phenomenal
successes
of
these
LLMs
that
they
are
limited
and
and
their
limit
is
quickly
approaching.
You
don't
think
that
they're
scalable
to
this
you
know
artificial
general
intelligence
or
a
super
intelligence.
Yann LeCun (Chief AI Scientist)
02:41.320
That's
right.
No,
they
don't
and
and
you
we
see
the
performance
saturating.
So
we
see
uh
progress
in
in
some
domains
like
mathematics,
for
example.
And
mathematics
and
and
code
generation,
you
know,
programming
are
two
domains
where
the
uh
the
the
manipulation
of
symbols
Yann LeCun (Chief AI Scientist)
02:59.160
actually
gives
you
something,
Yann LeCun (Chief AI Scientist)
03:00.440
right?
As
a
physicist,
you
you
know
this,
right?
You
write
the
equation
and
it
actually
kind
of
You
You
can
follow
it
and
it
it's
uh
it
drives
your
your
thinking
to
some
extent,
right?
I
mean,
you
you
drive
it
by
intuition,
but
but
the
symbol
manipulation
itself
actually
has
Yann LeCun (Chief AI Scientist)
03:16.600
meaning.
So,
this
type
of
problems,
LLM's
actually
kind
of
handle
pretty
well,
where
the
the
reasoning
really
consists
in
kind
of
searching
through
sequences
of
symbols.
Yann LeCun (Chief AI Scientist)
03:25.360
But
it's
only
there's
only
a
small
number
of
problems
for
which
that's
the
case.
Chess
playing
is
another
one.
Um
you
search
through
sequences
of
of
of
moves
that,
you
know,
for
a
good
one
or
sequences
of
derivations
in
mathematics
that
will
produce
a
particular
result,
right?
Yann LeCun (Chief AI Scientist)
03:41.240
Um
but
in
the
real
world,
you
know,
in
high
dimensional
continuous
things
where
the
search
has
to
do
with
like
how
do
I
move
my
muscles
to,
uh,
you
know,
grab
this,
uh,
you
know,
grab
grab
this,
this
Yann LeCun (Chief AI Scientist)
03:55.000
glass
here.
I'm
not
going
to
do
it
with
my
left
hand,
right?
I'm
going
to
have
to
change
hand
with
this
and
and
then
grab
it,
right?
You
need
to
plan
and
have
some
understanding
of
what's
possible,
what's
not
possible,
that,
you
know,
I
can
just
attract
the
glass,
you
know,
by
Yann LeCun (Chief AI Scientist)
04:10.080
telekinesis
or
I
can
just
I
can't
just
make
it
appear
in
my
in
my
left
hand
like
this.
I
can't
have
my
hand
kind
of
cross
my
Yann LeCun (Chief AI Scientist)
04:18.040
body.
Like,
you
know
You
know,
all
of
those
intuitive
things,
we
we
learn
them
when
we're
babies
um
and
and
we
learn,
you
know,
how
our
body
reacts
to
our
controls
and
how
uh
you
know,
the
the
world
reacts
to
to
the
actions
we
take.
So
So,
you
know,
if
I
push
this
glass,
I
know
Yann LeCun (Chief AI Scientist)
04:38.200
it's
going
to
slide.
If
I
push
it
from
the
top,
maybe
maybe
it's
going
to
flip.
Maybe
not
because
the
friction
is
not
that
high.
Yann LeCun (Chief AI Scientist)
04:45.120
If
I
push
with
the
same
force
on
this
table,
it's
not
going
to
flip.
I
You
know,
we
have
all
those
those
intuitions
that
allow
us
to
kind
of
apprehend
the
real
world.
But
this
is
it
turns
out
much
much
more
complicated
than
manipulating
language.
We
think
of
language
as
kind
of
Yann LeCun (Chief AI Scientist)
05:00.960
the
epitome
of
you
know
human
intelligence
and
stuff
like
that.
It's
actually
not
true.
Language
is
actually
easy.
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