amna: This year's Nobel prize in
chemistry went to three
scientists, David baker, John
jumper, and demis hassabis, for
their groundbreaking work using
artificial intelligence to
advance biomedical and protein
research.
The ai model they developed,
called alphafold, uses databases
with hundreds of thousands of
protein structures and millions
of protein sequences, to predict
and even design protein
structures.
Speeding up a months or
years-long process, to mere
hours or even minutes.
Alphafold was rolled out just
four years ago, and has since
been cited in scientific studies
more than 20,000 times.
Joining us now from London, is
demis hassabis co-founder and
CEO of Google deepmind and
recipient of the Nobel prize in
chemistry.
Congratulations, and welcome.
Demis: Thank you so much.
Great to be here.
Amna: First and foremost, what
you do think when you heard the
news?
Demis: I was totally stunned to
be honest, and it has not even
sunk in really 24 hours later.
So it's just feels very surreal.
Amna: So I'm going to try here
in simplest terms, which is not
simple at all, but to condense
the work you and your colleagues
have done it.
Basically, you and your
colleague John jumper discovered
new and powerful ways to not
only decode, but also design
proteins using artificial
intelligence.
I'm not even going to try to
understand the details of your
work, but in terms of
application, how could this
impact future development of
things like medicine and
vaccines?
What does it mean?
Demis: Well proteins are the
kind of building blocks of life,
really.
All the functions of your body
are kind of supported by
proteins.
And it is really important to
understand their structure, that
3D structure, so that you can
understand and function as they
have.
And so that's what alphafold,
our program, does.
It predicts that 3D structure,
just from the genetic sequence
and it will be really important
for things like drug discovery
and understanding disease.
Amna: There's one scientist who
reacted to the news of your
award by calling your work the
holy grail, in terms of what
it's been able to do.
Do you agree with that
characterization?
Demis: Well, it's very nice of
them to say so.
I mean, it's certainly a grand
challenge.
I mean, the reason that I sort
of -- I think it kind of caught
my attention is it's been a kind
of grand challenge of biology
for the last 50 years.
So people have been predicting
since the 1970's that this
should be possible.
But until now, no one has been
able to do it to an accuracy
high enough that it's useful for
biologists and medical experts.
Amna: So, just in the way of
background, you co-founded
deepmind back in 2010, but
before that I was interested to
read you designed video games.
Before that, you were a chess
prodigy.
You were once even ranked the
second highest player in the
world under the age of 14.
How did those endeavors, chess
and gaming, feed into this work
today?
Demis: Well, it's actually
there's a connection all the way
through my career, and I've done
different things.
So, it's because of gaming and
chess that I got started to
think about thinking.
And I was trying to improve my
own thought processes, as you do
when you're playing chess for,
you know, the junior teams and
the national junior teams and
things like that.
I was playing it very
professionally.
And part of that training, Y Y
also use chess computers, very
early chess computers in the
1980's, they were actually
physical blocks of plastic that
you had to press the keys on.
And I was sort of intrigued by
the fact that someone had
programmed this inanimate object
to actually play chess and play
chess well, and that's what got
me into ai.
Then I studied neuroscience as
well as computer science and
tried to understand better how
the power of brains work, and
how intelligence is produced,
and the mechanisms behind it.
And then finally that all comes
together with the work we do in
ai.
Amna: As you well know, one of
your fellow laureates this year
as a man named Geoffrey Hinton,
who was often called the
godfather of ai.
He resigned from Google last
year, and he's really been
sounding the alarm on what he
says are the potential dangers
here, that, as he puts it, he
worries that the overall
consequences of this might be
systems that are more
intelligent than us, that might
eventually take control.
Do you share that concern?
Demis: You know, I've known
geoff, we've been colleagues for
many, many years, and he's a
fantastic scientist.
My view is sort of more moderate
than that.
I feel like, and of course, I
work my whole life on ai because
I think it's going to be
unbelievably beneficial to
humanity and to society.
You know, alphafold is just I
think the first expression of
that.
And, you know, I think we can go
on next to try and cure many
terrible diseases.
I think it can help with climate
crisis, new materials, new
energy sources, new mathematics.
I think ai is going to
accelerate scientific discovery,
medical discovery across the
board.
So those are just some of the
benefits I think ai is going to
bring and why I've worked my
whole life on ai.
So it's going to be this huge,
transformative technology.
But as with any new powerful
technology, and perhaps I will
be the most powerful, it comes
with risks, attendant risks as
well, and unknowns.
And some of those are to do with
controllability, understanding
these systems, interpreting what
they do, and how to manage them,
you know, what are the values we
want these systems to have, we
want to use them for, how do we
want to deploy them.
And some of these questions are
technical in nature, technical
challenges, and others are more
societal and need discussion
with the whole of society and
civil society, academia, as well
as the tech companies and
industrial labs, and also
government.
And I've been encouraging all of
those debates to happen.
It is great that we are starting
to see thosesehings happen.
And I think given enough time
and effort, we will solve these
challenges.
And I'm a big believer in human
ingenuity.
But we need to start discussing
and researching those things
now.
Amna: That is demis hassabis,
co-founder and CEO of Google
deepmind and recipient of this
year's Nobel prize in chemistry.
Thank you, and congratulations
again.
Demis: Thank you very much.
♪♪