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IRTBYPRADA.to studying AI in my undergrad, to going to a
lot of the world’s top institutes, doing a PhD as
well as running a startup in my earlier career...
I’ve tried to use every scrap of experience. I’ve
consciously picked each of those decision points
to gather that piece of experience.”
Add to that list being a CEO, which is now his
day job. He has another role – that of researcher –
and, in order to do both, he structures his time into
distinct periods so that he can balance the running
of the business with his academic interests. Having
played the role of executive during the day, he
returns home around 7.30pm to have dinner with
his young family before embarking on a “second
day” around 10.30pm, which will generally end
around 4.00am to 4.30am.
“I love that time,” he says. “I’ve always been a
nocturnal person, since I was a kid. Everything is
quiet in the city and the house and I find it very
conducive to thinking, reading, writing... these
kinds of things. So that’s when I mostly keep up
to speed with the scientific literature. Or maybe
I’ll be writing or editing a paper, or thinking up
some new algorithmic idea, or thinking about
something strategic, or be investigating some
area of science that AI could be applied to.”
He listens to music when he works. The nature
of the music – from classical to drum and bass –
depends “on the emotion I’m trying to evoke in
myself. It depends on whether I’m trying to be
focused or inspired.” There are a couple of rules:
there can be no vocals, otherwise he will try and
listen to the lyrics; and there needs to be a level
of acquaintance with the music. “It needs to be
something I’m familiar with, but not too familiar
with. And it can’t be a new piece of music because
that is too disturbing for the brain. You’ve got to
break a tune in, and then you can use it.”
Hassabis says that he would like to spend 50 per
cent of his time on direct research. As part of this,
in April 2018, he hired Lila Ibrahim, a Silicon Valley
veteran who spent 18 years at Intel before becomingChief of Staff at Kleiner, Caulfield, Perkins and Byers- one of the most established venture capital firms in
the Valley – before moving to the startup Coursera.
Ibrahim is taking on many of Hassabis’s managerial
tasks – he says his direct reports have dropped from
20 people to six. Ibrahim describes her decision
to join DeepMind as “a moral calling,” prompted
by conversations she had with Hassabis and Legg
regarding the establishment of its Ethics & Society
initiative, which is attempting to establish standards
around the application of the technology.
“I think being based in London it brings a slightly
different perspective,” she says. “What would have
happened if DeepMind had been headquartered
in Silicon Valley would have been a very different,
I think. London feels like there’s so much more
humanity... the art, the cultural diversity. There’s
also what the founders brought in from the start and
the type of people who choose to work at DeepMind
brought in certain ways of doing things, a mindset.”
One incident perhaps offers insight into the
approach Ibrahim describes. Hassabis was a
chess prodigy; starting at the age of four, he rose
up the rankings until, when 11, he found himself
competing against a Danish master at a large,
international competition that took place in the
town hall of a village outside Liechtenstein.
After playing for close to an entire day, the
endgame approached. It was a scenario that
Hassabis had never seen before – he had a queen,
while his opponent had a rook, bishop and knight,
but it was still possible for Hassabis to force a
draw if he could keep his opponent’s king in check.
Hours passed, the other games ended and the
hall emptied. Suddenly, Hassabis realised that
his king had been cornered, meaning that check
mate would be forced. Hassabis resigned.
“I was really tired,” he says. “We were 12 hours in
or something and I thought somehow I must have
made a mistake and he’s trapped me.”
His opponent – a man Hassabis recalls being in
his 30s or 40s – stood up. His friends were standing
around him and he laughed and gestured at the
board. Hassabis realised that he had resigned
unnecessarily – the game should have been a draw.
“All I needed was to sacrifice my queen,” he
says. “This was his last roll of the dice. He’d been
trying for hours to outmanoeuvre me. And that was
his final cheap trick. And it worked. Basically,
I had nothing to show for 12 hours of slog.”
‘ DeepMindis what Ispent mywhole lifepreparingfor. Fromgamesdesign toneuroscience,I’ve triedto use everyexperience’or many startup founders, there is a
degree of serendipity to their mission – a problem
they’ve come across that they decided to solve, a
chance encounter with a co-founder or investor,
an academic advocate. This is not the case for
Hassabis, who has purposefully made a series of
decisions – some very early in life – that would
lead to DeepMind. “It’s what I spent my whole life
preparing for,” he says. “From games design to
games playing to neuroscience to programming,biggest drug companies.” Similarly, research from Deloitte estimated
that R&D returns in biopharma had declined to their lowest rate in nine
years, from 10.1 per cent in 2010, to 1.9 per cent in 2018.
“If you look at the CEOs of most of the big pharma companies, they’re
not scientists, they come from finance, or the marketing department,”
Hassabis says. “What does that say about the organisation? It means that
what they’re going to do is try and squeeze more out of what has already
been invented, cut costs or market better, not really invent new things- which is much more risky. That’s not the nature of blue sky thinking...
that’s not how you do it if you’re trying to land the rocket on the Moon.”
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