approaches that simply don’t work
efficiently on today’s hardware. “What
most of the [rival] startups are doing
is building a machine to do fast neural
networks, and that’s what you do if your
ambition for your company is to sell it
for a couple of hundred million in a year
or two,” says Knowles. “What we have
tried to do – because our ambition for the
company is to be permanent, and to be
broad enough to encompass engines forAI as opposed to just chips for perception- is build a much more general-purpose
machine. Nigel and I were very clear
about our ambition for this company:
we’ve grown and sold companies before,
but this one is our magnum opus.”
Toon chips in: “This is a once-in-a-
generation opportunity. If we get this
right, the IPU will define the future of
machine intelligence, powering world-
changing innovations for decades.”
VCs are rarely sparing in their use of
hyperbole. But when a big-hitting Valley
investor like Sequoia’s Miller says “We
think [Graphcore] can be a company
with a market cap in the tens of billions
of dollars”, and flies halfway round the
world to make an investment in a startup
that wasn’t raising money in the first
place – with BMW, Microsoft, Bosch, Dell
and Samsung also queuing up to invest- there tends to be a pretty good reason.
The answer lies in the almost limitless
fields Graphcore’s IPU can be applied to - anywhere, in fact, that machine intel-
ligence can enhance human activity.
“There are still some things humans are
going to be better at, typically creative
things,” says Atomico partner Siraj
Khaliq, a computer scientist and former
entrepreneur. “But when it comes to
looking at patterns and making predic-
tions – for example looking at a radiology
scan and deciding if there’s cancer there
or not; looking at someone’s viewing
habits and deciding what they should
watch next; even looking at the attributes
of a person, what they do and what they
like, and recommending who they should
marry via dating apps – all these things
machines will now do because they’re
just better at it. So I don’t think I’d be
doing it justice by saying: ‘Here are
one or two things that Graphcore’s IPU
will be used for’ – because it is really
pretty much everything.”
Back in Bristol, Knowles cites law and
med icine as two areas on the brink of
AI-driven transformation. “What is the
EUROPEThe continent is striving
to keep hold of its talent.
Germany is committed to
a £2.7 billion AI strategy,
and the UK has pledged
£18.5 million to train people
from diverse backgrounds.
Meanwhile, French chip
design firm Kalray and
Dutch manufacturer NXP
are partnering to develop
a computing platform for
autonomous cars.USIntel, NVIDIA and AMD
enjoy a strong position
in the global market –
their GPUs are key to
data centres, self-driving
cars and cryptocurrency
mining – but startups
such as Cerebras Systems
are challenging with
more specialised chips.
Cerebras is still in stealth
mode, but has raised $112
million in three rounds.AI CHIPS:
OPENING
SALVOS IN
A GLOBAL
SHOWDOWNCHINASince 2017, China has
outpaced the US in terms
of AI investment, but the
US still strikes more deals,
according to ABI Research.
Chinese chipmaker Horizon
Robotics, whose products
go into autonomous
cars and surveillance
cameras, announced in
February 2019 that it was
now valued at £2.4 billion,
overtaking Cambricon –
a Chinese company that,
at £2 billion, had been
hailed as the world’s
highest valued smart-
chip startup. Meanwhile,
cryptocurrency-mining
giant Bitmain is also
turning to AI chips. SW09-19-FTgraphcore.indd 153 25/07/2019 13:03