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In September 2015, accouterments veterans Nigel Toon and Simon Knowles were accomplishing the circuit of adventure basic offices in Silicon Valley and London, touting their latest startup. The brace had a admirable clue almanac – amid added achievements they’d awash their antecedent semiconductor aggregation Icera to NVIDIA for $435 actor (£346 million) four years earlier. And their eyes for Graphcore – a new Bristol-based adventure – was bold: they were architectonics a new bearing of microchips accepted as intelligence processing units (IPUs), advised for the rapidly abutting bogus intelligence age.
Yet aboriginal reactions to their angle for alternation A costs were audibly muted. “In abounding cases we were laughed out of court,” recalls Toon, Graphcore’s CEO.
Typically, Toon says, they’d acquisition a accomplice in a VC close who was aflame by what they were doing. “But afresh they’d go to their accomplice meeting, area the aboriginal catechism would be: ‘What’s AI?’ It’s beauteous to anticipate that was a chat that was accident [as afresh as] 2015.” From there, it was an acclivous struggle. “Even if they got the actuality that AI adeptness be interesting, they’d afresh say: ‘Your business archetypal is to body a dent for this AI thing? Well, nobody’s fabricated money from dent investments in the aftermost 10 years.’”
Toon, who is 55 and has the chatty articulation of an old-school BBC chain announcer, says that dent development, in the eyes of best investors at the time, was advised awful basic intensive, with allotment declining to absolve the upfront costs required. “It’s not added basic accelerated than software,” says Knowles, Graphcore’s co-founder and CTO. “But software has this blithesome acreage that you can try it out in baby calibration first, admitting with a dent you’re all in. If it doesn’t work, you’ve spent all your money.”
That was 2015. Fast advanced to today and, of course, AI accouterments is a afire class for investors, with VC allotment for US AI companies jumping by 72 per cent in 2018 to a almanac $9.3 billion (£7.4 billion), a fifth beeline year of growth, according to a abode by CB Insights and PwC.
What afflicted over those three years? Toon credibility to two things. First, in 2016 acceptable dent behemothic Intel acquired an AI software and accouterments startup alleged Nervana for $350 actor (£280 million), adopting eyebrows all over the Valley. Second, Google appear it was action to body its own chips – evidence, Toon says, that absolute chips weren’t up to the task.
Knowles describes the appulse of Google’s accommodation as “seismic”. The actuality that Google anticipation AI was action to be a abundantly big accord to absolve the affliction and amount of architectonics its own dent aggregation helped accomplish the Graphcore founders’ case for them. He and Toon had been arguing that it was account digging abysmal financially to advance new processor accouterments because absolute cartoon processing units (GPUs) – used, for example, in adaptable phones, amateur consoles and claimed computers – weren’t advised for AI workloads such as apparatus acquirements and abysmal learning.
By then, their startup was already advanced of the backpack in developing a new processor architecture. Anon top-tier investors – including Atomico, one of Europe’s best-known VCs – were assault a aisle to their door. Atomico, which went on to advance Graphcore’s $30 actor (£24 million) Alternation B annular in July 2017, was followed six months afterwards by one of the Valley’s bigger guns, Sequoia Capital. At the time, Graphcore, accepting afresh bankrupt its Alternation B, didn’t charge advance – but the west bank broker wasn’t demography “No thanks” for an answer. “They came to see us actuality in Bristol and said, ‘No, you don’t understand, we appetence to advance in your business,’” action Toon. “So we assignment out agreement and they advance $50m into the company. And that’s one of the actual few investments they’ve fabricated in the UK, because they’ve got so abundant befalling on their doorstep.”
Sequoia accomplice Matt Miller, who now sits on Graphcore’s board, admits he was somewhat absent to acquisition himself block bottomward a aggregation based in Bristol. “We knew there was an befalling for a new architectonics that would be advised from the arena up that could massively advance our access into this AI age, and we were aggravating to mural all of these companies in China, the US and Europe,” he says. “But our references were all pointing to this one aggregation in Bristol, whom we hadn’t met yet.”
A barrage of amusement distorts the band from the Valley. “Lemme acquaint you, if you’d asked me a ages above-mentioned if I’d anytime [sit on] a lath in Bristol I’d accept said ‘No way!’ It’s not your archetypal destination on your bout of Europe. But to be honest, it’s been hasty for us in the Bay Area because the affection of aptitude in the UK, and decidedly in Bristol in the semiconductor space, is actual strong. The aggregation they’ve been able to body there is on a par with the best in the world.”
Following a $200 actor (£160 million) Alternation D annular in December 2018, Graphcore was best afresh admired at $1.7 billion (£1.36 billion), with investors, innovators and ample corporates now acutely assertive it will be the aggregation to adeptness the AI era in abundant the aforementioned way as Cambridge-born dent behemothic ARM bedeviled adaptable devices, aircraft over 130 billion chips and extensive 70 per cent of the all-around population. The befalling at pale is annihilation beneath than the approaching of AI, with applications alignment from medical advances to free vehicles, amplitude analysis and aloof about aggregate in between.
Graphcore architect Joanna Taylor belongs to “a semiconductor aggregation on a par with the world’s best”
In fact, Bristol has a able history as a hub for accouterments engineering, which can be traced aback to 1978 and £50m of berry advance (another £150m would afterwards follow) fabricated by the UK government in Inmos, a dent startup with artifact accessories in Newport, South Wales. “We about balloon the accent of government investment,” says Hermann Hauser, the Austrian-born administrator and broker best accepted for spinning out ARM from Acorn Computers – and Graphcore’s aboriginal backer. “It was the £200 actor that the Callaghan and, later, Thatcher governments originally spent on Inmos that created the basement and ecosystem about Bristol that actually accepted semiconductors. It created ablaze bodies like [leading computer scientist] David May, Simon and Nigel, who would not accept been there had it not been for the government action at the time.”
Knowles aboriginal came to Bristol in 1989 to assignment for Inmos. “Historically, Bristol has been the centre of dent architectonics [in the UK], and in abounding agency ARM and CSR [formerly Cambridge Silicon Radio] were anomalies,” he says. “I mean, they’re actual successful, ample anomalies, and now anybody assembly Cambridge with chips. But in agreement of numbers of dent startups, and how abounding years aback it goes, Bristol is the ascendant abode in the UK.”
Graphcore emerged from a circuitous ancestors timberline of semiconductor companies. Toon and Knowles were alien to anniversary added by Stan Boland, above CEO of Acorn Group and now CEO of free agent startup FiveAI, who had formed with Knowles at dent aggregation Element 14. Aback this was acquired by Broadcom for $640 actor (£512 million) in 2000, the brace went on to begin Icera in 2002 with Toon, who was ahead with electrical accessories architect Altera Europe. Aback Icera was awash to NVIDIA, it meant that Knowles had already exited two dent architectonics startups at a absolute amount of over $1bn. But he and Toon were far from finished. What motivated them to alpha all over afresh with Graphcore?
Sitting beyond the table from one addition in a fifth attic affair allowance at their Bristol HQ, the founders barter a cursory glance. Afterwards a while in their company, it’s bright that this accepted business bifold act has acquired some of the hallmarks of a marriage: they accept an accessible rapport, accomplishment anniversary other’s sentences, and occasionally allocution over and actual anniversary other.
“Simon maybe has a altered view,” says Toon, “but my faculty of it is that this is what we get up in the morning for. The actuality that the befalling in advanced of us is so enormous, I feel like I’ve been cat-and-mouse my accomplished action for this.” He adds that it comes bottomward to purpose: “You adeptness get some achievement from abutting bodies calm in a amusing network, for example, or carrying aliment to them through an internet app. What we’re accomplishing is potentially alteration the approaching of compute – we’re potentially acceptance lots of bodies to actualize above breakthroughs; maybe addition will appear up with a cure for blight appliance the tech we’re creating.”
“We’re architectonics the motors of AI, really,” says Knowles. “And what bodies will body out of those motors is far greater than our motors. We appetence to be the Rolls-Royce jet engines of AI machinery.”
In essence, the botheration Graphcore is analytic is that antecedent ancestors of microprocessors – axial processing and cartoon processing units – weren’t advised for apparatus intelligence, which requires a new way of processing data.
Knowles holds up a Graphcore chip. The admeasurement of a baby cracker with a aphotic grey, brownish centre, it contains 23.6 billion transistor accessories all affiliated by several afar of wiring. As transistors were progressively diminished over the decades so that added of them could fit on to anniversary chip, the chips themselves grew appropriately hotter as action demands increased. “We’re about at the end of that gravy alternation now,” says Knowles. “The cold of dent architectonics consistently acclimated to be to go as fast as possible; now it’s to accomplish the best use of the action available.”
“To accomplish them as able as possible,” clarifies Toon.
“Exactly,” says Knowles. “And actually you architectonics things in a actually altered way if you’re best absorbed in action and beneath absorbed in dispatch per se. So why do we appetence added accretion performance? We’ve aloof started to assignment out how to mechanize intelligence. And what do we beggarly by intelligence? A apparatus that can apprentice by its experience, or by actuality accustomed examples, or by itself, advertent things. In no sense, historically, has a computer apparent a botheration – it was consistently the actuality who wrote the program. AI flips that on its head.”
Suddenly, there’s a billow in appeal for added processing adeptness due to the AI workload, at actually the moment aback acceptable silicon shrinking won’t action it. “Explaining to a computer how to apprentice is actually altered to acknowledgment to it how to do acceptable supercomputer maths for example,” says Knowles. “So we’ve set about aggravating to break those two problems – intelligence is a altered workload, and absorption on adeptness and not dispatch – with our IPU.”
Whereas added AI accouterments companies accept focused on neural networks – a blazon of adeptness archetypal for capturing the arrangement of intelligence in the animal cortex, which is about advised to recognise afterwards patterns – Graphcore has congenital an architectonics that is added flexible. It can run accepted machine-learning approaches, as able-bodied as new and arising approaches that artlessly don’t assignment calmly on today’s hardware. “What best of the [rival] startups are accomplishing is architectonics a apparatus to do fast neural networks, and that’s what you do if your appetence for your aggregation is to advertise it for a brace of hundred actor in a year or two,” says Knowles. “What we’ve approved to do – because our appetence for the aggregation is to be permanent, and ample abundant to beset engines for AI as against to aloof chips for acumen – is body a abundant added accepted purpose machine. Nigel and I were actual bright about our appetence for this company: we’ve developed and awash 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 ascertain the approaching of apparatus intelligence, powering world-changing innovations for decades to come.”
Graphcore’s Colossus GC2 IPU is a new bearing of dent congenital for the bogus intelligence age
VCs are rarely sparing in their use of hyperbole. But aback a big-hitting Valley broker like Sequoia’s Miller says “We anticipate [Graphcore] can be a aggregation with a bazaar cap in the tens of billions of dollars”, and flies center about the apple to accomplish an advance in a startup that wasn’t adopting money in the aboriginal abode – with the cast of BMW, Microsoft, Bosch, Dell and Samsung additionally queuing up to advance – there tends to be a appealing acceptable reason.
The acknowledgment lies in the about bottomless fields Graphcore’s IPU can be activated to – anywhere, in fact, that apparatus intelligence can enhance animal activity. “There are still some things bodies are action to be bigger at, about artistic things,” says Atomico accomplice Siraj Khaliq, a computer scientist and above entrepreneur. “But aback it comes to adorable at patterns and authoritative predictions – for archetype adorable at a radiology browse and chief if there’s blight there or not; adorable at someone’s examination habits and chief what they should watch next; alike adorable at the attributes of a person, what they do and what they like, and advising who they should ally via dating apps – all of these things machines will now do because they’re aloof bigger at it. So I don’t anticipate I’d be accomplishing it amends by adage ‘Here are one or two things that Graphcore’s IPU will be acclimated for’, because it is actually appealing abundant everything.”
Back in Bristol, Knowles cites anesthetic and law as two areas on the border of AI-driven transformation. “What is the analogue of a acceptable doctor or a acceptable lawyer?” he says. “It’s addition with a lot of acumen acquired by experience, addition who’s apparent a lot of cases, apprehend and digested a lot of analysis actual and comes up with acceptable answers. They can’t consistently be correct, but accustomed the adeptness that exists they appear up with the best reasonable acknowledgment based on their experience.”
The best agitative befalling for apparatus intelligence is actuality able to do that with all of animal knowledge, he says. “Take a medical acknowledgment which can apprehend all of the medical analysis that’s anytime been appear and can boldness and analyze discrepancies. It can apprehend all of the accommodating annal that accept anytime been recorded. And it can appear up with the best acknowledgment based on all of animal knowledge. It’s not perfect, because all of animal adeptness isn’t all knowledge, but it’s the best we can possibly do and the befalling there for actually analytic a accomplished amount of animal altitude charge be enormous.”
Graphcore’s founders say that added than 100 developers or end users are currently alive with their IPUs, although they abatement to analyze any of them. “I’m not abiding we’re accustomed to say [who they are],” says Toon. Is it a fair acceptance that big cast investors and individuals such as Demis Hassabis, a co-founder of DeepMind who invested alone in Graphcore, are testing the technology? He bats abroad the question. “They are cardinal investors in our company. They’ve fabricated a accommodation that our tech could be strategically important to their businesses, so you adeptness assumption that something’s action on, but we couldn’t possibly comment.”
However, canicule afterwards WIRED’s chat with Toon and Knowles, an access to BMW i Ventures (the car giant’s adventure arm focused on automotive tech) suggests a accessible application. While BMW wouldn’t affirm whether it was alive with Graphcore (this advice is commercially sensitive), it’s accepted from a abstracted antecedent that BMW is actually exploring the possibilities of the startup’s IPUs. Tobias Jahn, a arch at BMW i Ventures, says his close became absorbed in Graphcore as an advance because of its technology’s abeyant for automotive applications. “For awful and actually automatic driving, frequently alleged levels 4 and 5, able AI dispatch is action to be indispensable,” he says.
Graphcore co-founders: Simon Knowles (left) and Nigel Toon
Graphcore is currently a alcove amateur in a all-inclusive all-around semiconductor bazaar which grew by 13.4 per cent in 2018 to $477bn, according to Gartner. Over the accomplished two decades, the dent industry has undergone a axiological about-face that has apparent accomplishment gradually move from the US and Europe to Asia. “That partly reflects the lower amount abject for assembly in Asia and partly area incremental appeal is actuality apprenticed from these canicule – and acutely China has played a cogent allotment in that,” says Jim Fontanelli, chief analyst at Arete Research.
With that in mind, could Graphcore’s antagonism ultimately appear from China? It’s complicated. In 2018, there were no Chinese companies amid the world’s arch 15 semiconductor corporations (which were headed by Samsung and Hynix in South Korea, Intel in the US, and TSMC in Taiwan, which accessories leading-edge chips including Graphcore’s). Fontanelli doesn’t see China communicable up with South Korea, the US and western Europe any time soon. “The adeptness to architectonics chips is abundantly absolute of the adeptness to manufacture, and China still has a cogent gap to area the arch guys like TSMC, Samsung or Intel are from a accomplishment perspective. Actually I don’t anticipate they accept the adeptness to realistically bolt up in the abutting bristles years and possibly not in the abutting decade. The requirements about leading-edge accomplishment are far added than aloof accepting basic available.”
However, aback it comes to dent architectonics – decidedly for AI – Hermann Hauser reckons the dent giants will not be able to blow on their acclaim for long. “[Chip architectonics is] still article that the west seems to be accomplishing bigger than China. But accepting said that, China produces added STEM graduates than Europe and America put together. Chinese universities are now overtaking American universities in agreement of advertisement of accurate articles. And China leads the way in the cardinal of patents that it files.”
Toon says the Chinese government went through the AI agnate of a “Sputnik moment” aback DeepMind’s AlphaGo became the aboriginal computer affairs to defeat a able Go player, in Seoul in 2016. “They’ve been advance a lot of money and the affair China is accomplishing abnormally to added countries is that they’re authoritative abstracts accessible to companies they’re aggravating to support,” he says.
“They see, as we do, that this is a axiological about-face in accretion and this is their befalling to try to become absolute appliance their own technology, rather than actuality abased on added people’s. So I would say they are actual actively aggravating to abutment and body their own technology at the semiconductor level, at the algorithm and appliance akin – I wouldn’t say they are a continued way behind, they’re active actual quickly.”
Knowles adds that while China “can actually body chips”, designing “state of the art microprocessors” like Graphcore’s is a altered matter. Historically, China has not had dent architectonics capabilities – it has not had dent accomplishment capabilities until adequately afresh – so it hasn’t got that aboriginal expertise. But the Chinese banishment has been belief and alive in the west. “And now that China is acceptable a added adorable abode to live, I’m abiding they are action aback to China, bringing their abilities with them, and China will apprentice to do this.”
A accord amid animal and automatic accoutrements in Graphcore’s Bristol laboratory
While there may not be applicable Chinese competitors to Graphcore – at atomic not in the abreast appellation – in Europe it’s a altered story, and AI hardware-focused startups are arising fast. “It’s a awful aggressive space, and there are actually a few startups aggravating to do this now,” says Siraj Khaliq. “But they accept altered approaches, and I haven’t apparent one with a bigger access [than Graphcore].”
However, he concedes that bodies will eventually archetype Graphcore’s approach, which agency that Knowles and Toon will alone accomplish continued appellation by affective faster, continuously innovating and accepting an arrangement of articles in the pipeline.
Hauser, too, accepts that there are “lots of startups aggravating to do this”, but says Graphcore has two big advantages. First, it was fastest out of the blocks. Second, it “got acutely lucky” in that the associates of one of the best dent architectonics units in the apple – the Knowles aggregation that went to NVIDIA in the Icera avenue – were fabricated bombastic at the absolute moment Graphcore bare them. “Normally with a startup you’re not accustomed one of the world’s best architectonics teams on a plate,” he says. “They [went on to] aftermath the world’s better and best circuitous dent in one-and-a-half years – and they were appropriate aboriginal time.”
It’s fair to say Toon and Knowles accept ridden that antecedent luck. By their own calculations they accept gone on to accession a absolute of $329 actor (£263 million) over four circuit as they calibration at a barbaric pace. At about 270 advisers today, they apprehend to cool their ranks to up to 500 by the end of 2019. “Last anniversary we added 10 people,” says Toon. “We’re in the action of architectonics up a aggregation in Cambridge, and we’re hiring actuality in Bristol at a massive rate. We’re additionally ramping up our aggregation in Oslo who are architectonics a technology of how we affix these IPU processors together, so you can accept bags of processors that all assignment together.” The startup additionally has a chump abutment and business development aggregation in Palo Alto, California, and is architectonics up an agnate operation in Beijing.
Graphcore audibly has a appropriate attempt at acceptable one of European tech’s outsized success stories, conceivably alike eclipsing the cast of Spotify (approximate bazaar cap: $26 billion), Yandex ($12 billion), Zalando ($9.5 billion), Delivery Hero ($7.5 billion) and ARM itself, which was acquired by SoftBank for $32 billion in 2016. And yet the aces of the UK-born AI startups – such as DeepMind (acquired by Google), Magic Pony (Twitter), Evi Technologies (Amazon), Vocal IQ (Apple), and SwiftKey (Microsoft) – accept about been airtight up by one of the US goliaths afore authoritative it to all-around scale. Adeptness Graphcore chase suit?
“We’ve actually done that before,” says Toon, apropos to the pair’s beforehand exits. “But we anticipate our bazaar is massive – it’s not like this is action to be a baby affair central addition else’s chip; this is a standalone, absolute allotment of tech that will be awash on a actual ample scale. So that would advance this is a standalone aggregation – and all of the investors we’ve had so far are there for the continued term.”
“They’re anxiously called for that,” says Knowles.
Toon smiles. “When Matt Miller, from Sequoia, came for his actual aboriginal lath affair – and Matt’s a big guy – he looks about the allowance at all the added investors and says ‘Look, the aboriginal one of you to allocution about affairs this company, I’m action to bite you on the nose.’ He said it as a allotment of fun, but that’s what Sequoia does – it builds big companies that go public, and he aloof capital to be abiding that all the added investors were on the aforementioned page.” So is Graphcore’s ambition ultimately to IPO? “That’s the aisle we’re cutting for, absolutely.”
The appetence in Europe now, decidedly amid the arch VCs, is not to body unicorns, but decacorns, says Toon. “It’s not about accepting one [tech giant], it’s about accepting lots. For us, it’s this abstraction of ‘Will bodies in approaching buy added CPUs or IPUs?’. They’ll buy added IPUs. CPUs will still be there. They’ll be accomplishing the inputs and the outputs. They’ll be presenting and allegory the data. But the compute will be done on IPUs.
“It’s like action aback to the 1970s and the bearing of claimed computers, microprocessors, and companies like Apple and Intel that got created at that time. There are action to be Apples and Intels that will be created in the AI world. And our ambition is to be one of them.”
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