Why a former ARM executive is heading up a UK AI startup

Things are going well for UK artificial intelligence startups right now. As we reported last week, companies developing AI solutions are set to raise a staggering $2.1 billion in venture capital funding in the first half of 2024, with a Dealroom/HSBC Innovation Banking report showing the country is poised to see record investment throughout the year.

But despite a flood of venture capital money, UK AI innovators face the daunting task of developing and commercialising their technology and solutions at a time when start-ups in the US, China and elsewhere are also clamoring for customers. And of course, at the top of the tech industry, the likes of IBM, Google, Microsoft and OpenAI are spending billions to stay ahead of the competition.

So how does a relatively small startup company go from the lab to the market?

Earlier this week, I spoke with Noel Hurley, an IT industry veteran who spent 20 years across two stints at CPU design company ARM. During his time there, he served as vice president of several divisions, including CPUs and incubation. In January this year, he was appointed CEO of Literal Labs, a spin-out from Newcastle University in the northeast of England that is just beginning its commercialization journey. Having worked for one of the very few UK tech companies to have truly succeeded in the global market, I was keen to ask Hurley what the opportunities are for Literal Labs and other research-led AI competitors.

Find your niche

Let's start with Literal Labs. In Hurley's view, Literal Labs has a compelling pitch to potential customers. Rather than using the neural network technology that underpins much of today's advanced AI, the company has built on a concept called the Tsetlin Machine. For those unfamiliar with computer science theory, all you need to know is that this is a technology based on a concept called propositional logic. Literal Labs claims that this technology can produce tools that are up to 1000 times more energy efficient than their neural network counterparts.

As recently reported by Forbes.com, the demand for AI could push the world into an energy crisis. This tends to be seen in terms of the strain that a massive increase in consumption would put on the power grid, but it could also pose problems for companies that could benefit from incorporating AI into their systems.

Hurley gives the example of a production line, saying AI can be used to optimize processes and increase efficiency — the ultimate goal of the AI ​​revolution — but that this can be cost-prohibitive.

So Literal Labs' commercial focus is on edge computing – the kind of processing that happens closer to the site, rather than in far-away server farms – and this is where Hurley sees a foothold.

“There's a whole area of ​​AI called edge AI, which is using artificial intelligence on everyday devices, both from a consumer perspective and from an industrial perspective,” Hurley said.

In addition to production lines, the company sees opportunities in self-driving cars, robots and consumer devices. Hurley also said the Zetlin Machine concept is more transparent in tracking the relationship between inputs and outputs, which helps address the demand for so-called “explainable AI.” For example, say you have a tool that uses a variety of data to approve or deny a mortgage application. Regulated industries are increasingly demanding technology that can explain the process by which these decisions are made.

This means there is a niche market to address. This is perhaps essential for a startup, but if a solution based on the Tsetlin Machine concept would be a panacea, why isn't the technology more widely used? Hurley acknowledges that there is a trade-off: on the one hand, there is speed and efficiency; on the other, the accuracy of the process is currently low. The focus now is on engineering even greater accuracy, and finding applications where the current accuracy level is “good enough.”

Build self-confidence

In the meantime, there's the daunting prospect of finding customers and use cases, which, as Hurley acknowledges, will require a lot of conversations to build relationships and trust in the technology in the first place.

“Building a community around this technology is going to be important, as are building partnerships around this technology. Partnerships with neighbors in the value chain are going to be important. You know, it's going to take some evangelism to get engineers comfortable and enthusiastic about this technology and want to build and develop models using this approach,” he says.

So this is a long-term endeavor, and the same is likely to be true for many of the AI-focused companies currently being spun out of UK universities.

Potholes in the road

And the future is uncertain. The AI ​​investment upswing could become a bubble that eventually deflates, making it harder for new ventures in the sector to get approved and raise capital. Plus, the nature of the investment needs to be considered. Earlier this month, I spoke with Yoram Winjgaarde, founder of intelligence provider Dealroom, about AI investment across Europe. As he pointed out, it's not just venture capitalists who are interested in AI. “Large tech companies are a big part of AI investment,” he said.

All that's fine, but investment in UK and European AI by existing tech giants could undermine the ability of companies on this side of the Atlantic to thrive and grow on their own. That's something Hurley said in a recent interview with Fortune, where he warned that UK AI could become just a sideshow to the US giants.

So what are the chances that a small research-based company will actually be successful?

Hurley recalls his experience at ARM, where the same groundwork was required: “When I was working at ARM in Phase 2, I could go to any semiconductor company and immediately get an audience. But that wasn't the case in the early days,” he says.

But in its early days, ARM had ambitions to win orders in global markets. Hurley cites the leadership mantra of the company's first CEO, Robin Saxby. “He was very vocal about us being a global company. We would spend our time and energy on our customers, and we would be globally focused. Not to be the best in the UK, but to be the best in the world,” Hurley says.

Find the gap

But with the cloud hanging over the incumbent tech giants, is there room in the market for companies coming out of UK universities today? Hurley says the opportunity lies in identifying markets and use cases that the tech giants have little interest in, at least initially.

“Right now, a lot of the big players at this stage aren't really paying attention to niche markets because they're going for the biggest contracts or the ones that will give them the most return for the least amount of effort,” he says. “There are often gaps they're not paying attention to. The key is to look at the technology, what are the benefits of the technology, and then frankly go and talk to the customers that we think would benefit from our technology.”

Like many AI startups, Literal Labs is still at the beginning of its journey, and as with any early-stage business, it's anyone's guess whether its pitch will resonate with customers. But the way Hurley sees it, there's still room for growth in emerging businesses.