laptop and smartphoneThese are exciting times for machine learning start-ups both in the UK and abroad – due in no small part to the growing awareness of machine learning amongst investors and venture capitalists. This much was clear at Silicon Valley Comes to the UK (SVC2UK) last month, an annual event where entrepreneurs and investors discuss today’s most potentially disruptive technologies, and provide lessons for the UK’s start-up ecosystem.

Throughout our project on machine learning we’ve met many UK start-ups who are using this technology to create the next generation of innovative products, services and experiences. For example:

  • CheckRecipient uses machine learning and artificial intelligence to prevent highly sensitive information being sent to the wrong person.
  • Snap Fashion uses AI to help consumers browse its online clothes catalogue for high street clothes, based on material, design and texture preferences;
  • Synthace has developed Antha, a system that uses machine learning to transform the productivity of biomanufacturing and other biology processes; and
  • Intelligent X uses an Automated Brewing Intelligence systems to learn from consumer feedback to produce new beer recipes personalised to consumer taste.

We invited some of these companies to a panel at SVC2UK to speak about the opportunities and challenges for machine learning start-ups. This blog post highlights a few of the key points made during the event.

Silicon Valley Success

Silicon Valley has long been interested in start-ups that use new technologies to transform how we live, work and play. To paraphrase Obi Felten, a director at the company X (formerly Google X), and speaker at SVC2UK, Silicon Valley’s success comes from its experimental and collaborative environment, its appetite for risk, and its strong networks.

And in recent times Silicon Valley has had huge success with machine learning start-ups. For example, some of the most prominent successes of X include Google’s self-driving cars and self-flying delivery vehicles. Both of these ideas use machine learning algorithms and are paving the way for the future of transport.

A competitive environment

Machine learning start-ups have to survive in a highly competitive start-up environment, contending with well-known challenges facing start-ups, such as accessing finance and scaling their business. As we heard at SVC2UK, the latter is helped by finding a gap in the market and having a passionate user community to support the platform and make the most of its features, as Crystal Hutter, Co-Founder of education start-up Edmodo, explained during the ‘Scaling Your Business’ panel. Founders also need to be confident in their ability to execute their idea and business strategy better than other companies with similar ideas. For international expansion, being able to send a co-founder to the new market full-time was incredibly valuable if a company wanted to bring passion, presence and ultimately success in the new market.

But machine learning start-ups also have to deal with more technology-specific challenges such as quality of, and access to, data, as we’ve blogged about before. Moreover, the ideas, apps and services leaving Silicon Valley can mirror the lack of diversity in its entrepreneurs.

The UK, and European, landscape

But whilst there is a lot UK start-ups could learn from Silicon Valley success stories, panellists throughout the day noted that Europe could provide lessons for Silicon Valley and might in fact have a competitive advantage. Both investors and start-ups agreed that in Silicon Valley often a longer-term view was necessary, one that moved beyond software to include collaborative and connected hardware. This is where Europe has a potential advantage considering its long, rich history in industry and manufacturing, for example in the UK and Germany. Focusing our efforts on machine learning in the UK and creating an attractive environment for start-ups could help the UK retain its coveted place as a global machine learning hub in the future.

Coming away from SVC2UK, the big question for me was how the UK could harness machine learning’s transformative potential to create novel, user-friendly and forward-looking services that personalise experiences and automate our everyday tasks. After listening to the fascinating conversations at SVC2UK this year, machine learning start-ups seem to be a core part of the solution.