This week and last week, we’ve had two amazing interviews focusing on aspects of a startup’s operations that are critical for its success: How to price a product and how to create trust online around your product or service. You can’t have one without the other….
I had a chance to sit down with Patrick from www.priceintelligently.com and we walked through some case studies of companies iterating on how they price their products and services. It was great to hear how he approached understanding the customer before really getting to the pricing part.
But pricing is only part of the equation, without consumer trust, no matter how cheap or expensive the product is, it’s nearly impossible to sell. So on that note, the founders of Onfido and online-watch-retailer Chronext joined me to talk about how they built their customer trust online.
With venture investments in AI expected to hit a 300% rise in 2017, and with AI systems playing Atari way better than I ever did, it is no surprise that now is the time to bring to surface discussions like the ethics around AI systems, the impact that AI will have on our labor force, and which areas of AI will receive the most investment in the near future.
As part of the AIBE Summit which took place in the QEII conference center on the 4th of Feb, 2017, I was asked to talk a little about VC investment in the sector. Below are my slides and accompanying audio file of the talk. I hope you enjoy it and please feel free to leave any feedback.
More on the AIBE Summit from their website:
The AIBE Summit is a conference on artificial intelligence in business & entrepreneurship. It will be the largest event of its kind ever to be held, with a capacity of up to 800 participants. Our mission is to increase public understanding and intellectual discussion on the implications of AI for the business world, to raise the technological literacy of students, entrepreneurs, and professionals alike, and to recognise London as one of the world’s major digital capitals for the future of AI. It is an initiative pioneered by the LSE Entrepreneurs Society, driven to celebrate the newly formed Partnership on AI between Google, Facebook, Amazon, IBM, and Microsoft.
Over the past year or so, we’ve had the chance to sit down with over one hundred amazing founders, investors and experts to chat about all aspects of startup life. Ranging from the earliest of days in a company’s journey to scaling up and eventually exiting their companies, we’ve explored and been fortunate to share the journey of what many of our friends know through their experience.
When I started the podcast, the idea was to get behind the person’s achievements and to really understand how their early struggles helped get them the experience they were sharing. The theory is, that by understanding someone’s struggles, you can understand their achievements and learnings… and to this end, we feel we’ve achieved what we set out to do.
As with all projects, however, evolution is necessary. Having learned from our interviews to date, we are committed to finding amazing and knowledgeable people who can share what they know with us so we can learn collectively. We will also increasingly dive into discussions around functional topics and sectors to provide listeners with a deep-dive into hot topics from leading voices in the field.
Over the past year, we’ve also been creating curated playlists for those of you who want to learn more about a specific topic as well as for those of you who want to just better understand functional roles (such as sales or marketing or product development) and the role they can play in your business.
As part of this evolution, I’m happy to embrace the title of our new podcast — ‘This much I know’ — where we look forward to sharing the inside story from founders, investors and leading tech voices; the people who’ve built businesses, scaled globally, failed fantastically and learnt massively. This Much I know summarizes not just what our guests share but hopefully what collectively, as a community, we can provide to further our own knowledge from those who’ve been there, done that and, most importantly, survived to tell the tale.
We look forward to bringing you even more content in 2017 and, as ever, we’d love to hear your feedback. So, if there’s a topic area you’d like us to explore, a founder story you’re keen to discover or a personal story you’d love to share, please get in touch… and now onto who our first guest of the year was!
Big data, argues Kenneth Cukier, senior editor for data and digital at The Economist, is epoch defining: the ability for humans to store and transmit information at a scale previously inconceivable will transform ‘how we work, live and think’ — much as fire, bronze and the paper press revolutionized earlier societies. But how should we respond to the economic dislocation AI will produce in conjunction with big data?
Kenneth’s career in journalism is a distinguished one. The co-author of the New York Times Best Seller “Big Data” (2013) he manages new digital product development and oversees data analytics for The Economist. Prior to this, Kenneth served as technology editor of the Wall Street Journal Asia and also worked at the International Herald Tribune in Paris. In 2002–04 he was a research fellow at Harvard’s Kennedy School of Government.
During our chat, Kenneth shared that information has gone from ‘a stock to flow’. Instead of being stored in fixed media — such as clay discs 4,000 years ago — data is now liquid and dynamic. The application of machine learning techniques and algorithms to such data lets us do things once impossible, such as build self-driving cars or diagnose diseases at a far earlier stage. But, he cautions, ‘it is the mark of an unwise society’ and close to criminal that we are not properly sharing data in spheres such as healthcare.
Take a Listen to understand how we can learn from the information we collect, what change needs to materialize before we feel AI’s effect in proper, and how to respond to the job displacement that AI will bring about.
Back in the pre-iPhone era, investors would rally around the word ‘mobile’ as the ‘next big thing’. It was clear that mobility and doing things on small-screen devices would affect the lives of many for years to come, but what wasn’t clear was how. How were applications going to get smart enough to add value on the go? How were web standards going to evolve fast enough to accommodate all the different kinds of devices available in the market? Which platforms across the myriad of non-compatible platforms (Symbian, WinCE, RIM, Java etc), should developers invest their time?
What happened, we all now know as history… the iPhone set the bar for mobile devices and subsequently also created the app experience to enable walled-garden brand experiences, services, and products. Over the subsequent years, frameworks, APIs and other building blocks were built that enabled the quick development of apps and web apps to create the responsive and app-economy we all now take for granted as part of the offering for any new startup/service at launch. Two major platforms have created the landscape of mobile, iOS and Android, and everything else is mostly now built on that.
‘A vehicle for enablement that will be part of our daily lives in the very near future’
I believe the same is bound to happen with AI. In many ways it is tempting to think of it as a ‘standalone’ sector. However, in spite of the attention it is getting as one in the short term, I don’t believe it is in the long term. Rather, like mobile, it is fundamentally a vehicle for enablement that will be part of our daily lives in the very near future. As such, where the real development will take place will be in different verticals that will be disrupted or enhanced as part of AI’s evolution; the data sets, the algorithms, sdk’s and api’s becoming widely available, and a few major platforms, perhaps those being created by the likes of Google’s, Microsoft, IBM’s, or Amazon’s will become the foundation for the industry, similar to how iOS and Android dominated in the mobile space.
Our investments in companies using AI
At Seedcamp, we’ve been working on investing in companies across the value chain that are changing different sectors. In how to identify theft risk, we’ve backed Third Eye, which allows security staff, augmented with computer vision, to identify threats. We’ve backed Viz.ai,which allows doctors to detect anomalies in ultrasound scans far faster than would normally be possible. We’ve backed Beagle who are changing the legal landscape by identifying risk areas within legal circumstances as well as companies like AiBuild who are using a combination of computer vision and machine learning techniques to increase the accuracy and robustness of 3D printing robots. We’ve backed a couple of stealth companies (for now) in the cybersecurity space that are working on identifying network level attacks as well as transactional attacks within a company’s infrastructure. We’ve invested in companies that automate business processes such as UIPathand, lastly, we’ve backed companies that own and manage large data sets which companies will rely on for their AI-based tools in the future.
While at the moment we are finding our personal experiences with AI enhanced through first version services such as Siri/OK-Google/Amazon Echo (virtual assistant), chatbots e.g Facebook, Hedge funds/high frequency trading, cyber security — ie darktrace, OCR (optical character recognition), we believe we are just at the very beginning of this revolution, with far more daily tool integrated services to come.
These services will just get better and better as we rely more and more on algorithms which squeeze out the inefficiencies in our human-based decisions and will deliver us a far more personalized experience in our day-to-day lives than any of the current generation products/services can offer.
Want to learn more about AI? Attend our event in partnership with Northzone on 23rd November to hear more from experts in this space and pitches from startups applying artificial intelligence to their businesses.