
Just over a week ago, I was in Amsterdam for the inaugural European Machine Intelligence Summit with Re•Work. It was a real honour to be compere for Day 2 of the Machine Learning in Autonomous Vehicles Summit, which was run alongside with the Machine Learning Summit.
I started my own short talk on Day 2 with Uber. It is hard to talk about autonomous vehicles or the data around them without mentioning Uber. For me, it is a great example of the fact that, as consumers, we can be very engaged with a product or service, whereas those who are seeing their jobs displaced, such as traditional taxi drivers, don’t feel the same way about Uber’s disruptive business model.
I believe that this will be a common theme as we see a rise in autonomous vehicles and AI technology. For all the good that they will bring, they will also bring disruption. How we deal with the opportunities that disruption creates will be the defining factor as we transition to a more autonomous driving and car ownership experience. And that is all done to having an effective and highly agile Operating Model.
What is happening right now in Machine Intelligence?
As well as being compere, I was behind the scenes at both Summits and got to catch up with peers and speakers to hear their perspectives on Machine Learning technology and what is to come. Here is a quick round up of who I spoke to and their thoughts.
Intelligent shopping delivered to your door
From the Machine Intelligence Summit I was thrilled to get the chance to speak to Daniel Gebler of Picnic. Picnic, a Dutch company, have built a supermarket shopping app with a machine learning algorithm which can predict your shopping needs with 95% accuracy. It then delivers your shopping using full electric vehicles on pre-defined routes at certain times every few days, much like the milkman once did. Picnic has just raised €100m in its series B funding, more than Uber.
Machine Intelligence will drive Operating Models and hence also Business Models
I also met Carlos Eduardo Espinal of Seedcamp. Seedcamp is Europe’s first seed fund, identifying and investing early in world-class founders building valuable, global businesses using disruptive technology. They have invested in over 240 companies since launch in 2007 and Carlos is an expert in helping startups set fundraising milestones, and find product-market-fit.
Carlos and I talked at length about AI and Operating Models and how the two will interact in the future. Carlos feels that AI is the key to enabling the Operating Model of a business. This will then, in turn, ultimately be what will drive the Business Model. So AI can empower an Operating Model by making it more agile. I will be writing another blog on our conversations soon, with an in-depth look at Carlos’ perspectives, given his role as an investor with exposure to so many early-stage AI technologies.
Data is still key
Tijmen Blankevoort is co-founder and CTO of Scyfer, a spin-off company from the University of Amsterdam specialising in bringing Artificial Intelligence to business. They are working on an AI programme called Vera which can learn image recognition with current applications in the steel and healthcare industries, but of course there will be many more applications, so it will be very interesting to see how this startup can scaleup.
Tijmen spoke about the importance of the data used in developing AI like Vera. He estimates that 80% of the project is gathering the data and mapping the process that will be used. Tijmen believes that AI like Vera can really change the Operating Model of a business through economies of scale. Rather than presenting AI as something that will take jobs, he sees the key to the adoption of AI as a focus on its role in improving processes and allowing people to better own their domain. This will enable people to be more efficient and effective. It will empower people.
Banks are changing
It was also great to meet Dor Kedem, Lead Data Scientist from ING. Banks are a rich source of data but there are a variety of reasons, including regulation, why most large banks haven’t used the data to create new products or innovate in this very traditional sector. Dor spoke of ING’s mission to end this trend and shape up to be a truly forward-looking bank. ING has made the shift from servers to virtual machine cluster warehouses. This increased agility in resource allocation has meant that ING has been able to begin the process of cost reduction on their infrastructure, and reduce technical debt, although this has yet to be fully realised. ING also see the PSD2 regulation where much of the bank’s data will be in an Open API environment and much more accessible to customers as a great opportunity for change and to improve the customer experience. I will also take a look into ING’s highly agile operating model, where people are motivated, working in tribes and enjoy learning, because of ING’s investment in them and building their capabilities – in order to help the organisation succeed overall.
Autonomous Vehicles projects are here
At the Autonomous Vehicles Summit, EasyMile presented their autonomous project. Using small people shuttles in closed environments EasyMile has worked with the likes of Singapore’s Gardens by the Bay and the Waterfront in Darwin, Australia. Focusing on ‘last mile’ technology, and bringing fleet maintenance and software deployment into their business model, EasyMile is bringing autonomous projects to our streets right now.
Learning to drive tech for an autonomous future
Indra den Bakker, Deep Learning Engineer & Founder of 23insights and a Udacity Mentor, spoke about his current project. He has helped to create a nanodegree for Udacity to bring knowledge of this important autonomous vehicle technology to a wider audience. Co-created with the likes of Uber, BMW, Mercedes, McLaren and others, the course brings autonomous vehicles and the skills needed to develop for them to a new and wider audience. There is no doubt that in order to continue to grow and use autonomous vehicle technology in the future we’ll need more skilled engineers.
Increasingly in our fast changing digital economy, engineering and technology has such an important capability, it can certainly play a major role in a business’s future. What’s important is not necessarily how cool the technology is, as that’s what makes it a shiny object only, but in what purpose the engineering and technology serves, that is what is the value-add delivered to customers through the service offered by a business, and how the capability supports the Operating Model of the business in delivering the services. At the RE•Work summit, there was certainly an abundance of potential, which I hope become reality.
Thanks to Re•Work for their support in organising the interviews and for running a great event.