Is Europe a Leader or a Follower in the AI Revolution?

deevio’s CEO and co-founder Donato Montanari explains how Artificial Intelligence and Deep Learning work, how different markets and industries apply them in different ways and why Europe is the place to be for an AI company like deevio.

In today’s world, Artificial Intelligence is surrounding us everywhere. Could you give a short definition and explain why there is such a hype about AI?

AI is a very general term. It refers to decisions made by machines. What is fairly new in the realm of AI, and has been particularly successful in the last 10 years, is the concept of Machine Learning: the machine is not just making a decision, but it is learning through the decisions it makes. There are several ways to implement Machine Learning but one of the most successful ones is Deep Learning.

Deep Learning refers to algorithms trying to replicate the structure of the brain. All of this has happened very recently because of the incredible breakthrough in computing power.

And in which contexts and industries can AI and Deep Learning be applied?

Anytime you have an important breakthrough in technology, you try to apply it everywhere. The same has been happening here. Every market and every industry is trying to figure out how this technology can be helpful. The consumer industry is being the one driving this process in a lot of areas. For instance, when we speak into our phone and the phone translates what we say into text, that’s Deep Learning. And what we observe in this respect is that, when you start doing this, it’s not very accurate. You have to repeat the words and the sentences, and it makes a lot of mistakes. But the more you use it, the more accurate it becomes because it learns how you speak. This is probably the most prolific example of Deep Learning because everybody uses it. And that’s why it gets better and better so fast. Therefore, the companies with the best software in this field are the ones that have the most users giving them the data so they can train the software. This makes companies like Google, Apple, Microsoft and Facebook the key players on this market.

Who are the driving forces when we talk about AI on a global level? You already mentioned companies like Google and Facebook. So, it’s all about the data?

Let’s break it down. The fundamental science behind AI and Deep Learning is old. Then you have the technological implementation — the computer power — which is very recent. And the most important part is the data. So, the questions are: Who has the data? How do you use the data? And what kind of regulations, if any, are on the data? If you were to look at it globally for the consumer market, most of the data is where most of the people are. Which means that the countries where you expect Deep Learning to be more successful are the countries that are most populated. If you tried to measure it in terms of how broadly Deep Learning has been applied or in terms of how many patents a country has on the technology or how many papers have been written on the topic, China is way beyond everybody else because they have billions of people they can get the data from. This is the biggest advantage that China has in the consumer sector right now. And this tremendous advantage in demographic is coupled with a strong government policy allowing companies to do whatever they want with people’s data. The combination of a lot of people and no data privacy means that these machines can learn extremely fast.

So, what role does Europe play in the AI revolution, if any?

I think it depends on which market we focus on. In terms of population, we cannot compete with Asia. So clearly, in consumer-centric applications Europe cannot be the leader. Moreover, privacy is very important to Europeans and, especially in Germany, we are leading in privacy protection, which is a good thing in my opinion. Where I think we do have a chance to be the leader is in the manufacturing world. Europe was the first continent to be industrialized, so it’s really in our DNA to manage repetitive processes and to make the same thing millions of times all the same. We have the discipline for that. And most important: We know how to track it. If we now think in terms of data in the manufacturing industry, data that is pertinent to the production process, to quality control, to the output and to the incoming materials, then Europe is probably the continent where most of this data is stored. With the automotive industry in Germany leading the way, Europe has a tradition of process optimisation. Process optimisation relies on statistics and statistics relies on data. Which means that here in Europe we have a lot of data in the manufacturing world. Whereas China leads the consumer market because they have the consumer-related data, Europe could lead the manufacturing world because we have the manufacturing data. When it comes to applying Deep Learning, Machine Learning and AI in the manufacturing industry, Europe is the place to be. Take deevio for example. We do end-of-line quality control with Deep Learning and we think we are the best in the world at doing this. And we decided to do this in Berlin.

Why is Germany and especially Berlin an interesting location for you?

I was really impressed today when I saw this map of Saxony, which is not well-known for being a high-tech region, showing all the automotive companies situated there.

The density of factories in the Dresden-Leipzig-Chemnitz triangle is amazing. And that’s the same everywhere in Germany. That’s why in Germany: this is where the data is located. And why Berlin? Because once you have the data, you need people who can do something with it. People who can transform the raw data into actionable insights. And thanks to companies like Zalando and Spotify that are successful in the consumer sector, Berlin has these people: the data scientists. One of the reasons why we decided to start deevio in Berlin is to have access to this pool of talent because there are not many regions outside of China and the US where you can find experienced data scientists who are really top-notch. The combination of having the data and the data scientists in the same country is very powerful.