Mads Ingwar - The art of simplicity

Mads Ingwar - The art of simplicity

Læs Interviewet på Dansk

Mads Ingwar holds a PhD in Machine Learning and Data Science. Being an entrepreneur and angel investor, his companies focus on developing self-learning algorithms, including those used in self-driving cars and in systems created to detect credit card fraud.

He grew up in the village of Skelhøje in Central Jutland. His childhood home, a smallholding built from fieldstone, allowed him and his family to both cultivate their own vegetables and keep sheep and horses. Mads admits to always having been a computer geek, and from an early age became interested in algorithms and what they can achieve. 

"For me, it is important to work with companies that are interested in making a difference. Nowadays, it is actually possible to change the world for the better using the data we have access to, whether it is about reducing pollution or giving people better pension returns. It's important for me to help push that development along. That is my drive," Mads says.

 

FROM MICRO TO MACRO 

When Mads graduated, the development of AI and Machine Learning was still in its formative years. He focused on Computer Vision for processing CCTV data (surveillance cameras in public spaces), as he came to realise that the material the cameras collected could not only be used to detect crime, but also for municipalities, cities and shops to use the data to observe people's pattern of movement and base this information on how to best carry out everyday matters - including measuring bike paths, how areas are used, and how many people are needed in a specific workplace at certain times of the day.

“When it comes to this kind of data, we have gone from micro to macro. Just the other day, I saw a group of men in yellow vests who were counting the amount of road users on Knippelsbro, and today we can do the very same thing with much more accuracy using the data we can collect" says Mads Ingwar.

“Using the algorithms, we are able to determine exactly how many bikes, mopeds, and cars are on the roads, and by doing so we can, among other things, see that there is a big difference between reality and public perception of the traffic in Copenhagen," he says. 

“Data is the new gold. Today, all companies rely on their IT systems and a ”byproduct" of this is data. There are millions of terabytes data waiting to be used. Right now, it is being wasted away in silos, and everyone is aware of its value, but very few have the actual skill sets to exploit it. Google and Facebook are good at it. They know everything about you. That is what makes them great at keeping customers, and one of the reasons that they can charge higher prices for their services," he says.

MINIMISING YOUR CHOICES

Mads Ingwar’s approach has always been to simplify and streamline.
"Whether I'm dealing with a big pension business, to invest a lot of millions, or a small start-up company, to me it is important, that you can make use of these large amounts of data and create new insights that save both time and money. Time and money that can be spent or invested in other ways. That's what I like about my shirts from LOOW," he says. 

“I’m not very good at - or interested in - buying things, and the things I do buy need to deliver what I expect from them. In my wardrobe you will find four t-shirts, four shirts, and two suits, and I love the idea of wearing my favourite clothes every day. 

We make many choices every single day, and a lot of the time we have made 30 decisions before we make it out of the door in the morning. That is why I love not having to worry about making choices when it comes to my clothing - and I am a big fan of being able to wear a LOOW-shirt under a blazer for a meeting, and when I'm going climbing. This makes perfect sense to me.”

 

Mads is a co-founder of Sentia.ai and Managing Partner of Think Big Analytics. He is an Angel Investor with focus on AI and Machine Learning.

Text: Andrea Bak
Photo: Henning Hjorth

Mads is wearing our LOOW long sleeve T-shirt, Ocean - Large (188cm/ 80kg)