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February 2, 2017
By Anita Schjøll Abildgaard
literature reviewiris aiscithonresearch assistant

Helping researchers at the Helsinki Challenge

Helping researchers with problem validation at the Helsinki Challenge

Recently we were asked ‘what are the happiest moments in an entrepreneur’s life?’ For us at Iris.AI, one of the ways we experience those moments is when we are able to watch researchers finding something useful with the AI tool we built.

This is why the past two days have been so special.

We organized a two-day Science Hackathon, or Scithon as we call it, in collaboration with Helsinki Challenge for a group of 40 researchers working to solve major global problems. The Scithons help R&D focused companies and research institutions address their scientific research challenges in a compressed time frame. 

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One of the things that sparked our enthusiasm to work with the Helsinki Challenge is their mission. Working off of the framework of the UN’s 2030 Agenda for Sustainable Development, the Challenge focuses on three major themes; Sustainable Planet, Urban Future and People in Change. Partly idea accelerator, partly science-based competition, the Helsinki Challenge helps the 20 teams working on reaching the SDGs to pull off their projects.

Over the course of the week, we met over a dozen brilliant teams dedicated to finding solutions to societal issues like access to diagnostic healthcare services, eliminating malaria, addressing loneliness and isolation in youth and creating eco-friendly textiles for the growing population.

The Helsinki Challenge teams used Iris.AI to conduct multidisciplinary research and explore the connections of different fields.  Some teams found new topics and concepts that they might not have not initially thought of.

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Here’s what a few of the teams had to say about using the tool.

“I do a lot of multidisciplinary research and don’t always know the keywords for those topics or industries.  Iris.AI showed me concepts that might not be intuitive and I was able to get a bigger picture of the topic.” — Reconfigure Mobility

“I like the way the results are presented, it’s great. The data map is very appealing”  — Futurena

“I like that I can input a larger block of text, rather than just a few keywords, when searching for relevant articles” — Heatstock

The research teams weren’t the only ones who learned a lot this week. We did too!  

The Helsinki Challenge teams gave us valuable feedback about the product and the user experience. It’s also clear that Iris.AI still has a lot to learn!

Lastly, we learned that these teams aren’t just researchers and scientists, they are also social entrepreneurs. And for most entrepreneurs, there is great joy in seeing your creative solution come to life.

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We wish these teams the best in their scientific, entrepreneurial problem-solving journey and hope that each of them gets to experience their own moment of happiness.

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