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Frontiers partners with machine learning challenge platform AIcrowd -

Frontiers has announced a partnership with machine learning challenge platform AIcrowd. The deal is expected to transform crowd-sourced solutions to machine learning challenges into peer-reviewed, open-access articles.

Used by organisations like Google, Unity, and Stanford University, AIcrowd’s machine learning platform is having a real impact on the artificial intelligence research landscape while solving real-world problems. As a result of this new partnership with Frontiers in Artificial Intelligence, its innovative, crowdsourced solutions will now reach a wider audience as freely available, peer-reviewed article collections.

The platform, which started life as crowdAI in Salathé’s digital epidemiology lab at EPFL, helps universities, businesses, government agencies, NGOs and IOs to run and manage their machine learning challenges. Its transformation from university lab idea into fast-growing company is the result of increasing demand from key stakeholders and engagement by a global research community.

One of the platform’s most successful research challenges was ‘Learning to Run’ by Stanford University, in partnership with University of California Berkeley and EPFL. Participants were tasked with developing a controller that would enable a physiologically-based human model to navigate a complex obstacle course as quickly as possible.

Another successful challenge was by the aid organisation Humanity & Inclusion, exploring how machine learning could generate relevant and real-time maps to support disaster relief efforts. Participants were provided with a dataset including individual tiles of satellite imagery, with the goal of training a model which, given a new tile, could annotate all the buildings within it. The solutions submitted were extremely promising and the best ones are now being studied and prepared for future production.

In order to better manage the increased demand, the team that developed crowdAI incorporated AIcrowd in Novermber 2018. The platform was built on open source principles, with data from challenges available online, and this remains one of its core pillars.

The partnership with Frontiers in Artificial Intelligence takes this Open Science approach a step further, turning challenge solutions into peer-reviewed, open-access articles.

Under the collaboration, each year the best solutions from select AIcrowd challenges will be published for free as peer-reviewed articles in Frontiers in Artificial Intelligence, forming a special collection of ‘challenge papers’ edited by Salathé together with Diego Perez Liebana (Queen Mary University of London) and Lukasz Kidzinski (Stanford University).

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Click here to read the original press release.


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