With a unique innovation ecosystem that is 8,000 start-ups, 1,300 research laboratories and 162,000 researchers strong, Paris Region intends to play a major role in the development of new technologies based on artificial intelligence.
 
The initiative of this unique and exceptional challenge is part of this ambition: by targeting companies in the Paris Region and those wishing to set up on its territory, Paris Region wants to promote the digital performance of its economic stakeholders, consolidate its excellence on an international scale and its position as Europe’s leading AI hub
 
The Paris Region AI Challenge 2018 is open to startups that offer solutions based on Artificial Intelligence and aimed at the international market.
 
To take part in this challenge, you must meet the eligibility requirements that can be found in the official rules. Our challenge is targeted at:
  • Startups created less than 5 years ago
  • Established permanently in the Paris Region or committed to establishing in the next 6 months
  • That have raised less than €500,000 in funds
 
ON WHICH CRITERIA WILL YOU BE ASSESSED?
  • Project maturity
  • Innovative, disruptive and differentiating potential of the solution
  • Social impact / Progress for the community offered by the solution
  • Relevance and robustness of the business model
  • Assessment of the founding team (vision, complementary skills, ability to deliver, core skills, references…)
 
The deadline for the submission: 17 June 2018 11:59 PM
 
Source: The Paris Region
 

Illustration Photo: Small VNIR hyperspectral camera can show for example raw avocados from ripe. VTT Technical Research Centre of Finland has developed a highly cost-efficient hyperspectral imaging technology, which enables the introduction of new artificial intelligence applications into consumer devices. Spectral filtering technology takes advantage of the very-near-infrared (VNIR) wavelengths, which even low-cost mobile phone cameras can detect. Artificial intelligence can be used to interpret this environmental spectral data within images, which is not visible to the naked eye. (credits: VTT Technical Research Centre of Finland / Flickr Creative Commons Attribution-NonCommercial-NoDerivs 2.0 Generic (CC BY-NC-ND 2.0))

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