In The Pocket and RoboVision are rolling out an ambitious project named Alltag. Currently in MVP mode, we joined forces with Vluchtelingenwerk Vlaanderen to enroll refugees in the go-to market of this top tier technology.
The idea behind Alltag is to develop a platform that connects the demand for AI models with the labour market in a very flexible way. The demand for artificial intelligence models is skyrocketing. Just think about the development of self-driving cars, virtual assistants, frictionless stores… It is state-of-the-art technology, but there’s a major bottleneck in the AI industry: neural networks need to be trained. That’s where the human factor comes into play.
To do this, you’ll need to ‘feed’ your model data with the desired labelled data. The market of data and AI is huge and a lot of startups are jumping on the opportunity of improving the quality of data by employing humans to train the models.
"AI and deep learning will have an enormous impact on our lives and on how we work. The data economy can bring with it enormous benefits but only if the human factor is taken into due consideration in the development of deep learning platforms. We feel that a partnership made a lot of sense; reinforcing our AI knowhow with In The Pocket's digital product and platform expertise"
Together with RoboVision we’ve created a tool that helps with the tagging and semantic labelling of data. By using deep learning, this tool can recognise specific plant types and parts. The human link in the development of this technology is indispensable, but it’s not always easy to find people who can help. Data labelling isn’t hard, everyone can do it with the right guidance. Alltag’s product vision is unique in the sense that we are building a decentralised platform to guarantee that the people working on it are treated fairly and receive fair pay.
With that in mind we approached Vluchtelingenwerk Vlaanderen. Refugees are ideal beta testers for this product because the market is very international. And the actual work of structuring data is easy-to-learn, language-independent labour that can be done remotely.
With the support of Vluchtelingenwerk Vlaanderen we recruited refugees to help with the data labelling. Anyone who starts using the application will see images on which he or she has to designate certain things. For example, you are asked to mark the stem of a plant so the technology can be used in plantations to plant stems automatically with robots.
The touchscreen allows you to work very precisely, which is ideal for making accurate markings. As soon as the platform has sufficient markings, deep learning can look for patterns so that in the future these markings can happen without human intervention.