Deep learning, prefabricated

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Why major companies are ahead of the curve

Igor Susmelj and Heiki Riesenkampf are technological development workers. With their product, they enable low-threshold access to deep learning methods without having to rely on tech giants such as Google or Microsoft. These companies have an enormous advantage when it comes to deep learning – they have long been processing huge amounts of data that they can use to train their models. For complex applications such as the development of driverless cars, millions of images and thousands of hours of video are required. Deep learning also demands a high level of computing power, because the parameters often have to be trained over several days. Mirage uses open-source data and research platforms for its models.

A platform for pioneers

The two young entrepreneurs have already invested a lot of time, money and energy into Mirage – but have not yet earned anything. They have both kept afloat with a variety of jobs, which has been working well: “In the software field, you don’t need a lot of infrastructure or to be in a particular place,” says Susmelj, who comes from Lucerne. They are also able to use ETH’s community working spaces for start-ups and spin-offs at favourable conditions, though Susmelj finds the network he has developed thanks to ETH more important. “It is extremely helpful,” he says.

Of course, he next wants to move beyond this “student mode” and earn money for his work. Mirage is currently relying on companies’ interest in experimentation: “Many companies want to try out new technologies,” he says. The basic features are currently available free of charge on the platform. In this way, Mirage aims to develop a customer base that will raise awareness of the solution and then later be willing to pay for new products and services.

Source: ETH Zurich