Making AI algorithm development cheaper, faster

August 22, 2018 // By Julien Happich
With synthetic data, Estonia-based AI startup Neuromation promises to make organized data sets a breeze to access for AI training, with plentiful variations and built-in robustness.

In the booming world of artificial intelligence and deep learning, Neuromation's CEO Yashar Behzadi sees two large elephants in the room that could tame the adoption rate of AI, one is the shortage of data scientists and the other is the shortage of properly organized datasets to train neural networks for specific tasks.


Neuromation's CEO Yashar Behzadi.

It is not just the mechanics of creating neural networks that can be challenging, but data scientists must also organize and label training data so that each algorithm will be properly trained on its assigned tasks. Even for companies with enough data scientists on staff, this can make machine learning time-consuming and impractical.

Aiming to solve these two issues, Neuromation's ambition is to create a community of AI developers, connecting them to several ecosystem partners such as data providers and service providers around a unique blockchain-enabled AI market place, along with shared tools to develop and train algorithms, including the use of synthetic data sets.


The Neuromation platform: an AI market place.

With its Neuromation platform, Behzadi wants to make it ten times cheaper and faster to develop AI algorithms than it is feasible today, making it easier for AI developers to connect with their customers or technical experts.

"There are about six million software developers who want to implement AI in the next 12 months, we want to empower those folks" the CEO told eeNews Europe over a phone interview, noting that a recent study from Tencent revealed that there are just 300,000 AI developers and other AI professionals worldwide, unable to fill the surging demand for new AI applications.


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