NEWS & TECHNOLOGY ARTIFICIAL INTELLIGENCE
Synthetic data to the rescue of AI
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.
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
The two elephants in the room taming AI’s promising future.
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.
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
“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.
Discussing synthetic data, Behzadi describes
it as computer-generated data that
mimics real data.
A simple example Neuromation puts
forward on its website is the creation of
huge data sets for object or facial recognition,
based on computer-generated images
where objects and faces can be rendered
very realistically and manipulated to create
endless variations in sizes, shapes, colour,
light exposure, viewing angles and so forth.
All that data comes readily labelled for robust
and accurate object classification, at a fraction
of the time and cost needed for a human
operator to sort and create specific data sets from acquired
photos. Neuromation also sees robotics as a promising sector,
where fully simulated environments can be more effective to
train industrial robots at real world tasks.
According to Behzadi, with synthetic data,
companies only need 50% of their original, authentic
training data to finish the formal training
of their algorithms. The CEO argues that some
AI applications such as object recognition
could even be trained almost exclusively with
synthetic data, cutting out on lengthy and
expensive human labour.
“As a natural roadmap, we started with
image data which is simple to model. We
have industry experts in CGI effects working
together with deep learning experts to improve
our models. The next level of complexity will be
to create dynamic data. Where the physics are
known, you can create generalized models”,
Behzadi explained eeNews Europe.
Neuromation’s CEO Yashar Behzadi.
The Neuromation platform: an AI market place.
10 News September 2018 @eeNewsEurope www.eenewseurope.com