Deep learning and neural networks

Deep learning refers to an approach in machine learning, which aims at teaching machines to recognise abstract concepts based on large datasets. The leading edge currently is unsupervised machine learning, where the machine is left to make sense of the data on its own. Deep learning has made huge leaps in pattern recognition possible. Google Deepmind is one of the prominent companies utilising deep learning.

Why is this important?

For platforms deep learning offers the possibility to make sense of and recognise patterns from large amounts of data. Google provides an open source library called TensorFlow for this. Another benefit are the services that deep learning provides, such as voice recognition, chatbots etc. These can provide new functionality to the platform. On a broader view, the motivation is to use the deep learning to solve global problems.

Things to keep an eye on

The focus is now especially on unsupervised machine learning and “differentiable neural computers”, which can make sense of complex structured data. Examples of what deep learning algorithms such as the Google DeepMind can do range from lip reading to advanced translation to making sense of a metro map. One interesting development is making APIs to enable artificial intelligence algorithms to play games such as Starcraft and learn through it. This also means that artificial intelligence might be the future user of a platform. The big question then is will it benefit or exploit the platform.

Selected articles and websites

DeepMind has conquered games, London’s Underground and now it wants to help save the planet
Deep Learning Papers
Google’s DeepMind AI Said to Outperform Professional Lip-Readers
Zero-Shot Translation with Google’s Multilingual Neural Machine Translation System
Google’s AI creates its own inhuman encryption
Google DeepMind to Use Blizzard’s StartCraft II for AI Research Platform
Differentiable neural computers

Mikko Dufva

Research Scientist VTT Technical Research Centre of Finland Ltd
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