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2 years ago
12 Amazing Deep Learning Breakthroughs of 2017


Originally published in Forbes, Feb 5, 2018

For today’s leading deep learning methods and technology, attend the conference and training workshops at Deep Learning World Las Vegas, June 3-7, 2018.  

The quest to give machines a mind of their own occupied the brightest AI specialists in 2017. Machine learning (and especially the newly hip branch, deep learning) practically delivered all of the most stunning achievements in artificial intelligence so far — from systems that beat us at our own games to art-producing neural networks that rival human creativity.

At the onset and in hindsight, experts have heralded 2017 as “The Year of AI”. Here are a dozen  deep learning breakthroughs from the past year that validate the claim

1.  DeepMind’s AlphaZero Clobbered The Top AI Champions In Go, Shogi, And Chess

Following its stunning win over the best human Go player in 2016, AlphaGo was upgraded a year later into a generalized and more powerful incarnation, AlphaZero. Free of any human guidance except the basic game rules, AlphaZero learned how to play master-level chess by itself in just four hours. It then proceeded to trounce Stockfish (the top AI chess player) in a 100-game match — without losing a single game.

2.  OpenAI’s Universe Gained Traction With High-Profile Partners

Aiming for the field’s holy grail (a “friendly” artificial general intelligence), Universe is a free platform where developers can train an AI agent via reinforcement learning across disparate environments such as websites, applications, and games. Released in December of 2016, the platform gained traction in 2017, with partners such as EA, Valve, and Microsoft Studios jumping at the chance to allow Universe AI agents to roam across and learn from their games.

3.  Sonnet & Tensorflow Eager Joined Their Fellow Open-Source Frameworks

Google launched TensorFlow as an open-source machine learning library in 2015, followed by  Magenta (an AI platform for creating art and music) a year later. In 2016, Facebook AI released PyTorch, a python deep learning platform supporting dynamic computation graphs, which Google matched eagerly with the release of Tensorflow Eager. In 2017 and through its AI subsidiary DeepMind, Google released Sonnet, an open-source framework that makes it easier for developers to build neural network components.

4.  Facebook & Microsoft Joined Forces To Enable AI Framework Interoperability

The tech giants — with the help of partner communities (including AWS, Nvidia, Qualcomm, Intel, and Huawei) — developed the Open Neural Network Exchange (ONNX), an open format for representing deep learning models that also allows models to be trained in one framework and transferred to another for inference.

To continue reading this article in FORBES, click here.

About the Author:

Mariya Yao is the Chief Technology Officer and Head of Research & Design at TOPBOTS, a strategy and research firm for applied artificial intelligence and machine learning. They educate executives and entrepreneurs on breakthrough emerging technologies and help them successfully deploy them in their enterprises. Read her  book at

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