Reinforcement learning

On 10 and 11 April 2018, Mark Zuckerberg, the founder and chief executive of Facebook went through a two-day congressional testimony in the U.S. (Cecilia Kang et al., “Mark Zuckerberg Testimony: Day 2 Brings Tougher Questioning“, The New York Times, 11 April 2018). The questioning followed the scandal involving Facebook and Cambridge Analytica, … Continue reading Big Data, Driver for Artificial Intelligence… but Not in the Future?

This article focuses on Deep Learning, the sub-field of Artificial Intelligence that leads the current exponential development of the sector. As we seek to envision how a future AI-powered world will look and what it will mean to its actors, notably in terms of politics and geopolitics, it is indeed fundamental to first understand what is AI.
We shall first give examples of how Deep Learning is used in the real world. We distinguish two types of activities: classical AI-powered activities and totally new AI-activities, related to the very emergence of DL. In both cases we shall point out their revolutionary potential.
Then, we shall take a deeper dive in the world of Deep Learning, taking as practical example the evolution of Google’s DeepMind AI-DL program initially developed to win against human Go masters: AlphaGo, then AlphaGo Zero and finally AlphaZero. After briefly presenting where DL is located within AI, we shall focus first on Deep Neural Networks and Supervised Learning. Second we shall look at the latest evolution with Deep Reinforcement Learning and start wondering if a new AI-DL paradigm, which could revolutionise the current dogma regarding the importance of Big Data, is not emerging.