Critical Uncertainty ➚➚➚ Disruption of the current AI-power race for private and public actors alike – The U.S. takes a very serious lead in the race. ➚➚ Accelerating expansion of AI ➚➚ Accelerating emergence of the AI-world ➚➚ Increased odds to see the U.S. consolidating its lead in the AI-power race. ➚➚ Escalating AI-power race notably between the U.S. and China. ➚➚ Rising challenge for the rest of the world to catch up ➚ Potential for escalating tension U.S. – China, including between AI actors […]
2018 could be the year when the U.S. takes back the lead over China with the most powerful supercomputer in the world. It could be the year when the AI-power war over computing power started. 2017 is the year when Artificial Intelligence started creating Artificial Intelligence (AI). It is the year when China overtook the US …
Here we shall present the drivers and forces behind the current exponential development of Artificial Intelligence (AI). Deep Learning, a sub-field of AI, leads this expansion, as we explained in “When Artificial Intelligence will Power Geopolitics – Presenting AI” (open access) and in “Artificial Intelligence and Deep Learning – The New AI-World in the Making” (semi-open …
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.
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