$20亿用于美国国防的下一代人工智能 - 信号

对问题和不确定性的影响

临界不确定性➚➚➚ 扰乱了目前私人和公共行为者的人工智能力量竞赛--美国在竞赛中取得了非常严重的领先。
➚➚  人工智能的加速扩张
➚➚  人工智能世界的加速兴起
➚➚ 看到美国在人工智能力量竞赛中巩固其领先地位的几率增加。
➚➚ 不断升级的人工智能力量竞赛,特别是在美国和中国之间。
➚➚ 世界其他地区追赶的挑战不断上升
紧张局势升级的可能性 美中之间,包括人工智能行为者之间的关系 […]

当AI开始创造AI时--人工智能与计算能力

2018年可能是美国凭借世界上最强大的超级计算机夺回对中国的领先地位的一年。这可能是人工智能--计算能力的战争开始的一年。2017年是人工智能开始创造人工智能(AI)的一年。这一年,中国超越了美国 ...

★人工智能--力量、驱动力和利害关系

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 …

人工智能和深度学习--正在形成的新人工智能世界

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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