Human Compatible: Artificial Intelligence and the Problem of Control by Stuart Russell

Free download ebook format txt Human Compatible: Artificial Intelligence and the Problem of Control 9780525687016 MOBI DJVU


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  • Human Compatible: Artificial Intelligence and the Problem of Control
  • Stuart Russell
  • Page: 320
  • Format: pdf, ePub, mobi, fb2
  • ISBN: 9780525687016
  • Publisher: Penguin Publishing Group

Download Human Compatible: Artificial Intelligence and the Problem of Control




Free download ebook format txt Human Compatible: Artificial Intelligence and the Problem of Control 9780525687016 MOBI DJVU

A world-leading artificial intelligence researcher explains why uncontrolled superhuman AI represents an existential threat to humanity, and lays out a new approach to AI that will enable us to coexist successfully with increasingly intelligent machines In the popular imagination, superhuman artificial intelligence is an approaching tidal wave that threatens not just jobs and human relationships, but civilization itself. Conflict between humans and machines is seen as inevitable and its outcome all too predictable. In this groundbreaking book, distinguished AI researcher Stuart Russell argues that this scenario can be avoided, but only if we rethink AI from the ground up. Russell begins by exploring the idea of intelligence in humans and in machines. He describes the near-term benefits we can expect, from intelligent personal assistants to vastly accelerated scientific research, and outlines the AI breakthroughs that still have to happen before we reach superhuman AI. He also spells out the ways humans are already finding to misuse AI, from lethal autonomous weapons to viral sabotage. If the predicted breakthroughs occur and superhuman AI emerges, we will have created entities far more powerful than ourselves. How can we ensure they never, ever, have power over us? Russell suggests that we can rebuild AI on a new foundation, according to which machines are designed to be inherently uncertain about the human preferences they are required to satisfy. Such machines would be humble, altruistic, and committed to pursue our objectives, not theirs. This new foundation would allow us to create machines that are provably deferential and provably beneficial. In a 2014 editorial co-authored with Stephen Hawking, Russell wrote, "Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last." Solving the problem of control over AI is not just possible; it is the key that unlocks a future of unlimited promise.

Human Compatible: Artificial Intelligence and the Problem of Control
Human Compatible: Artificial Intelligence and the Problem of Control: Stuart Russell: 9780525558613: Books - Amazon.ca. Human Compatible: Artificial Intelligence and the Problem of Control
Human Compatible: Artificial Intelligence and the Problem of Control: Stuart Russell: Amazon.com. Human Compatible: AI and the Problem of Control (Audio Download
Human Compatible: AI and the Problem of Control (Audio Download): Amazon. co.uk: Stuart Russell, Penguin Audio : Books. The rise of robots: forget evil AI – the real risk is far more insidious
The Center for Human-Compatible Artificial Intelligence, launched this week with but the machine might then hack into the traffic light control system so that all of the “The problem isn't consciousness, but competence. Human Compatible: Artificial Intelligence and the Problem of Control
Compre Human Compatible: Artificial Intelligence and the Problem of Control ( English Edition) de Stuart Russell na Amazon.com.br. Confira também os eBooks   Controlling Artificial Intelligence
We are several breakthroughs away from having superhuman AI, human- compatible AI – meaning AI that is compatible with human By and large the field has not spent time thinking about the control problem,” he says,  Bibliography - Center for Human-Compatible AI
Preference inference - Building AI systems that learn what humans want. Moral theory - Moral issues that HCAI systems and their developers might . (2) Human -level control through deep reinforcement learning, Mnih et al.



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