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After DeepMind’s breakthrough, there’s no reason why a robot can’t ultimately use some variant of deep reinforcement learning to teach itself to walk… - Max Tegmark
" "After DeepMind’s breakthrough, there’s no reason why a robot can’t ultimately use some variant of deep reinforcement learning to teach itself to walk without help from human programmers: all that’s needed is a system that gives it points whenever it makes progress. Robots in the real world similarly have the potential to learn to swim, fly, play ping-pong, fight and perform a nearly endless list of other motor tasks without help from human programmers. To speed things up and reduce the risk of getting stuck or damaging themselves during the learning process, they would probably do the first stages of their learning in virtual reality.
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About Max Tegmark
Max Tegmark (born May 5, 1967) is a Swedish-American physicist, cosmologist and machine learning researcher. He is a professor at the Massachusetts Institute of Technology and the scientific director of the Foundational Questions Institute. He is also a co-founder of the Future of Life Institute and a supporter of the effective altruism movement, and has received research grants from Elon Musk to investigate existential risk from advanced artificial intelligence.
Biography information from Wikiquote
Also Known As
Alternative Names:
Tegmark
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Max Shapiro
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Max Erik Tegmark
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The Matrix, Agent Smith (an AI) articulates this sentiment: “Every mammal on this planet instinctively develops a natural equilibrium with the surrounding environment but you humans do not. You move to an area and you multiply and multiply until every natural resource is consumed and the only way you can survive is to spread to another area. There is another organism on this planet that follows the same pattern. Do you know what it is? A virus. Human beings are a disease, a cancer of this planet. You are a plague and we are the cure.
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A great way for a particle arrangement to further this goal is to make copies of itself, to produce more energy absorbers. There are many known examples of such emergent self-replication: for example, vortices in turbulent fluids can make copies of themselves, and clusters of microspheres can coax nearby spheres into forming identical clusters. At some point, a particular arrangement of particles got so good at copying itself that it could do so almost indefinitely by extracting energy and raw materials from its environment. We call such a particle arrangement life.
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