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Machines won't have I/O bottlenecks, they won't have limited lifespans, won't need to wait for years to reach maturity. If an artificial general intelligence b

Machines won't have I/O bottlenecks, they won't have limited lifespans, won't need to wait for years to reach maturity. If an artificial general intelligence becomes as intelligent as Albert Einstein or John von Neumann, then the time required to produce a copy would be almost nothing compared to the 20+ years required for a human. Imagine that instead of talking you are able to copy parts of your brain and sending them to other humans. This is what AI will do... just serializing large trained models and sending them around. We are no match for an artificial general intelligence. Imagine competing against a country where once one person becomes good at some skill, then everyone instantly becomes good at that skill. That will be what competing against machines will be like.

deleted 6y ago
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lasagnaphil 6y ago
From a grad student's point of view who currently uses "deep learning" to solve problems, we're nowhere near that kind of general intelligence. Neural networks are very good at approximating various kinds of functions given lots of redundant training data, but they have never shown the flexibility of actual human brains (as in creating new neural connections with only sparse experiences, along with deductive/symbolic reasoning). To really mimic human brains, we first need to know quantitatively how our neurons communicate with each other and form connections in our brains (more exactly, the differential equations in which voltage levels change among neurons, as well as the general rule of how new connections are created/destroyed.) Even after figuring out the bio-mechanics, it's going to be a hard task to implement/approximate this in silicon, and would probably need huge breakthroughs in material science and computer architecture. Copying state from a human brain to silicon would be as much as hard, since that will need incredibly high-definition non-destructive 3d scanning technology. I'll bet we're at least 100+ years for humanity to even try attempting the things you're talking about. We also have to consider that in the next few decades, the world in general will be far more busy trying to deal with the drawbacks of globalized capitalism (as well as dealing with climate change).
- malka 6y ago
  Imo it would be easier to interact with real neurons. It raises some ethics questions though
- 29athrowaway 6y ago
  You forget one thing: we have people reverse engineering biological neural networks from various perspectives. We got to deep learning because Mountcastle, Hubel and Wiesel reverse engineered the visual cortex of cats. That was the starting point of Fukushima's Neocognitron, the ancestor of the deep learning stuff you study today. Then, only a fraction of our brain is used on cognitive tasks. The rest is used in motor tasks and taking care of autonomous tasks like regulating your heart, glands and such. Things will happen faster than you think.

deleted 6y ago

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lasagnaphil 6y ago

From a grad student's point of view who currently uses "deep learning" to solve problems, we're nowhere near that kind of general intelligence. Neural networks are very good at approximating various kinds of functions given lots of redundant training data, but they have never shown the flexibility of actual human brains (as in creating new neural connections with only sparse experiences, along with deductive/symbolic reasoning). To really mimic human brains, we first need to know quantitatively how our neurons communicate with each other and form connections in our brains (more exactly, the differential equations in which voltage levels change among neurons, as well as the general rule of how new connections are created/destroyed.) Even after figuring out the bio-mechanics, it's going to be a hard task to implement/approximate this in silicon, and would probably need huge breakthroughs in material science and computer architecture. Copying state from a human brain to silicon would be as much as hard, since that will need incredibly high-definition non-destructive 3d scanning technology. I'll bet we're at least 100+ years for humanity to even try attempting the things you're talking about. We also have to consider that in the next few decades, the world in general will be far more busy trying to deal with the drawbacks of globalized capitalism (as well as dealing with climate change).

malka 6y ago
Imo it would be easier to interact with real neurons. It raises some ethics questions though
29athrowaway 6y ago
You forget one thing: we have people reverse engineering biological neural networks from various perspectives. We got to deep learning because Mountcastle, Hubel and Wiesel reverse engineered the visual cortex of cats. That was the starting point of Fukushima's Neocognitron, the ancestor of the deep learning stuff you study today. Then, only a fraction of our brain is used on cognitive tasks. The rest is used in motor tasks and taking care of autonomous tasks like regulating your heart, glands and such. Things will happen faster than you think.