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I’m not too convinced by this guy’s argument: as evidence, he presents the progress made by deep learning/CNNs in the past few years. He then rightly acknowledges the difficulty of getting machines to do abstraction and reasoning, noting that we have ideas about how to approach these things but that they require much more computing power than we have now.

...Then he basically asserts that we can extrapolate the near-term availability of tons more compute power from Moore’s Law, which is where he lost me.

We’re already running into the limits of physical law in trying to move semiconductor fabrication to smaller and smaller processes, and there are very real and interesting challenges to be overcome before, I think, we can resume anything close to the exponential growth we’ve enjoyed over the last 40 years.

This guy may well think a lot about these difficulties, but not mentioning them at all made his argument sound incredibly naïve to me.




>...Then he basically asserts that we can extrapolate the near-term availability of tons more compute power from Moore’s Law, which is where he lost me.

That's not what he's asserting. Even with Moore's law dead, OpenAI claims there is significant room with ASICs, analog computing, and simply throwing more money at the problem. There is a ton of low-hanging fruit in Non-Von Neumann architectures. We should expect it to be plucked, as we have huge use case which is potentially limitlessly profitable.


That's how I take it as well, as I said in another comment it is a compelling pitch. And yes he's not talking about Moore's Law, but how much compute is actually being dedicated to DLNN's simply because the value of doing so is going up so fast.


The video boils down to “more compute => AGI.” It’s silly and specious.


Accelerating the efficiency of an optimization algorithm doesn't get you AGI, this should be clear by now. As for fielding such systems, one quick way to destroy humanity to a degree is to turn everything into a glorified optimization problem which will no doubt be turned against people to maximize profit.


If you'll accelerate AIXI (optimization algorithm) [0], you'll get (real-time) AGI.

[0]: https://en.wikipedia.org/wiki/AIXI


If only this wasn't an fundamentally flawed theory that isn't scalable based on computational complexity and information theory.


Approximations to AIXI are computable.


> We’re already running into the limits of physical law in trying to move semiconductor fabrication to smaller and smaller processes, and there are very real and interesting challenges to be overcome before, I think, we can resume anything close to the exponential growth we’ve enjoyed over the last 40 years.

That is irrelevant. You just scale horizontally, more and more data-centers. Sure, it will not be free like in the past.




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