Eliezer Yudkowsky write a post on Facebook on on Oct 17, where I replied at the time. Yesterday he reposted that here (link), minus my responses. So I’ve composed the following response to put here:

I have agreed that an AI-based economy could grow faster than does our economy today. The issue is how fast the abilities of one AI system might plausibly grow, relative to the abilities of the entire rest of the world at that time, across a range of tasks roughly as broad as the world economy. Could one small system really “foom” to beat the whole rest of the world?

As many have noted, while AI has often made impressive and rapid progress in specific narrow domains, it is much less clear how fast we are progressing toward human level AGI systems with scopes of expertise as broad as those of the world economy. Averaged over all domains, progress has been slow. And at past rates of progress, I have estimated that it might take centuries.

Over the history of computer science, we have developed many general tools with simple architectures and built from other general tools, tools that allow super human performance on many specific tasks scattered across a wide range of problem domains. For example, we have superhuman ways to sort lists, and linear regression allows superhuman prediction from simple general tools like matrix inversion.

Yet the existence of a limited number of such tools has so far been far from sufficient to enable anything remotely close to human level AGI. Alpha Go Zero is (or is built from) a new tool in this family, and its developers deserve our praise and gratitude. And we can expect more such tools to be found in the future. But I am skeptical that it is the last such tool we will need, or even remotely close to the last such tool.

For specific simple tools with simple architectures, architecture can matter a lot. But our robust experience with software has been that even when we have access to many simple and powerful tools, we solve most problems via complex combinations of simple tools. Combinations so complex, in fact, that our main issue is usually managing the complexity, rather than including the right few tools. In those complex systems, architecture matters a lot less than does lots of complex detail. That is what I meant by suggesting that architecture isn’t the key to AGI.

You might claim that once we have enough good simple tools,

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