The quote you give focuses just on the issue of time-span. It also has already been addressed in this thread. Machine intelligence in the sense it is often used is not at all the same as artificial general intelligence. This has in fact been addressed by others in this subthread. (Although it does touch on a point you've made elsewhere that we've been using machines to engage in what amounts to successive improvement which is likely relevant.)
So what caused you to use the term as if it had a specific definition when you didn't think it did?
I did what, exactly?
I would have thought that your comments in the previously linked thread started by Mass Driver would be sufficient, like when you said:
One "anti-foom" factor is the observation that in the early stages we can make progress partly by cribbing from nature - and simply copying it. After roughly "human level" is reached, that short-cut is no longer available - so progress may require more work after that.
And again in that thread where you said:
1 seems unlikely and 2 and 3 seem silly to me. An associated problem of unknown scale is the wirehead problem. Some think that this won't be a problem - but we don't really know that yet. It probably would not slow down machine intelligence very much, until way past human level - but we don't yet know for sure what its effects will be.
Although rereading your post, I am now wondering if you were careful to put "anti-foom" in quotation marks because it didn't have a clear definition. But in that case, I'm slightly confused to how you knew enough to decide that that was an anti-foom argument.
Right - so, by "anti-foom factor", I meant: factor resulting in relatively slower growth in machine intelligence. No implication that the "FOOM" term had been satisfactorily quantitatively nailed down was intended.
I do get that the term is talking about rapid growth in machine intelligence. The issue under discussion is: how fast is considered to be "rapid".
Michael Anissimov posted the following on the SIAI blog:
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Kaj's commentary: if you haven't done so recently, do check out the SIAI publications page. There are several new papers and presentations, out of which I thought that Carl Shulman's Whole Brain Emulations and the Evolution of Superorganisms made for particularly fascinating (and scary) reading. SIAI's finally starting to get its paper-writing machinery into gear, so let's give them money to make that possible. There's also a static page about this challenge; if you're on Facebook, please take the time to "like" it there.
(Full disclosure: I was an SIAI Visiting Fellow in April-July 2010.)