On Sep 9, 2008, at 7:54 AM, Matt Mahoney wrote:

--- On Mon, 9/8/08, Steve Richfield <[EMAIL PROTECTED]> wrote:
On 9/7/08, Matt Mahoney <[EMAIL PROTECTED]> wrote:

The fact is that thousands of very intelligent people have been trying to solve AI for the last 50 years, and most of them shared your optimism.

Unfortunately, their positions as students and professors at various
universities have forced almost all of them into politically correct
paths, substantially all of which lead nowhere, for otherwise they would
have succeeded long ago. The few mavericks who aren't stuck in a
university (like those on this forum) all lack funding.

Google is actively pursuing AI and has money to spend. If you have seen some of their talks, you know they are pursuing some basic and novel research.

Google to the best of my knowledge is pursuing a some areas of narrow AI. I do not believe they are remotely after AGI.




Perhaps it would be more fruitful to estimate the cost of automating the global economy. I explained my estimate of 10^25 bits of memory, 10^26
OPS, 10^17 bits of software and 10^15 dollars.

You want to replicate the work currently done by 10^10 human brains.

Hmm. Actually probably only some 10^6 of them at most are doing anything much worth replicating. :-)

A brain has 10^15 synapses. A neuron axon has an information rate of 10 bits per second. As I said, you can argue about these numbers but it doesn't matter much. An order of magnitude error only changes the time to AGI by a few years at the current rate of Moore's Law.

Software is not subject to Moore's Law so its cost will eventually dominate.

So creating software creating software may be a high payoff subtask.

A human brain has about 10^9 bits of knowledge, of which probably 10^7 to 10^8 bits are unique to each individual.

How much of this uniqueness is little more than variations on a much smaller number of themes and/or irrelevant to the task?

That makes 10^17 to 10^18 bits that have to be extracted from human brains and communicated to the AGI.

What for? That seems like a very slow path that would pollute your AGI with countless errors and repetition.

This could be done in code or formal language, although most of it will probably be done in natural language once this capability is developed.

Natural languages are ridiculously slow and ambiguous. There is no way the 10^7 guesstimated unique bits per individual will ever get encoded in natural language anyway (or much of anything else other than its encoding in those brains).

Since we don't know which parts of our knowledge is shared, the most practical approach is to dump all of it and let the AGI remove the redundancies.

Actually, of the knowledge the AGI needs we have pretty good ideas of how much is shared.

This will require a substantial fraction of each person's life time, so it has to be done in non obtrusive ways, such as recording all of your email and conversations (which, of course, all the major free services already do).

What exactly is your goal? Are you attempting to simulate all of humankind? What for when the real thing is up and running? If you want uploads there are more direct possible paths after the AGI has perfected some crucial technologies.




The cost estimate of $10^15 comes by estimating the world GDP ($66 trillion per year in 2006, increasing 5% annually) from now until we have the hardware to support AGI. We have the option to have AGI sooner by paying more. Simple economics suggests we will pay up to what it is worth.

Why believe that the real productive intellectual output of the entire human world is anywhere close to or represented by the world GDP? It is not likely that we need to download the full contents of all human brains including the huge part that is mere variation on human primate programming to effectively meet and exceed this productive intellectual output. I find this method of estimating costs utterly unconvincing.

- samantha



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agi
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