From: Mark Nuzzolilo (nuzz604@gmail.com)
Date: Mon Jun 16 2008 - 11:19:24 MDT
I'll take a swing at this.
Let's start with the assumption that a machine cannot output a machine of
greater algorithmic complexity.
Now for a thought experiment put humans in that same category. A single
human would not be able to produce something "greater" than itself. The
details of this are unimportant. The point is that when you take a larger
group of humans, the complexity increases and you can now produce a machine
potentially greater than a single human. This machine could then improve
the intelligence or ability of single humans at a time, and then those
humans could then create a greater machine.
This is obviously not a "typical" RSI scenario but if my reasoning is
correct here (correct me if I am wrong), then in theory RSI would be
possible even by taking this concept and abstracting it to specific (and
properly designed) AGI components rather than specific components of a group
of humans (the humans themselves).
Mark Nuzzolilo
On Sun, Jun 15, 2008 at 1:18 PM, Matt Mahoney <matmahoney@yahoo.com> wrote:
> Is there a model of recursive self improvement? A model would be a
> simulated environment in which agents improve themselves in terms of
> intelligence or some appropriate measure. This would not include genetic
> algorithms, i.e. agents make random changes to themselves or copies,
> followed by selection by an external fitness function not of the agent's
> choosing. It would also not include simulations where agents receiving
> external information on how to improve themselves. They have to figure it
> out for themselves.
>
> The premise of the singularity is that humans will soon reach the point
> where we can enhance our own intelligence or make machines that are more
> intelligent than us. For example, we could genetically engineer humans for
> bigger brains, faster neurons, more synapses, etc. Alternatively, we could
> upload to computers, then upgrade them with more memory, more and faster
> processors, more I/O, more efficient software, etc. Or we could simply build
> intelligent machines or robots that would do the same.
>
> Arguments in favor of RSI:
> - Humans can improve themselves by going to school, practicing skills,
> reading, etc. (arguably not RSI).
> - Moore's Law predicts computers will have as much computing power as human
> brains in a few decades, or sooner if we figure out more efficient
> algorithms for AI.
> - Increasing machine intelligence should be a straightforward hardware
> upgrade.
> - Evolution produced human brains capable of learning 10^9 bits of
> knowledge (stored using 10^15 synapses) with only 10^7 bits of genetic
> information. Therefore we are not cognitively limited from understanding our
> own code.
>
> Arguments against RSI:
> - A Turing machine cannot output a machine of greater algorithmic
> complexity.
> - If an agent could reliably produce or test a more intelligent agent, it
> would already be that smart.
> - We do not know how to test for IQs above 200.
> - There are currently no non-evolutionary models of RSI in humans, animals,
> machines, or software (AFAIK, that is my question).
>
> If RSI is possible, then we should be able to model simple environments
> with agents (with less than human intelligence) that could self improve (up
> to the computational limits of the model) without relying on an external
> intelligence test or fitness function. The agents must figure out for
> themselves how to improve their intelligence. How could this be done? We
> already have genetic algorithms in simulated environments that are much
> simpler than biology. Perhaps agents could modify their own code in some
> simplified or abstract language of the designer's choosing. If no such model
> exists, then why should we believe that humans are on the threshold of RSI?
>
>
> -- Matt Mahoney, matmahoney@yahoo.com
>
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