Yeah, I read his book as well and found it remarkably naive in some ways
... I mean, clearly the author knows what he's doing regarding certain
types of probabilistic inference methods, but he seems surprisingly unaware
of the broader picture regarding AGI, algorithmic information, and so forth
... I had the intention of writing a critical review when i read the book,
but never got around to it ;p ...

On Fri, Feb 12, 2016 at 11:52 AM, TimTyler <[email protected]> wrote:

> I read and reviewed Pedro Domingos's book "The Master Algorithm".
> My review is here:
>
> http://smile.amazon.com/gp/cdp/member-reviews/AYJ8P83FHQARZ
>
> To summarize my biggest criticism:
>
> The book documents the search for a silver bullet of machine intelligence.
> The author didn't seem to be familiar with Legg's 2008 proof that machine
> intelligence will be complex. In "Is there an Elegant Universal Theory
> of Prediction?" Legg offers a simple, constructive proof that, for any
> prediction algorithm, there exist sequences with similar Kolmogorov
> complexity to the prediction algorithm, that the predictor can never
> learn how to predict. Legg's conclusion is that successful general
> purpose predictors of complex sequences will themselves necessarily
> be highly complex. Machine intelligence doesn't have a silver bullet.
>
> --
> __________
>  |im Tyler http://timtyler.org/
>
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-- 
Ben Goertzel, PhD
http://goertzel.org

"The reasonable man adapts himself to the world: the unreasonable one
persists in trying to adapt the world to himself. Therefore all progress
depends on the unreasonable man." -- George Bernard Shaw



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