indeed you are correct there maybe! thats a cool thought.
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Another way that removing spurious order from data is beneficial:
Parallel algorithms
When I recently tried running cmix on the OBWB, I noticed it ran on only
one core (and incredibly slowly).
I'm not sure how the OBWB is organized but if it is a bunch of "articles"
whose order conveys little
order and meaning ->
I throw a ball at you.
you throw a ball at i.
Is the ball going to you or me?
Maybe in different languages, french ppl might read it the opposite of english
ppl? But I dont know I only speak 1 language.
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Artificial General
If you want to reduce order from a string, sort all the strings in
alphabetical order, when storing them and when accessing for them, then the
order will be taken out of the match. :)
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Right. The example is not so much to suggest a practical/significant
improvement in the Hutter Prize as to address a general problem:
Specification of information sometimes requires deliberately leaving out
ordering information -- as in set literals like
cats = set(fluffy, scruffy, paws, claws,
Removing the ordering constraint on enwik8 should reduce the compressed
size by about 50K bytes, or 2 bytes per article. But it wouldn't affect the
nature of the research. Here is more about the data.
http://mattmahoney.net/dc/textdata.html
On Tue, Jan 14, 2020, 7:59 AM James Bowery wrote:
>
It is a respecification of the information to expose the spatial dimension
of the corpus, while leaving the time dimension in tact.
On Tue, Jan 14, 2020 at 1:51 PM John Rose wrote:
> Isn't that technically near-lossless? Leaving some tiny wiggle room?
> *Artificial General Intelligence List
Isn't that technically near-lossless? Leaving some tiny wiggle room?
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In reality, sensors and effectors exist in space as well as time. Serializing
the spatial dimension of observations to formalize their Kolmogorov Complexity,
so they conform to the serialized input to a Universal Turing machine,
over-constrains the observations, introducing order not relevant
