The purpose of the large text benchmark was to find the best algorithms for
modeling natural language. I use 1 GB because you process that much
language in a lifetime. A model that can predict as well as a human could
be used to pass the Turing test. Compression measures prediction accuracy.
I explain how in http://mattmahoney.net/dc/rationale.html

AGI includes vision, robotics, and other skills that Turing did not include
in his definition of intelligence. These skills are needed to automate
labor, so we include them. My research was strictly in language. Video and
audio have too much noise to use lossless compression to test models of
them. Lossy compression could theoretically achieve 5 to 10 bits per
second, but the testing would require human subjectivity to evaluate
quality.

Compressing video to 10 bits per second would be accomplished by converting
it to a human readable script and compressing the text. The decompressor
would read the script and create the video it describes. It would be tested
by showing the decompressed video a day after the original and asking you
to identify any differences. This should be possible because human long
term memory learning rate is about 2 bits per second.

Of course we can't do this yet. It's going to to take enormous computing
power and vast training data that we don't yet have.

On Sun, Nov 24, 2019, 5:52 PM <[email protected]> wrote:

> Yeh I agree with that one,   but dont forget theres an exponential amount
> of text you need to go with the cpu time and memory - and thats not easy to
> come by.   That amazing 1% ratio text compressor isnt even enough to push
> it much further than what is required.
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