> demo.chaoticlanguage.com

It works with "I went to Brazil", but seems to break with "In Brazil,
people are friendly" (it creates "Brazil people" as a node). Any way to
give it feedback?

On Sun, 17 Feb 2019 at 22:48, Rob Freeman <chaotic.langu...@gmail.com>
wrote:

> On Mon, Feb 18, 2019 at 10:05 AM Stefan Reich via AGI <
> agi@agi.topicbox.com> wrote:
>
>> Nothing wrong with pushing your own results if you consider them
>> worthwhile...
>>
>
> Well, I think on one level it's much the same as Pissanetzky.
>
> Pissanetzky's is a meaningful way of relating elements which generates new
> patterns. You have new patterns all the time, but they are nevertheless
> meaningful, because the relationships generating them are meaningful. So it
> takes us away from the idea learning every pattern, which is what I believe
> traps deep learning (and prevents Tesla from spotting firetrucks..., and
> getting to that last mile self-driving.)
>
> Similarly I found new patterns, which were very much like Pissanetzky's
> invariant permutations. But I did it for language. When I projected out
> these new patterns of "invariants" for each new sentence, I found hierarchy.
>
> You can think of this as a next stage in a progression from symbolism to
> distributed representation, now to novel but meaningful rearrangements of
> distributed elements.
>
> Meanwhile deep learning just keeps pushing against a ceiling of what can
> be learned.
>
> FWIW you can see an old and simple demo of the principle of hierarchy
> coming out of novel rearrangements (of embeddings) at:
>
> demo.chaoticlanguage.com
>
> Summary paper circa 2014 at:
>
> Parsing using a grammar of word association vectors
> http://arxiv.org/abs/1403.2152
>
> -Rob
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>


-- 
Stefan Reich
BotCompany.de // Java-based operating systems

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