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CauseNet: Towards a causality graph extracted from the web

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Re: CauseNet: Towards a causality graph extracted from the web

#81

Post by [deleted] »

bckr wrote: post #61
Nevermark wrote: post #38

Earlier quoted context omitted.

That was very well said. One quibble, and really mean only one: > a high-dimensional probabilistic causal framework Deep learning models aka neural network type models, are not probabilistic frameworks. While we can measure on the outside a probability of correct answers across the whole training set, or any data set, there is no probabilistic model. Like a Pachinko game, you can measure statistics about it, but the…

What’s the relationship between what you’re saying and the concepts of “temperature” and “stochasticity”? The model won’t give me the same answer every time.

[deleted]

Re: CauseNet: Towards a causality graph extracted from the web

#82

Post by svnt »

tossandthrow wrote: post #58
eru wrote: post #55

Earlier quoted context omitted.

That doesn't make much sense. If you take multiple systems and make them work in concert, you just get a bigger system.

Concerts - again plural. And naturally you only bring in appropriate instruments.

Turtles all the way down?

Re: CauseNet: Towards a causality graph extracted from the web

#83

Post by tossandthrow »

kachnuv_ocasek wrote: post #47
tossandthrow wrote: post #23

Earlier quoted context omitted.

Ontology, not ontologies, have been tried. We have quite a good understanding that a system cannot be both sound a complete, regardless people went straight in to make a single model of the world.

> a system cannot be both sound a complete Huh, what do you mean by this? There are many sound and complete systems – propositional logic, first-order logic, Presburger arithmetic, the list goes on. These are the basic properties you want from a logical or typing system. (Though, of course, you may compromise if you have other priorities.)

Yep - when you use a multiplum of systems, then some systems can be regarded complete while other systems are sound.

This is in contrast to just one system that attempts to be sound and complete.

Re: CauseNet: Towards a causality graph extracted from the web

#85

Post by aleatorianator »

kruffalon wrote: post #65

I read it as "casual" rather than "causal", got very dissapointed while reading the article! An inventory of casual knowledge would be really fun, although it's hard to think what it would consist of now that I think about it... There is this concept of "hidden knowledge" about all the things you know at work that no one really thinks about is knowledge so it's hard to let newcomers know about it. But that does sound…

it's as simple as precisely describing "common sense"

Re: CauseNet: Towards a causality graph extracted from the web

#86

Post by svnt »

jijijijij wrote: post #72
eru wrote: post #55

Earlier quoted context omitted.

That doesn't make much sense. If you take multiple systems and make them work in concert, you just get a bigger system.

> If you take multiple systems and make them work in concert, you just get a bigger system. The conclusion may be wrong, but a "bigger system" can be larger than the sum of its constituents. So a system can have functions, give rise to complexity, neither of its subsystems feature. An example would be the thinking brain, which is made out of neurons/cells incapable of thought, which are made out of molecules incapabl…

This is just emergence, though? How is emergence related to completeness?

This happens over and over with the relatively new popularization of a theory: the theory is proposed to be the solution to every missing thing in the same rough conceptual vector.

It takes a lot more than just pointing in the general direction of complexity to propose the creation of a complete system, something which with present systems of understanding appears to be impossible.

Re: CauseNet: Towards a causality graph extracted from the web

#87

Post by jijijijij »

tossandthrow wrote: post #74
jijijijij wrote: post #68

Earlier quoted context omitted.

I believe, neither the expansion of Gödel's theorems to "everything", non-formalized systems, nor the conclusion of a resolution by harnessing multiple systems in concert, are sound reasoning. I think, it's a fallacious reductionism.

What is a non-formalized system? I am very curious on this. In particular, if you are able to split systems into formalized and non formalized, then I thinks there are quite some praise and a central spot in all future history books for you!

I am not a native speaker, so please don't get hung up on particular expressions.

I meant, the colloquial philosophies and general ontology are not subject of Gödel's work. I think, the forgone expansion is similar to finding evidence for telepathy in the pop-sci descriptions of quantum entanglement. Gödel's theorems cover axiomatic, formal systems in mathematics. To apply it to whatever, you first have to formalize whatever. Otherwise, it's an intuition/speculation, not sound reasoning. At least, that's my understanding.

Further reading: https://en.wikipedia.org/wiki/G%C3%B6del's_incompleteness_th...

Re: CauseNet: Towards a causality graph extracted from the web

#88

Post by SilverElfin »

tgv wrote: post #14

This makes little sense to me. Ontologies and all that have been tried and have always been found to be too brittle. Take the examples from the front page (which I expect to be among the best in their set): human_activity => climate_change. Those are such a broad concepts that it's practically useless. Or disease => death. There's no nuance at all. There isn't even a definition of what "disease" is, let alone a way t…

What is an ontology exactly? I see Palantir talking about it all the time and it just sounds like vague marketing.

Re: CauseNet: Towards a causality graph extracted from the web

#89

Post by 2OEH8eoCRo0 »

rwmj wrote: post #35

Isn't this like Cyc? There have been a couple of interesting articles about that on HN: https://news.ycombinator.com/item?id=43625474 "Obituary for Cyc" https://news.ycombinator.com/item?id=40069298 "Cyc: History's Forgotten AI Project"

Everything old is new again
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