G asserts its own unprovability in F

[Skepdick]

To express natural language semantics syntactically required ChatGPT
to automate the process. The CYC project spent 700 labor years trying
to manually formalize the subset of knowledge known as common sense.

Formalizing all of natural language semantics merely involves specifying
relations between finite strings. It is more effective and efficient to use
GUIDs as placeholders for the unique sense meanings of words.

Dude. [Redacted]

We had this conversation 2 weeks ago. ChatGPT is not relational - it's probabilistic.

You are confusing paradigms.


[Edited by iMod]

[PeteOlcott]

To express natural language semantics syntactically required ChatGPT
to automate the process. The CYC project spent 700 labor years trying
to manually formalize the subset of knowledge known as common sense.

Formalizing all of natural language semantics merely involves specifying
relations between finite strings. It is more effective and efficient to use
GUIDs as placeholders for the unique sense meanings of words.

Dude. [Redacted]

We had this conversation 2 weeks ago. ChatGPT is not relational - it's probabilistic.

You are confusing paradigms.

None-the-less it does formalize natural language semantics.

[PeteOlcott]

The formal language semantics of formal languages merely requires an
algorithm to encode this.

And the input of this algorithm is ...?

That depends on which formal language has been formalized.
It will always be some form is text, Unicode or ASCII.

[PeteOlcott]

To express natural language semantics syntactically required ChatGPT
to automate the process. The CYC project spent 700 labor years trying
to manually formalize the subset of knowledge known as common sense.

Formalizing all of natural language semantics merely involves specifying
relations between finite strings. It is more effective and efficient to use
GUIDs as placeholders for the unique sense meanings of words.

Dude. Do you suffer from alzheimers or something?

We had this conversation 2 weeks ago. ChatGPT is not relational - it's probabilistic.

You are confusing paradigms.

https://writings.stephenwolfram.com/202 ... s-it-work/
Semantic Grammar and the Power of Computational Language

[Skepdick]

None-the-less it does formalize natural language semantics.

No, it doesn't. Natural languages don't have semantics.

https://youtu.be/E4KhK3kktcM?t=2273

[Skepdick]

That depends on which formal language has been formalized.
It will always be some form is text, Unicode or ASCII.

Those are encodings not languages.

[PeteOlcott]

That depends on which formal language has been formalized.
It will always be some form is text, Unicode or ASCII.

Those are encodings not languages.

Yes those are encoding and not languages. Since you did not specify
a language I could not be more specific.

https://writings.stephenwolfram.com/202 ... s-it-work/
Semantic Grammar and the Power of Computational Language

When we start talking about “semantic grammar” we’re soon led to ask “What’s underneath it?” What “model of the world” is it assuming? A syntactic grammar is really just about the construction of language from words. But a semantic grammar necessarily engages with some kind of “model of the world”—something that serves as a “skeleton” on top of which language made from actual words can be layered.

Until recent times, we might have imagined that (human) language would be the only general way to describe our “model of the world”. Already a few centuries ago there started to be formalizations of specific kinds of things, based particularly on mathematics. But now there’s a much more general approach to formalization: computational language.

search for [semantic] on the link

[Skepdick]

But now there’s a much more general approach to formalization: computational language.

It's simply impossible to get through to you. Having given you the benefit of the doubt for so long [Redacted]

The be-all-end-all of computational systems, the most general property we care about is the property we call Turing completeness otherwise known as computational universality.

ANY computationally universal language can express contradictions. This is a feature not a bug!
Any attempt thereafter to remove contradictions from an otherwise universal language results in loss of universality.

Which is precisely the point of Godel's theorems.

You can give up universality (Turing completeness) and gain consistency e.g the typed lambda calculus.
Or you can keep universailty and lose consistency e.g the untyped lambda calculus.

I want universality! It means I have to live with inconsistency.

Which one do you want?


[Edited by iMod]

[Agent Smith]

Hahahahohohohehehe!

What's gotten into him?

I dunno! Let's check.

Oh! Page 95!

That explains it! Wait till he gets to page 104!

Keep yer phone charged!

Roger!

[PeteOlcott]

But now there’s a much more general approach to formalization: computational language.

It's simply impossible to get through to you. Having given you the benefit of the doubt for so long [Redacted]

The be-all-end-all of computational systems, the most general property we care about is the property we call Turing completeness otherwise known as computational universality.

ANY computationally universal language can express contradictions. This is a feature not a bug!
Any attempt thereafter to remove contradictions from an otherwise universal language results in loss of universality.

Which is precisely the point of Godel's theorems.

You can give up universality (Turing completeness) and gain consistency e.g the typed lambda calculus.
Or you can keep universailty and lose consistency e.g the untyped lambda calculus.

I want universality! It means I have to live with inconsistency.

Which one do you want?

My simple system has universality and consistency.
That you can't see that does not make it untrue.

My simple formal system that merely derives the semantic consequence of expressions of language that have been stipulated to be true would reject Godel's G as semantically incoherent on the basis that the proof of G requires a sequence of inference steps in F the proves there is no such sequence of inference steps in F.

[Skepdick]

My simple system has universality and consistency.

Not possible.

If it's Turing-complete it's inconsistent.
If it's consistent it's not Turing-complete.

[Redacted]

[Edited by iMod]

[PeteOlcott]

My simple system has universality and consistency.

Not possible.

If it's Turing-complete it's inconsistent.
If it's consistent it's not Turing-complete.

[Redacted]

In other words you are simply assuming that the halting problem proof is correct.

Simulating (partial) Halt Deciders Defeat the Halting Problem Proofs
https://www.researchgate.net/publicatio ... lem_Proofs

[Skepdick]

My simple system has universality and consistency.

Not possible.

If it's Turing-complete it's inconsistent.
If it's consistent it's not Turing-complete.

[Redacted]

In other words you are simply assuming that the halting problem proof is correct.

Simulating (partial) Halt Deciders Defeat the Halting Problem Proofs
https://www.researchgate.net/publicatio ... lem_Proofs

In other words - [Redacted]

[Edited by iMod]

[PeteOlcott]

Not possible.

If it's Turing-complete it's inconsistent.
If it's consistent it's not Turing-complete.

[Redacted]

In other words you are simply assuming that the halting problem proof is correct.

Simulating (partial) Halt Deciders Defeat the Halting Problem Proofs
https://www.researchgate.net/publicatio ... lem_Proofs

In other words - [Redacted]

In other words I hit the limit of your technical competence and this really bugs you. If I didn't hit the limit of your technical competence you would be able to point to some specific mistake that I made. Because you can't do that you simply started yelling.

[PeteOlcott]

No one can point to any mistake only because I am correct.

When a simulating halt decider correctly simulates N steps of its input it derives the exact same N steps that a pure UTM would derive because it is itself a UTM with extra features.

My reviewers cannot show that any of the extra features added to the UTM change the behavior of the simulated input for the first N steps of simulation:
(a) Watching the behavior doesn't change it.
(b) Matching non-halting behavior patterns doesn't change it
(c) Even aborting the simulation after N steps doesn't change the first N steps.

Because of all this we can know that the first N steps of input D simulated by simulating halt decider H are the actual behavior that D presents to H for these same N steps.

computation that halts… “the Turing machine will halt whenever it enters a final state” (Linz-1990:234)

When we see (after N steps) that D correctly simulated by H cannot possibly reach its simulated final state in any finite number of steps of correct simulation then we have conclusive proof that D presents non-halting behavior to H.

Copyright 2020 PL Olcott

Linz, Peter 1990. An Introduction to Formal Languages and Automata. Lexington/Toronto: D. C. Heath and Company. (317-320)

[Edited by iMod]