[nl]

Until you can make quantifiable predictions of behaviour that you want to see it sounds like your objections are philosophical rather than scientific.

> A prediction of a "next frame" is always therefore just going to be a symptom of the frames before it.

But the physical appearance of the automobile itself was absolutely influenced by what went before - they were called "horseless carriages" after the appearance after all.

And NLP Language Models can produce genuinely original and unique writing. This is a poem a large LM wrote for me:

  The sceptered isle
  Hath felt the breath of Britain,
  Longer than she cares to remember.
  Now are her champion arms outstared,
  Her virgin bosom stained with battle's gore.
  Lords and nobles, courtiers and commons,
  All stand abashed; the multitudinous rout
  Scatter their fears in every direction;
  Except their courage, which, to be perfect,
  Must be all directed to the imminent danger
  Which but now struck like a comet; and they feel
  The blow is imminent

> we aim to coordinate, move, and so on with words.

https://say-can.github.io/

"Robots ground large language models in reality by acting as their eyes and hands while LLMs help robots execute long, abstract language instructions"

[mjburgess]

Chopping up sequences of film, and stiching them together, based on their prior similarity isn't making a movie -- and that's all you have here. People wrote poetry -- *for the first time* -- to say something about their own environment, that they are present in. All you have here is a system which has remembered a compressed representation of these poems and stiches them together to fool you.

It really is a kind of proto-psychosis to think this machine has written a poem. It has generated the text of a poem.

> quantifiable predictions of behaviour that you want to see

This is trivial. I ask the machine a large number of ordinary questions, eg., "what do you think about what i'm wearing?", "what would it take to change your mind on whether murder is justified?", "do you think you'd like new york?", "could you pass me the salt?", etc. -- a trivial infinity of questions lifted from the daily life of language users.

The machine cannot answer any of those questions. All it will do is generate some text on the occasion that the machine sees that text. This isn't an answer. That isnt the question. The question isnt "summarise a million documents and report an on-average plausible answer to these questions".

When I ask a person any of those questions, if they did that, they wouldnt be answering them. This is trivial to observe.

These systems are just taking modes() of subsets of historical data. That's just what they are. The appearence of their using language is an illusion

To use language is to have something to say, to wish to talk about something. When i say, "I liked the movie!" I am not summarising a million reviews and finding an average sentence. I am thinking about my experience of the movie, and generating a public sharable "text" that aims to communicate what i actually think.

*THAT* is language. Language is your intention to speak *ABOUT* something, and the capacity to generate a public shared set of words which communicate what you are talking about. Any process which begins *without anything to say* cannot ever reach langauge as a capacity.

Langauge, as a capacity, begins by being in the world. No summary of the public statmenets of past speakers has anything to do with being in the world; and having things to say. Chopping that up and stiching it together is a trick.

And this is trivial to show empirically. It is only by having absolutely no study of langauge use can anyone claim that text documents have anything ot do with it. IT's mumbohjumbo.

[nl]

I see. You believe there is something unmeasureable that matters.

I don't. I believe a perfect simulation of intelligence is intelligence.

[mjburgess]

It's not unmeasurable. If you ask a friend, "did you like that movie?" would you be happy if they hadnt seen it; didnt know anything about it; etc. etc. and simply generated a response based on some review data they'd read?

Is that what you want from people? You want them just to report a summary of the textbooks, of the reviews of other people? You dont want them to think for a moment, about anything and have something to say?

This is a radically bleak picture; and omits, of course, everything important.

We arent reporting the reports of others. We are thinking about things. That isnt unmeasurable, it is trivial to measure.

Show someone the film, ask them questions about it, and so on -- establish their taste.

NLPs arent simulations of anything. It's a parlour trick. If you want a perfect simulation of intelligence, go and show me one -- I will ask it what it likes; and I doubt it'll have anything sincere to say.

There is no sincerity possible here. These systems are just libraries run through shredders; they havent been anywhere; they arent anywhere. They have nothing to say. They arent talking about anything.

You and I are not the libraries of the world cut up. We are actually responsive to the environments we are in. If someone falls over, we speak to help them. We dont, as if lobtomized, rehearse something. When we use words we use them to speak about the world we are in; this isnt unmeasuarable -- its the whole point.

[hackinthebochs]

Why do you think a model of intelligence needs to have tastes, values, likes/dislikes, etc for it to be something more than statistics or pattern matching? Why are you associating these consciousness qualities with AGI?

[mjburgess]

To use a language is just to talk about things. You cannot answer the question, "do you like what i'm wearing?" if you dont have the capacity for taste.

Likewise, this applies to all language. To say, "do you know what 2+2 is?" *we* might be happy with "4" in the sense that a calculator answers this question. But we havent actually used language here. To use language is to understand what "2" means.

In otherwords, the capacity for langauge is only just the capacity to make a public communicable description of the non-linguistic capacities that we have. A statistical analysis of what we have already said, does not have this contact with the world, or the relevant capacities. It's just a record of their past use.

None of these systems are langauge users; none have language. They have the symbols of words set in an order, but they arent talkiung abotu anything, because they have nothing to talk about.

This is, i think really really obvious when you ask "did you like that film?" but it applies to every question. We are just easily satisifed when alexa turns the lights off when we say "alexa, lights off". This mechanical satisifcation leads some to the frankly schiozphrenic conclusion that alexa understands what turning the lights off means.

She doesnt. She will never say back, "but you know, it'll be very dark if you do that!" or "would you like the tv on instead?" etc. Alexa isnt having a conversation with you based on a shared understanding of your environment, ie., using langauge.

Alexa, like all NLP systems, are illusions. You arent speaking to anything. You arent asking anything a question. Nothing is answering you. You are the only thing in the room that understands what's going on, and the output of the system is meaningful only because you read it.

The system itself has no meaning to what its doing. The lights go off, but not because the system understood that your desire. It could not, if it failed to undestand, ask about your desire.

[hackinthebochs]

You're just reiterating that you think tastes, opinions, likes/dislikes are something intrinsic to the issues here. I'm asking why do you think these things are intrinsic to language understanding or intelligence?

>To use language is to understand what "2" means.

I've never held a "2", yet I know what 2 is as much as anyone. It is a position in a larger arithmetical structure, and it has a correspondence to collections of a certain size. I have no reason to think a sufficiently advanced model trained on language cannot have the same grasp of the number 2 as this.

>A statistical analysis of what we have already said, does not have this contact with the world, or the relevant capacities. It's just a record of their past use.

Let's be clear, there is nothing inherently statistical about language models. Our analysis of how they learn and how they construct their responses is statistical. The models themselves are entirely deterministic. Thus for a language model to respond in contextually appropriate ways means that it's internal structure is organized around analyzing context and selecting the appropriate response. That is, it's "capacities" are organized around analyzing context and selecting appropriate responses. This to me is the stuff of "understanding". The fact that the language model has never felt a cold breeze when it suggests that I close the window if the breeze is making me cold is irrelevant.

>You arent speaking to anything. You arent asking anything a question. Nothing is answering you.

It seems that your hidden assumption is that understanding/intelligence requires sentience. And since language models aren't sentient, they are not intelligent. But why do the issues here reduce to the issue of sentience?