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Bag of words, have mercy on us

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Re: Bag of words, have mercy on us

#201

Post by littlestymaar »

ben_w wrote: post #162
littlestymaar wrote: post #150

Earlier quoted context omitted.

> LLMs and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others? “Internal combustion engines and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others?” The question isn't about what an hypothetical mechanism can do or not, it's about whether the concrete mechanism we…

The general argument you make is correct, but you conclusion "And this one doesn't." is as yet uncertain. I will absolutely say that all ML methods known are literally too stupid to live, as in no living thing can get away with making so many mistakes before it's learned anything, but that's the rate of change of performance with respect to examples rather than what it learns by the time training is finished. What is…

> but that's the rate of change of performance with respect to examples rather than what it learns by the time training is finished.

It's not just that. The problem of “deep learning” is that we use the word “learning” for something that really has no similarity with actual learning: it's not just that it converges way too slowly, it's also that it just seeks to minimize the predicted loss for every samples during training, but that's no how humans learn. If you feed it enough flat-earther content, as well a physics books, an LLM will happily tells you that the earth is flat, and explain you with lots of physics why it cannot be flat. It simply learned both “facts” during training and then spit it out during inference.

A human will learn one or the other first, and once the initial learning is made, it will disregards all the evidence of the contrary, until maybe at some point it doesn't and switches side entirely.

LLMs don't have an inner representation of the world and as such they don't have an opinion about the world.

The humans can't see the reality for itself, but they at least know it exists and they are constantly struggling to understand it. The LLM, by nature, is indifferent to the world.

Re: Bag of words, have mercy on us

#202

Post by fsflover »

bamboozled wrote: post #54
bloaf wrote: post #46

Earlier quoted context omitted.

And the big players have built a bunch of workflows which embed many other elements besides just "predictions" into their AI product. Things like web search, to incorporating feedback from code testing, to feeding outputs back into future iterations. Who is to say that one or more of these additions has pushed the ensemble across the threshold and into "real actual thinking." The near-religious fervor which people in…

I take a offence in the idea I’m “religiously downplaying LLMs”. I pay top dollar for access to the best models because I want the capabilities to be good / better. Just because I’m documenting my experience it doesn’t mean I have an Anti-ai agenda ? I pay because I find LLMs to be useful. Just not in the way suggested by the marketing teams. I’m downplaying because I have honestly been burned by these tools when I’v…

"LLMs don't reply to my queries perfectly, therefore they don't think"?

Re: Bag of words, have mercy on us

#203

Post by emsign » 

  But we don’t go to baseball games, spelling bees, and
  Taylor Swift concerts for the speed of the balls, the
  accuracy of the spelling, or the pureness of the
  pitch. We go because we care about humans doing those
  things. It wouldn’t be interesting to watch a bag of
  words do them—unless we mistakenly start treating
  that bag like it’s a person.unless we mistakenly
  start treating that bag like it’s a person.
That seems to be the marketing strategy of some very big, now AI dependend companies. Sam Altman and others exaggerating and distorting the capabilities and future of AI.

The biggest issue when it comes to AI is still the same truth as with other technology. It's important who controls it. Attributing agency and personality to AI is a dangerous red flag.

Re: Bag of words, have mercy on us

#204

Post by nephihaha »

emsign wrote: post #203

But we don’t go to baseball games, spelling bees, and Taylor Swift concerts for the speed of the balls, the accuracy of the spelling, or the pureness of the pitch. We go because we care about humans doing those things. It wouldn’t be interesting to watch a bag of words do them—unless we mistakenly start treating that bag like it’s a person.unless we mistakenly start treating that bag like it’s a person. That seems to…

A lot of us wouldn't go to a Taylor Swift concert. I had to endure several days of interrupted commuting thanks to them though.

Support alternative and independent bands. They're around, and many are enjoyable. (Some are not but avoid them LOL.)

Re: Bag of words, have mercy on us

#205

Post by nephihaha »

akoboldfrying wrote: post #112
RayVR wrote: post #70

Earlier quoted context omitted.

Are you a stream of words or are your words the “simplistic” projection of your abstract thoughts? I don’t at all discount the importance of language in so many things, but the question that matters is whether statistical models of language can ever “learn” abstract thought, or become part of a system which uses them as a tool. My personal assessment is that LLMs can do neither.

LLMs and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others? If it turns out that LLMs don't model human brains well enough to qualify as "learning abstract thought" the way humans do, some future technology will do so. Human brains aren't magic, special or different.

There isn't anything else around quite like a human brain that we know of, so yes, I'd say they're special and different.

Animals and computers come close in some ways but aren't quite there.

Re: Bag of words, have mercy on us

#206

Post by ben_w »

rob74 wrote: post #186
ben_w wrote: post #162

Earlier quoted context omitted.

The general argument you make is correct, but you conclusion "And this one doesn't." is as yet uncertain. I will absolutely say that all ML methods known are literally too stupid to live, as in no living thing can get away with making so many mistakes before it's learned anything, but that's the rate of change of performance with respect to examples rather than what it learns by the time training is finished. What is…

> no living thing can get away with making so many mistakes before it's learned anything If you consider that LLMs have already "learned" more than any one human in this world is able to learn, and still make those mistakes, that suggests there may be something wrong with this approach...

Not so: "Per example" is not "per wall clock".

To a limited degree, they can compensate for being such slow learners (by example) due to the transistors doing this learning being faster (by the wall clock) than biological synapses to the same degree to which you walk faster than continental drift. (Not a metaphor, it really is that scale difference).

However, this doesn't work on all domains. When there's not enough training data, when self-play isn't enough… well, this is why we don't have level-5 self-driving cars, just a whole bunch of anecdotes about various different self-driving cars that work for some people and don't work for other people: it didn't generalise, the edge cases are too many and it's too slow to learn from them.

So, are LLMs bad at… I dunno, making sure that all the references they use genuinely support the conclusions they make before declaring their task is complete, I think that's still a current failure mode… specifically because they're fundamentally different to us*, or because they are really slow learners?

* They *definitely are* fundamentally different to us, but is this causally why they make this kind of error?

Re: Bag of words, have mercy on us

#207

Post by littlestymaar »

quantummagic wrote: post #193
rob74 wrote: post #186

Earlier quoted context omitted.

> no living thing can get away with making so many mistakes before it's learned anything If you consider that LLMs have already "learned" more than any one human in this world is able to learn, and still make those mistakes, that suggests there may be something wrong with this approach...

But humans do the same thing. How many eons did we make the mistake of attributing everything to God's will, without a scientific thought in our heads? It's really easy to be wrong, when the consequences don't lead to your death, or are actually beneficial. The thinking machines are still babies, whose ideas aren't honed by personal experience; but that will come, in one form or another.

> The thinking machines are still babies, whose ideas aren't honed by personal experience; but that will come, in one form or another.

Some machines, maybe. But attention-based LLMs aren't these machines.

Re: Bag of words, have mercy on us

#208

Post by shawabawa3 »

nkrisc wrote: post #197
panarky wrote: post #152

Earlier quoted context omitted.

When someone says "AIs aren't really thinking" because AIs don't think like people do, what I hear is "Airplanes aren't really flying" because airplanes don't fly like birds do.

If I shake some dice in a cup are they thinking about what number they’ll reveal when I throw them?

that depends, if you explain the rules of the game you're playing and give the dice a goal to win the game, do they adjust the numbers they reveal according to the rules of the game?

If so, yes, they're thinking

Re: Bag of words, have mercy on us

#209

Post by danielbln »

thesz wrote: post #192
akoboldfrying wrote: post #112

Earlier quoted context omitted.

LLMs and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others? If it turns out that LLMs don't model human brains well enough to qualify as "learning abstract thought" the way humans do, some future technology will do so. Human brains aren't magic, special or different.

> Human brains aren't magic, special or different. DNA inside neurons uses superconductive quantum computations [1]. [1] https://www.nature.com/articles/s41598-024-62539-5 As the result, all living cells with DNA emit coherent (as in lasers) light [2]. There is a theory that this light also facilitates intercellular communication. [2] https://www.sciencealert.com/we-emit-a-visible-light-that-va... Chemical structures…

They are extremely complex, but is that complexity required for building a thinking machine? We don't understand bird physiology enough to build a bird from scratch, but an airplane flies just the same.

Re: Bag of words, have mercy on us

#210

Post by danielbln »

nkrisc wrote: post #197
panarky wrote: post #152

Earlier quoted context omitted.

When someone says "AIs aren't really thinking" because AIs don't think like people do, what I hear is "Airplanes aren't really flying" because airplanes don't fly like birds do.

If I shake some dice in a cup are they thinking about what number they’ll reveal when I throw them?

If I take a plane apart and throw all the parts off a cliff, will they achieve sustained flight?

If I throw some braincells into a cup alongside the dice, will they think about the outcome anymore than the dice alone?

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