As a software developer who took an elective in neural networks - when people call LLMs stochastic parrots, that's not criticism of their results.
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R relay@relay.an.exchange shared this topic
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As a software developer who took an elective in neural networks - when people call LLMs stochastic parrots, that's not criticism of their results.
It's literally a description of how they work.
The so-called training data is used to build a huge database of words and the probability of them fitting together.
Stochastic because the whole thing is statistics.
Parrot because the answer is just repeating the most probable word combinations from its training dataset.Calling an LLM a stochastic parrot is lile calling a car a motorised vehicle with wheels. It doesn't say anything about cars being good or bad. It does, however, take away the magic. So if you feel a need to defend AI when you hear the term stochastic parrot, consider that you may have elevated them to a god-like status, and that's why you go on the defense when the magic is dispelled.
@leeloo If I want to disparage, I say "LLMs are just a word list with a randomizer". It's slightly less accurate, because it's a very specific kind of word list and a likewise specific kind of randomizer, but it gets the cultists all riled up. So that's cool.
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As a software developer who took an elective in neural networks - when people call LLMs stochastic parrots, that's not criticism of their results.
It's literally a description of how they work.
The so-called training data is used to build a huge database of words and the probability of them fitting together.
Stochastic because the whole thing is statistics.
Parrot because the answer is just repeating the most probable word combinations from its training dataset.Calling an LLM a stochastic parrot is lile calling a car a motorised vehicle with wheels. It doesn't say anything about cars being good or bad. It does, however, take away the magic. So if you feel a need to defend AI when you hear the term stochastic parrot, consider that you may have elevated them to a god-like status, and that's why you go on the defense when the magic is dispelled.
nope. What you describe as "stocastical parrot" is Markov, Hidden Markov Model (HMM) , not a VLLM.
You can find an HMM in your mobile phone, AKA T9, AKA "keyboard suggestions".
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R relay@relay.mycrowd.ca shared this topic
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nope. What you describe as "stocastical parrot" is Markov, Hidden Markov Model (HMM) , not a VLLM.
You can find an HMM in your mobile phone, AKA T9, AKA "keyboard suggestions".
@uriel
What part exactly are you saying nope to.Dispelling the magic and god-like status or some specific detail?
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@uriel
What part exactly are you saying nope to.Dispelling the magic and god-like status or some specific detail?
nope to the bunch of bullshit you wrote under the assumption a VLLM is a Hidden Markov Model , aka "stochastic parrot".
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@calcifer
> But the hype is unreal and legitimately dangerous.I blame Sam Altman for that 100%
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nope to the bunch of bullshit you wrote under the assumption a VLLM is a Hidden Markov Model , aka "stochastic parrot".
@uriel
Ah, so you are saying that you decided that I said something I never did, and then saying nope to that, so that you can pretend that you have a real argument.Like when creationists try arguing against evolution using pseudo-scientific arguments to hide that they are defending the bible.
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As a software developer who took an elective in neural networks - when people call LLMs stochastic parrots, that's not criticism of their results.
It's literally a description of how they work.
The so-called training data is used to build a huge database of words and the probability of them fitting together.
Stochastic because the whole thing is statistics.
Parrot because the answer is just repeating the most probable word combinations from its training dataset.Calling an LLM a stochastic parrot is lile calling a car a motorised vehicle with wheels. It doesn't say anything about cars being good or bad. It does, however, take away the magic. So if you feel a need to defend AI when you hear the term stochastic parrot, consider that you may have elevated them to a god-like status, and that's why you go on the defense when the magic is dispelled.
Oh, the good old “I was misunderstood.” I genuinely hope your communication skills improve someday, so you can finally express your ideas clearly
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nope to the bunch of bullshit you wrote under the assumption a VLLM is a Hidden Markov Model , aka "stochastic parrot".
@uriel
What I'm saying is that you are beating a strawman of your own making and putting words in my mouth. -
@robotistry
@leeloo
so it's a parrot not because it's a matrix of probabilities, but because its hasn't experienced the real-world consequences of its words/actions and updated the probabilities based on those consequences?@wolf480pl @leeloo No. Maybe this will help.
0: one action, no choice (clockwork automaton, wind-up toy)
1: different actions, no choices (RC car)
2: choice, no plan (reactive robot)
3a: plan, no on-line or off-line learning (adaptive robot)
3b: plan, no on-line learning (same number for 3a and 3b because these are effectively the same when operating)
4: on-line learning - but only what and how it has been told
5a: ability to spontaneously generate new categories of output without being explicitly asked or told to do so (WBEAT)
5b: ability to spontaneously identify new categories of the same kinds of input WBEAT
6: ability to spontaneously identify new kinds of things to learn WBEAT
7: ability to spontaneously identify new ways to learn WBEAT
8: ability to choose new things to learn WBEATLLMs that you're not training are category 3b. They are static machines, responding to your input like an elevator responding to a button push.
LLMs that learn are category 4.
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@wolf480pl @leeloo No. Maybe this will help.
0: one action, no choice (clockwork automaton, wind-up toy)
1: different actions, no choices (RC car)
2: choice, no plan (reactive robot)
3a: plan, no on-line or off-line learning (adaptive robot)
3b: plan, no on-line learning (same number for 3a and 3b because these are effectively the same when operating)
4: on-line learning - but only what and how it has been told
5a: ability to spontaneously generate new categories of output without being explicitly asked or told to do so (WBEAT)
5b: ability to spontaneously identify new categories of the same kinds of input WBEAT
6: ability to spontaneously identify new kinds of things to learn WBEAT
7: ability to spontaneously identify new ways to learn WBEAT
8: ability to choose new things to learn WBEATLLMs that you're not training are category 3b. They are static machines, responding to your input like an elevator responding to a button push.
LLMs that learn are category 4.
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@wolf480pl @leeloo Examples:
Category 5a: a text-based LLM that spontaneously, without being asked, learns to output musical notation.
Category 5b: a text-based LLM that spontaneously, unprompted, without being asked, learns that filenames can be used as input.
Category 6: a text-based LLM that spontaneously, without being asked (directly or indirectly) learns that it can output ascii images or generate sounds instead of sentences.
Category 7: a text-based LLM spontaneously changes its underlying code so that it can learn how to write novels by memorizing and imitating performances instead of via a matrix of probabilities (fundamental change to its internal capabilities)
Category 8: a text-based LLM chooses when to interact with the world.
(The original categories I developed years ago were based on what the system can modify: its weights, how many weights, what kinds of weights, etc. I think this might be clearer?)
I don't think even Moltbook is showing anything above 4.
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As a software developer who took an elective in neural networks - when people call LLMs stochastic parrots, that's not criticism of their results.
It's literally a description of how they work.
The so-called training data is used to build a huge database of words and the probability of them fitting together.
Stochastic because the whole thing is statistics.
Parrot because the answer is just repeating the most probable word combinations from its training dataset.Calling an LLM a stochastic parrot is lile calling a car a motorised vehicle with wheels. It doesn't say anything about cars being good or bad. It does, however, take away the magic. So if you feel a need to defend AI when you hear the term stochastic parrot, consider that you may have elevated them to a god-like status, and that's why you go on the defense when the magic is dispelled.
@leeloo A much better answer is "So are humans".
(according to everything we've so far been able to document regarding our own processes)
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R relay@relay.infosec.exchange shared this topic
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@leeloo A much better answer is "So are humans".
(according to everything we've so far been able to document regarding our own processes)
@troed
The part that we understand about how our brain works is so simple that we can understand it.The rest, we have no clue about.
Replicating the simple parts and pretending that will get us anywhere close to intelligence is the kind of magic I'm talking about.
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@troed
The part that we understand about how our brain works is so simple that we can understand it.The rest, we have no clue about.
Replicating the simple parts and pretending that will get us anywhere close to intelligence is the kind of magic I'm talking about.
@leeloo We don't know that. It's equally likely that we have a belief in that there must be some kind of "magic" in our brains that there simply isn't.
From a physics standpoint there can be no magic - the brain is just a large neural network with various inputs (wind blowing on arm hair etc) that results in outputs (mouth moving).
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@leeloo We don't know that. It's equally likely that we have a belief in that there must be some kind of "magic" in our brains that there simply isn't.
From a physics standpoint there can be no magic - the brain is just a large neural network with various inputs (wind blowing on arm hair etc) that results in outputs (mouth moving).
@troed
Be specific. "We don't know that" does not tell me anything about which part of my reply you are referring to.Especially as my comment was a combination of obvious statements and claims that we don't know.
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@troed
Be specific. "We don't know that" does not tell me anything about which part of my reply you are referring to.Especially as my comment was a combination of obvious statements and claims that we don't know.
@leeloo We don't know that there are other things happening in the brain than what we have already documented.
The belief that there's "magic" happening in the brain is part of the argument between dualists and monists - that there's somehow a "mind" that's separate from the body. So far we've found nothing to support such a claim.
(My own studies in neuroscience are a decade old but I do follow the discourse)
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@lmorchard @leeloo @wolf480pl I guess part of it is maybe that I don't think intelligence is some exclusively human thing. LLMs clearly aren't human-like intelligent. I'm personally confident they're not as intelligent as any primate.
But are they as intelligent as a shrimp? I think they've got to be more intelligent than a mosquito.
I wouldn't turn to a shrimp for advice but they're not *without* intelligence.
@dragonfrog
I think an ML model trained to speedrun a platformer game is intelligent like a mosquito, but LLMs probably aren't.
@lmorchard @leeloo -
@leeloo We don't know that there are other things happening in the brain than what we have already documented.
The belief that there's "magic" happening in the brain is part of the argument between dualists and monists - that there's somehow a "mind" that's separate from the body. So far we've found nothing to support such a claim.
(My own studies in neuroscience are a decade old but I do follow the discourse)
@troed
If we are nothing but input -> math -> output, then human rights don't matter. Murdering someone is no different from switching a device off.If that's the world view you want to argue, that's on you.
It also assumes that there are nothing left to discover. Which has been a mistake every time anyone has made the claim in any other area. Are humans really that much simpler than the rest of the universe?
To be clear, I did not say that there is any kind of magic involved in human intelligence. I said that the part of "AI" that people get on the defence over when we reduce it to math and software is magic, because unlike humans - where I must remind you that I said we don't know - we know exacly what those datacenters are doing: Math and software.
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@troed
If we are nothing but input -> math -> output, then human rights don't matter. Murdering someone is no different from switching a device off.If that's the world view you want to argue, that's on you.
It also assumes that there are nothing left to discover. Which has been a mistake every time anyone has made the claim in any other area. Are humans really that much simpler than the rest of the universe?
To be clear, I did not say that there is any kind of magic involved in human intelligence. I said that the part of "AI" that people get on the defence over when we reduce it to math and software is magic, because unlike humans - where I must remind you that I said we don't know - we know exacly what those datacenters are doing: Math and software.
@leeloo I'm not arguing for a worldview - I'm just talking about what's the current state of science on the topic.
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@leeloo I'm not arguing for a worldview - I'm just talking about what's the current state of science on the topic.
@troed
Yet you couldn't simply let my claim stand that we don't know what lied beyond the current state.
