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All this anthropomorphizing of activation networks strikes me as very odd. None of these neurons "want" to do anything. They respond to specific input. Maybe hu

• lainga 3y ago
  Wait till you find out how we talk about evolutionary adaptation... a couple analogies and elided concepts here and there and you'd swear Lamarck had smothered Darwin in his cradle
  • jjw1414 3y ago
    Yes, Lamarck is alive and well. I frequently hear colleagues in biology with years of experience making lazy statements such as, "Humans evolved to walk because..." as if evolution is a conscious act. In many cases, these people are using the term evolution as shorthand for, "Random mutations gave rise to new gene variants (alleles), and over numerous generations, natural selection leads to an increase in the prevalence of beneficial variants, specifically those that provide a reproductive advantage. The genetic variants that combined to enable bipedal locomotion provided such an advantage to the human population". Evolution is a passive, natural process driven by genetic variation, environmental changes, and the differential reproductive success of individuals with advantageous traits. This in turn results in population changes. Evolution doesn't involve a conscious choice or direction. Evolution is the result of the cumulative effects of these factors over long periods of time.
    • idontpost 3y ago
      [dead]
    • dekhn 3y ago
      While I generally agree with you, is it really "lazy" to say "humans evolved to walk to"? Usually in the context, it's not being used to claim there is some sort of intent or purpose, but rather to shortcut the (rather verbose) description you gave. Also I can think of some counterpoints to yours: the people who bred teosinte into corn (or any wild grain into a domesticated one) appear to be making conscious choices or direction- that is, they used their intelligence and reasoning from observed examples of pairings to conclude that they could make improved specimens based on selective breeding (without knowing about random mutations of natural selection!). And if we start to modify human germline then would also be an example of evolution with conscious choice or direction (assuming the modifications became fixed in the population).
    • Sharlin 3y ago
      Even in math, the most exact of all fields of study, people in practice are being nonrigorous and ambiguous and take shortcuts all the time. That’s just how communication works, because it would be incredibly grating and inefficient to try to be 100% unambiguous when everybody already knows what you mean.
    • hoseja 3y ago
      Social, memetic evolution is at least partially Lamarckian.
• aatd86 3y ago
  Do you mean that artificial neurons are inherently passive while biological neurons are inherently active i.e. they would act in spite of external input? Just wondering if I understood you, I don't know anything on the subject.
  • baobabKoodaa 3y ago
    That was already addressed in the comment you're responding to. They wrote that in the case of artificial neural networks "at least we know [there is no god inside the machine]". With regards to humans, we don't know.
    • aatd86 3y ago
      That wasn't clear to me because having internal state doesn't mean that any process is running. That's the difference between memory and CPU.
    • TacticalCoder 3y ago
      There are a great many possibilities between: - a fully deterministic machine (even if the interface and the way OpenAI let people access ChatGPT make it seem like it's non-deterministic, there are fully deterministic models out there, who not only only respond to inputs but also always respond the exact same thing given the same inputs [query, seed, ...]), and: - god exists There could be chaos at work when human thinks. There may be interferences at play, say because whatever element that traveled trillion of kilometers just traversed our brain. While a fully deterministic machine that always respond to the same input in the same way is just that: a deterministic machine. P.S: I don't know about other LLMs like Falcon 180b but image-generation models like StableDiffusion are fully deterministic. I think a model is using a broken design and shall quickly hit limitations if it cannot be queried in a deterministic way (and its usecases are certainly limited if repeatability is not achievable). If you want different answers, use a different seed or a different query. But the same query+seed should always give the exact same output.
      • syntaxfree 3y ago
• Notatheist 3y ago
  I feel anthropomorphizing is perfectly reasonable especially in this context. How would you like it described?
  • janalsncm 3y ago
    There’s so much baggage attached with it. The only thing a neural network “wants” is to minimize its loss function. That’s all.
    • bobbylarrybobby 3y ago
      All humans “want” to do is obey the laws of physics.
    • csours 3y ago
      Can we anthropomorphize the loss function then?
      • dragonwriter 3y ago
        That's like anthropomorphizing utility functions in place of the humans that (are conjectured to) have them, isn't it?
    • srcreigh 3y ago
      You must not believe in human free will then. Or maybe you don’t believe the brain is the key aspect of human intelligence. Or believe the brain is more than just a organic NN
      • janalsncm 3y ago
        I’m saying that neural networks are so different from brains that anthropomorphizing them runs a real risk of glossing over important differences. Terms like “free will” and “intelligence” are too fuzzy to talk about precisely unless we’re on the exact same page regarding what we mean. And applying our imprecise definitions to machines is not doing us any favors.
• ShamelessC 3y ago
  Wait what are you referring to specifically? Any anthropomorphism in the article is _clearly_, clearly the author's admitted simplification due to the incredible density of the subject matter. Given that, I honestly can't find anything too upsetting. In any case, anthropomorphism is something I don't mind, mostly. Is it misleading? For the layman. But the domain is one of modeling intelligence itself and there are many instances where an existing definition simply makes sense. This happens in lots of fields and causes similar amounts of frustration in those fields. So it goes.
  • janalsncm 3y ago
    > Humans also use neural nets to reason about concepts. We have a lot of neurons, but so does GPT-4. I feel this is an abuse of the language. Biological neurons and ANN neurons aren’t the same or even all that similar. Brains don’t do backprop for example. Only forward passes. There’s a zoo of neurotransmitters which change the behavior of individual neurons or regions in the brain. Unused neurons in the brain can be repurposed for other things (for example if your arm is amputated).
    • famouswaffles 3y ago
      >Biological neurons and ANN neurons aren’t the same or even all that similar. They're not the same but they're definitely similar. >Brains don’t do backprop for example. We've developed numerous different learning algorithms that are biologically plausible, but they all kinda work like backpropagation but worse, so we stuck with backpropagation. We've made more complicated neurons that better resemble biological neurons, but it is faster and works better if you just add extra simple neurons, so we do that instead. Spiking neural networks have connection patterns more similar to what you see in the brain, but they learn slower and are tougher to work with than regular layered neural networks, so we use layered neural networks instead. The only reason modern NNs aren't closer to their biological counterparts is because they genuinely suffer for it. The secret of bird flight was wings. Not feathers. Not flapping.
      • tsimionescu 3y ago
• drones 3y ago
  All this anthropomorphizing of humans strikes me as very odd. None of these humans "want" to do anything. They respond to specific input. Maybe artificial neural networks are the same, but in the case of humans we at least know it's a simple reaction to neurotransmitter signals.
  • arolihas 3y ago
    You're probably just being tongue in cheek here, but I still wanted to add that we humans do actually "want". Desires, intentions, these are real things. You can try to represent them as loss functions or rewards in some mathematical model but that isn't the original thing. Consider this excerpt from https://scottaaronson.blog/?p=7094#comment-1947377 https://scottaaronson.blog/?p=7094#comment-1947377 > Most animals are goal-directed, intentional, sensory-motor agents who grow interior representations of their environments during their lifetime which enables them to successfully navigate their environments. They are responsive to reasons their environments affords for action, because they can reason from their desires and beliefs towards actions. In addition, animals like people, have complex representational abilities where we can reify the sensory-motor “concepts” which we develop as “abstract concepts” and give them symbolic representations which can then be communicated. We communicate because we have the capacity to form such representations, translate them symbolically, and use those symbols “on the right occasions” when we have the relevant mental states. (Discrete mathematicians seem to have imparted a magical property to these symbols that *in them* is everything… no, when I use words its to represent my interior states… the words are symptoms, their patterns are coincidental and useful, but not where anything important lies). In other words, we say “I like ice-cream” because: we are able to like things (desire, preference), we have tasted ice-cream, we have reflected on our preferences (via a capacity for self-modelling and self-directed emotional awareness), and so on. And when we say, “I like ice-cream” it’s *because* all of those things come together in radically complex ways to actually put us in a position to speak truthfully about ourselves. We really do like ice-cream.
    • Zambyte 3y ago
      > but I still wanted to add that we humans do actually "want". I would also like to add that the subject of conversation is artificial and natural neurons, which humans, though contain some, are not. If a NN is trained to do something, it can be equally considered as "wanting" to do that thing within the autonomy it is afforded, as much as any human.
• famouswaffles 3y ago
  >None of these neurons "want" to do anything. They respond to specific input. Yes well, your neurons don't "want" to do anything either. >Maybe humans are the same, but in the case of artificial neural networks we at least know it's a simple mathematical function So what, magic ? a soul ? If the brain is computing then the substrate is entirely irrelevant. Silicon, biology, pulleys and gears. all can be arranged to make the same or similar computations. If you genuinely believe the latter, it's fine. The point is that "simple" mathematical function is kind of irrelevant. Either the brain computes and any substrate is fine or it doesn't. >Also, an artificial neuron is nothing like a biological neuron. They're not the same but "nothing like" is pushing it a lot. They're inspired by biological neurons and the only reason modern NNs aren't closer to their biological counterparts is because they genuinely suffer for it, not because we can't. >Biological neurons fire because of their internal state, state which is modified by biological signaling chemicals Brains aren't breaking break causality. The fire because of input.
  • airgapstopgap 3y ago
    Comments like this are incredibly grating. You condescend to the interlocutor for making a mistake which only exists in your own mistaken world model. Your confidence that neurons and ANN weights and «pulleys and gears» are all equivalent because there is, in theory, an intention to instantiate some computation, and to think otherwise is tantamount to belief in magic and broken causality, is just confused and born out of perusing popular-scientific materials instead of relying on scientific literature or hands-on experience. > The fire because of input. No they do not fire because of input, they modulate their firing probability based on input, and there are different modalities of input with different effects. Neurons are self-contained biological units (descended, let me remind you, from standalone unicellular organisms, just like the rest of our cells), which actually have an independently developing internal state and even metabolic needs; they are not merely a system of logic gates even if you can approximate their role with a system of equations or an ANN. This is very different, mechanistically and teleologically. Hell, even spiking ANNs would be substantially different from currently dominant models. > So what, magic ? a soul ? If the brain is computing then the substrate is entirely irrelevant Stop dumbing down complex arguments to some low-status culture war opinion you find it easy to dunk on.
• benchaney 3y ago
  Can you be more specific about what particular anthropomorphizing you object to? The only place the author uses the word want is in describing the wants of humans.
• gremlinunderway 3y ago
  I think you're being a bit pedantic here. Neurons also don't "respond" to specific input either. They can't speak or provide an answer to your input. These are all just abstract metaphors and analogies. Literally everything in computer science at some point or another is an abstract metaphor or analogy. When you look up the definition and etymology of "input", it says to "put on" or "impose" or "feed data into the machine". We're not literally feeding the machine data, it doesn't eat the data and subsist on it. You could go on and on and nitpick every single one of these, and I don't think the use of "want" (i.e. anthropomorphizing the networks to have intent) is all that bad.
• clbrmbr 3y ago
  I didn’t hear much anthropomorphism outside of the subtitle. Anyways, this is Scott’s writing style. I recall an earlier ACX post on alignment that was real heavy on ascribing desires and goals to AI models.