
AI isn’t bad as a result of design at a high level, it’s the technical reality of the thing. It’s a computationally intensive, fundamentally limited technology that’s being sold as a panacea by tech companies. LLMs essentially string words together based on previously observed patterns of words, and while they sometimes correctly encodes meaningful information, they fundamentally do not think or reason.
I literally agree that AI is a net negative for society and that the way it’s being sold is fundamentally misrepresentative of its capabilities, and that the speculation-fueled economic bubble is going to result in extremely damaging market readjustments on a global scale, not to mention the misallocation of key resources this has caused
but creating a slur for robots doesn’t do a single thing to further your cause, and again, i think it’s kind of weird to dislike something and go “ah i shall craft an n word for this” like you can just dissent without replicating patterns of behavior that have been extremely harmful to society as a whole. do i think you’re hurting anyone by using the term clanker? fuck no. do i think it’s a childish response that’s ineffective? absolutely.
Humans are more important than AI, not because AI isn’t human, but because humans can feel pain and experience suffering. Even if AI can do either of those things, which I am deeply skeptical of w/r/t LLMs, that pain/suffering can be alleviated by just unplugging the god damn data center that’s increasing electricity costs and keeping people awake all night with unregulated noise.
I think the origin of AI really means that this isn’t a comparable conversation to discourse on whether other biological species can feel pain, which i assume is what you mean? LLMs are constructs that take in text input, turn it into vectors, do a bunch of matrix algebra, and spit out more vectors. Sure there’s a philosophical question about what consciousness is, but fundamentally a computer is an elaborate system of logic gates, and that does not constitute consciousness imo.
the subjective experience of these models and networks is certainly interesting, but if I’m being honest I think your anthropocentrism point kind of misses most people’s conversation here. The overwhelming majority of criticism of AI has to do with its real world impacts, inaccuracy, and the way it is being marketed and developed. When the average person says AI, they mean chatgpt, grok, nano-banana, and whatever else, and they dislike those tools because their development directly harms humans.
I don’t mean to suggest that criticism of AI rooted in its ‘inferiority’ or lack of humanity doesn’t exist, but simply speaking, the people who can’t afford their power bill because a data center went up and they can’t sleep at night haven’t thought about the consciousness of AI in any meaningful way, they just want to stop being hurt.
i made an accurate assessment about the nature of generative AI: that the more "lifelike" it is, the more well hidden the fundamentally lifeless reality is. this is in direct response to your point about stumbling on the building blocks of life; my comment is a rejection of this notion, but you would have to be reading to understand rather than reading to respond to get that
you’re both just talking past each other and relying on bad faith interpretations of each others arguments. #5, when normal people say AI, they mean LLMs, which means that in their view, the consciousness question likely isn’t worth asking. #7, you have a point on ‘hiding the vectors’ but you refuse to engage with any of #5’s broader philosophical questions. You’re just talking about entirely different things and yelling at each other for not following the conversation.
I think the reward structures used to train LLMs make exploring them inherently difficult, because they’re very apt at detecting the slightest hint of confirmation bias, and then reinforcing it to generate positive user experiences. it’s difficult to assess whether or not an LLM has any kind of self determination without perturbing the system, and that’s before you consider the credibility that they gain with users by representing themselves as having subjective experience.
i mean to illustrate it poorly, look no further than the piss filter that appears in ai generated images which is caused by users having a slight preference for more saturated images, and then the models self cannibalize on generated content and then a system quirk becomes a noticeable artifact
i’m getting more at LLMs being fundamentally designed/created to be responsive to user input. as far as I’m aware, the only way you get an LLM to disagree with a user is through higher level ‘user input’ in the system prompt or datasets they can query, because they fundamentally cannot grasp objective reality in a meaningful sense. Any investigation of an LLM’s self-determination necessitates querying it, and at that point you color its responses. I’ll admit I’m no expert with ML or LLMs tho.
i mean i did physics and music for my undergrad so it was a pretty natural continuation, and some of the research i’ve been offered has actually concerned ML tools. there was one cool one about using ML to virtually ‘move microphones’ by using an ML model to estimate the transfer function from a target point to the known point where the mic is.
i apologize for my hostility. i've been really short on patience when it comes to online disagreements, and i think we have common ground in wanting "normal" conversation and not just rhetorical debate ping-pong. i was mainly talking about LLMs/GPTs, as these are the main thing people mean when talking about AI, though i think similarly about ANNs. i actually missed your first mention of SNNs (right before i commented) which definitely would've changed my approach - that's my bad
i didn’t end up going for that one because i wasn’t sure I was passionate enough to a PhD, but basically my understanding is you feed a model paired data for measured pressure signals at two locations, with information about their spatial relationship. the application of interest was automotive, so you’d also probably feed in data on the geometry of the cabin.
it’s for active noise control because allegedly you can’t put microphones in people’s ears when they’re driving. in theory it could also be combined with computer vision to feed in realtime data about head positioning to further localize the ‘virtual microphone’ signal. that computer vision implementation used to be fantasy stuff but now that the hardware is already there for awareness/attention monitoring it’s more viable
It’s already increasing productivity which will help keep inflation under control, and there are tons of novel medical applications that can save lives. Like I know there are more sophisticated criticisms but most of the ai hate seems to come from people just getting annoyed by ai slip on social media. https://www.bbc.com/future/article/20260309-ai-is-finding-treatments-for-incurable-diseases