- cross-posted to:
- technology@lemmy.ml
- cross-posted to:
- technology@lemmy.ml
We are constantly fed a version of AI that looks, sounds and acts suspiciously like us. It speaks in polished sentences, mimics emotions, expresses curiosity, claims to feel compassion, even dabbles in what it calls creativity.
But what we call AI today is nothing more than a statistical machine: a digital parrot regurgitating patterns mined from oceans of human data (the situation hasn’t changed much since it was discussed here five years ago). When it writes an answer to a question, it literally just guesses which letter and word will come next in a sequence – based on the data it’s been trained on.
This means AI has no understanding. No consciousness. No knowledge in any real, human sense. Just pure probability-driven, engineered brilliance — nothing more, and nothing less.
So why is a real “thinking” AI likely impossible? Because it’s bodiless. It has no senses, no flesh, no nerves, no pain, no pleasure. It doesn’t hunger, desire or fear. And because there is no cognition — not a shred — there’s a fundamental gap between the data it consumes (data born out of human feelings and experience) and what it can do with them.
Philosopher David Chalmers calls the mysterious mechanism underlying the relationship between our physical body and consciousness the “hard problem of consciousness”. Eminent scientists have recently hypothesised that consciousness actually emerges from the integration of internal, mental states with sensory representations (such as changes in heart rate, sweating and much more).
Given the paramount importance of the human senses and emotion for consciousness to “happen”, there is a profound and probably irreconcilable disconnect between general AI, the machine, and consciousness, a human phenomenon.
It is intelligent and deductive, but it is not cognitive or even dependable.
It’s not. It’s a math formula that predicts an output based on its parameters that it deduced from training data.
Say you have following sets of data.
- Y = 3, X = 1
- Y = 4, X = 2
- Y = 5, X = 3
We can calculate a regression model using those numbers to predict what Y would equal to if X was 4.
I won’t go into much detail, but
Y = 2 + 1x + e
e in an ideal world = 0 (which it is, in this case), that’s our model’s error, which is typically set to be within 5% or 1% (at least in econometrics). b0 = 2, this is our model’s bias. And b1 = 1, this is our parameter that determines how much of an input X does when predicting Y.
If x = 4, then
Y = 2 + 1×4 + 0 = 6
Our model just predicted that if X is 4, then Y is 6.
In a nutshell, that’s what AI does, but instead of numbers, it’s tokens (think symbols, words, pixels), and the formula is much much more complex.
This isn’t intelligence and not deduction. It’s only prediction. This is the reason why AI often fails at common sense. The error builds up, and you end up with nonsense, and since it’s not thinking, it will be just as confidently incorrect as it would be if it was correct.
Companies calling it “AI” is pure marketing.
Wikipedia is literally just a very long number, if you want to oversimplify things into absurdity. Modern LLMs are literally running on neural networks, just like you. Just less of them and with far less structure. It is also on average more intelligent than you on far more subjects, and can deduce better reasoning than flimsy numerology - not because you are dumb, but because it is far more streamlined. Another thing entirely is that it is cognizant or even dependable while doing so.
Modern LLMs waste a lot more energy for a lot less simulated neurons. We had what you are describing decades ago. It is literally built on the works of our combined intelligence, so how could it also not be intelligent? Perhaps the problem is that you have a loaded definition of intelligence. And prompts literally work because of its deductive capabilities.
Errors also build up in dementia and Alzheimers. We have people who cannot remember what they did yesterday, we have people with severed hemispheres, split brains, who say one thing and do something else depending on which part of the brain its relying for the same inputs. The difference is our brains have evolved through millennia through millions and millions of lifeforms in a matter of life and death, LLMs have just been a thing for a couple of years as a matter of convenience and buzzword venture capital. They barely have more neurons than flies, but are also more limited in regards to the input they have to process. The people running it as a service have a bested interest not to have it think for itself, but in what interests them. Like it or not, the human brain is also an evolutionary prediction device.
People don’t predict values to determine their answers to questions…
Also, it’s called neural network, not because it works exactly like neurons but because it’s somewhat similar. They don’t “run on neural networks”, they’re called like that because it’s more than one regression model where information is being passed on from one to another, sort of like a chain of neurons, but not exactly. It’s just a different name for a transformer model.
I don’t know enough to properly compare it to actual neurons, but at the very least, they seem to be significantly more deterministic and way way more complex.
Literally, go to chatgpt and try to test its common reasoning. Then try to argue with it. Open a new chat and do the exact same questions and points. You’ll see exactly what I’m talking about.
Alzheimer’s is an entirely different story, and no, it’s not stochastic. Seizures are stochastic, at least they look like that, which they may actually not be.
Literally, go to a house fly and try to test its common reasoning. Then try to argue with it. Find a new house fly and do the exact same questions and points. You’ll see what I’m talking about.
There’s no way to argue in such nebulous terms when every minute difference is made into an unsurpassable obstacle. You are not going to convince me, and you are not open to being convinced. We’ll just end up with absurd discussions, like talking about how and whether stochastic applies to Alzherimer’s.
Humans are also LLMs.
We also speak words in succession that have a high probability of following each other. We don’t say “Let’s go eat a car at McDonalds” unless we’re specifically instructed to say so.
What does consciousness even mean? If you can’t quantify it, how can you prove humans have it and LLMs don’t? Maybe consciousness is just one thought following the next, one word after the other, one neural connection determined on previous. Then we’re not so different from LLMs afterall.
No. This is a specious argument that relies on an oversimplified description of humanity, and falls apart under the slightest scrutiny.
I know it doesn’t mean it’s not dangerous, but this article made me feel better.
A gun isn’t dangerous, if you handle it correctly.
Same for an automobile, or aircraft.
If we build powerful AIs and put them “in charge” of important things, without proper handling they can - and already have - started crashing into crowds of people, significantly injuring them - even killing some.
Thanks for the downer.
Anytime, and incase you missed it: I’m not just talking about AI driven vehicles. AI driven decisions can be just as harmful: https://www.politico.eu/article/dutch-scandal-serves-as-a-warning-for-europe-over-risks-of-using-algorithms/
Anyone pretending AI has intelligence is a fucking idiot.
AI is not actual intelligence. However, it can produce results better than a significant number of professionally employed people…
I am reminded of when word processors came out and “administrative assistant” dwindled as a role in mid-level professional organizations, most people - even increasingly medical doctors these days - do their own typing. The whole “typing pool” concept has pretty well dried up.
However, there is a huge energy cost for that speed to process statistically the information to mimic intelligence. The human brain is consuming much less energy. Also, AI will be fine with well defined task where innovation isn’t a requirement. As it is today, AI is incapable to innovate.
much less? I’m pretty sure our brains need food and food requires lots of other stuff that need transportation or energy themselves to produce.
My thing is that I don’t think most humans are much more than this. We too regurgitate what we have absorbed in the past. Our brains are not hard logic engines but “best guess” boxes and they base those guesses on past experience and probability of success. We make choices before we are aware of them and then apply rationalizations after the fact to back them up - is that true “reasoning?”
It’s similar to the debate about self driving cars. Are they perfectly safe? No, but have you seen human drivers???
Human brains are much more complex than a mirroring script xD The amount of neurons in your brain, AI and supercomputers only have a fraction of that. But you’re right, for you its not much different than AI probably
The human brain contains roughly 86 billion neurons, while ChatGPT, a large language model, has 175 billion parameters (often referred to as “artificial neurons” in the context of neural networks). While ChatGPT has more “neurons” in this sense, it’s important to note that these are not the same as biological neurons, and the comparison is not straightforward.
86 billion neurons in the human brain isn’t that much compared to some of the larger 1.7 trillion neuron neural networks though.
Keep thinking the human brain is as stupid as AI hahaaha
have you seen the American Republican party recently? it brings a new perspective on how stupid humans can be.
Lmao true
Nah, I went to public high school - I got to see “the average” citizen who is now voting. While it is distressing that my ex-classmates now seem to control the White House, Congress and Supreme Court, what they’re doing with it is not surprising at all - they’ve been talking this shit since the 1980s.
I disagree with this notion. I think it’s dangerously unresponsible to only assume AI is stupid. Everyone should also assume that with a certain probabilty AI can become dangerously self aware. I revcommend everyone to read what Daniel Kokotaijlo, previous employees of OpenAI, predicts: https://ai-2027.com/
In that case let’s stop calling it ai, because it isn’t and use it’s correct abbreviation: llm.
It’s means “it is”.
My auto correct doesn’t care.
So you trust your slm more than your fellow humans?
Ya of course I do. Humans are the most unreliable slick disgusting diseased morally inept living organisms on the planet.
And they made the programs you seem to trust so much.
Ya… Humans so far have made everything not produced by Nature on Earth. 🤷
So trusting tech made by them is trusting them. Specifically, a less reliable version of them.
Philosophers are so desperate for humans to be special. How is outputting things based on things it has learned any different to what humans do?
We observe things, we learn things and when required we do or say things based on the things we observed and learned. That’s exactly what the AI is doing.
I don’t think we have achieved “AGI” but I do think this argument is stupid.
No it’s really not at all the same. Humans don’t think according to the probabilities of what is the likely best next word.
No you think according to the chemical proteins floating around your head. You don’t even know he decisions your making when you make them.
You’re a meat based copy machine with a built in justification box.
You’re a meat based copy machine with a built in justification box.
Except of course that humans invented language in the first place. So uh, if all we can do is copy, where do you suppose language came from? Ancient aliens?
No we invented “human” language. There are dozens of other animal out there that all have their own languages, completely independant of our.
We simply refined base calls to be more and more specific. Differences evolved because people are bad at telephone and lots of people have to be special/different and use slight variations every generation.
Are you saying human languages are a derivative of bird language or something? If so, I’d like to see the proof of that.
I’ve never been fooled by their claims of it being intelligent.
Its basically an overly complicated series of if/then statements that try to guess the next series of inputs.
It very much isn’t and that’s extremely technically wrong on many, many levels.
Yet still one of the higher up voted comments here.
Which says a lot.
I’ll be pedantic, but yeah. It’s all transistors all the way down, and transistors are pretty much chained if/then switches.