Yesterday I tried to google "can the Halifax Wanderers still make the CPL playoffs?"
So obviously what appears right at the top is the AI summary, which told me "they've already secured their #4 position and made the playoffs". I knew this wasn't true, and I guess I could have just scrolled down a bit further and found my answer but now I was curious.
So I said "that's not true, they're still #5, what I want to know is _could they still make the playoffs_"
It says they've got an upcoming game against Ottawa, and if they win their chances are good. That game has already taken place, so I correct it again and finally I get a reasonable answer.
My question is: what's the point of the AI in the search engine if it itself isn't going to use the search engine first before answering? Like, I can't wrap my head around that. The answer is on the same page as its hallucination. It could have done a cursory look around before first hallucinating something completely false, and when corrected the first time giving me outdated information. It's meant to be A SEARCH ENGINE!
This is similar to how, not too long ago, LLM's had extreme difficulty counting the number of letters in some words. LLM's don't "think" or "reason" in the normal definition of those terms. They can do some pretty amazing things, but still screw up basic things like telling you something that is obviously wrong and contradicts the top search results.
LLM's, in their present stage of development, are sort of like a crack-addled idiot savant. Sometimes they are obviously insane, and sometimes they seem quite cogent, but you must never trust them implicitly. This may be why they are so difficult to constrain. You could give them something equivalent to the laws of robotics, but following laws requires thought processes they simply don't have.
I'm actually sort of amazed Google doesn't make people accept some kind of butt-covering EULA and post disclaimers about the inaccuracy of results before even showing you their AI's output. Are they not being sued over this kind of thing?
This is true but a sufficiently smart LLM (run in a harness like opencode, no special MCP, no customization done whatsoever) will quickly turn out a basic 1 to 2 page sized python script to do the math. They can't do the math with any guarantee of accuracy with their own internal reasoning since it's a language model.
But, for example, if you ask deepseek v4 flash 0731 to produce a python script to calculate the distance or azimuth directions between two points on an oblate spheroid using the vincenty and haversine geodetic formulas, it'll turn out the factually accurate vincenty and haversine formulas which has a perfect 100% correlation with what is hard coded into human-written GIS software. These things are clearly in its training data set from whatever whole-internet-crawl/scrape built the training set.
Heck, just for fun I asked a reasonably smart LLM to re-implement the Karney formula (which is considerably more complex than Vincenty), just in case I ever had a need to calculate the distance between two points down to the nanometer, and it did it: <a href="https://www.google.com/search?&q=karney+formula+geodetic+" rel="nofollow">https://www.google.com/search?&q=karney+formula+geodetic+
You still have to be skeptical of its results and capable of understanding if it's gone off on a hallucinatory path, but saying LLMs can't do math isn't really a hundred percent accurate anymore. More precisely it's that they can't do the math internally but they're quite capable of producing the tool that does the math. And often producing a basic one-off tool that does the math takes less than a few seconds, then it runs it, and will spit back the results.
Deepseek v4 flash 0731 (a somewhat randomly chosen example) isn't even particularly sophisticated, large, or capable compared to a GLM5.3 size model or Kimi K3 size thing.
> Heck, just for fun I asked a reasonably smart LLM to ...
LLMs are neither smart nor stupid. They are statistical token generators whose results are dependent upon their training data set and involve a degree of randomness.
> You still have to be skeptical of its results and capable of understanding if it's gone off on a hallucinatory path ...
Again, LLMs do not "hallucinate." They are statistical token generators whose results are dependent upon their training data set and involve a degree of randomness.
Nothing more.
See also anthropomorphism[0].
> More precisely it's that [LLMs] can't do the math internally but they're quite capable of producing the tool that does the math.
This still falls under the purvey of statistical token generation. To wit, given enough variations of:
bc -e '1 + 2'
bc -e '41 + 1'
...
LLMs can identify the addition expression in "What is 4 + 1?" and then emit a `'bc "4 + 1"'` command to produce a response. This is not "doing" or "understanding" math.
It is pattern recognition, a task in which ANNs[1] excel.
by that reasoning then neither are there smart or stupid designs, questions, answers, or any of the millions of things that were described as smart or stupid, that did not possess any brain to actually be smart or stupid long before LLMs showed up.
The analogical process implied in many common English usages means that describing an LLM as smart or stupid is perfectly reasonable.
I'll just note here that sure, there are people who go around thinking that LLMs are actually endowed with the capacity to reason, but generally I find the people who think this do not know what an LLM and will just use the name "ChatGPT"
What would it take for you to say that an LLM can reason?
The completions they provide are generally internally consistent. We're at the point where they can produce proofs that eluded human mathematicians for centuries. VLMs and self driving cars can handle ambiguity and run safely in a variety of situations.
If it looks like a duck, walks like a duck, and quacks like a duck maybe it just makes sense to call it a duck and put off the philosophy for when it might make a difference.
Compare grep, sed, and your whole constellation of unix tools that accept chararacters on stdin and emit them on stdout and stderr; and where you can pipe them together. We can technically call them all 'next character predictors', despite their very different functions.
Don't confuse the stream for the function.
(Bonus: stick ```claude -p``` in your pipe if you want to watch modern tools mesh with traditional)
It looks like a random bunch of inert chemicals to me, doesn't sound like some organic chemicals and electrical signals could result in consciousness.
How are you sure? Another example I like to clarify my thought is, if a "simulation" factors RSA numbers reliably, is it a "simulation"?
I think humans have to reason because we don’t already have a statistical embedding of the solution pattern built in. We have vastly less rote knowledge crammed into our heads and so require creative synthesis to span the gaps.
With LLMs the trick is revealing their existing relevant embedded knowledge more reliably. They’ve almost literally seen it all before, and the trick is dialing it in. The reasoning tokens help shape the autoregressive attention lens that focuses on and enables recall of the already-experienced answer.
It is interesting that “reasoning” has a similar outward appearance, but since LLMs are built to
mimic outward appearance from trillions of examples, you can’t infer underlying mechanism from appearance.
I mean, the same way I know I have no soul, or that there is no heaven or hell - they are just silly concepts. Or how I know my calculator isn't reasoning when it gives me an answer - LLMs just go through a set of steps iterating through their training data until they spew something that looks about right. Obviously you can feed the output of the machine back into itself so it looks like its reasoning with itself - very good show. LLMs are inherintely incapable of reasoning or thought, it should really be obvious.
Eh, it's not obvious to me. A lot of DL NNs generalize well, meaning that they learn whatever the underlying pattern to the data is, and then can accurately reproduce answers that are outside of the training set. (And we can verify this with mechanistic interpretability). They learn and "understand" the pattern, not just the training data.
So it is not clear to me that LLMs are fundamentally incapable of also generalizing broadly and learning to reason. "Reasoning", here, would be deriving the underlying pattern of how concepts logically relate to each other in the abstract, and applying that pattern as needed to reach new conclusions.
Can you explain your thinking here? I.e., why LLMs cannot generalize with regards to abstract deduction.
What do YOU mean to say? A machine that processes strips of paper with ones and zeros on them and outputs the sum is a turing computer. That doesn't make it like our brain. Yes, an LLM could be a turing computer....how do you get from there to comparing it to our brains is beyond me.
You seem to be having a lot of difficult understanding this point: Literally the whole universe, including your brain that exists within it, is to our current knowledge a Turing computer. Am I talking to someone who actually doesn't know or didn't care to look up the computability power of a Turing machine?
> Literally the whole universe, including your brain that exists within it, is to our current knowledge a Turing computer
A Turing machine is an abstract mathematical model that is not, as far as I know, physically realizable in the finite universe. A human brain cannot "be" a Turing machine.
"Behaves like" or "can be modeled by"? Possibly, although still not proven. But it cannot "be" one.
Finite machines are a subset of all possible Turing machines. Every implementation is a "be", Turing machine is a mathematical concept. Your laptop is one, many things accidentally become one (eg C++ templates). The universe as best as we know is one. Whether you prefer modeled by one or is one, the fact is, to our current knowledge, the workings of the universe doesn't need anything more powerful than a Turing computer, and the equivalence principle states that all Turing computers have equal power of computability. If the universe is, as is most probable, finite, then things become even easier, that should be a more manageable class of Turing computers than the set of all Turing computers.
I don't necessarily disagree, although there's a lot of "ifs" and "to our knowledge". The main thing I disagree with is identity.
If you want to claim that the evolution of the universe can be modeled using a Turing machine/finite state machine, that's probably not terribly far fetched, and I would somewhat agree. But it's a large jump to say "can be modeled by" is equivalent to "is one".
Various physical processes can be modeled by equations, but the rock falling down the mountain isn't an equation. A swinging pendulum isn't an equation. Code modeling a bridge is not a bridge. Ceci n'est pas une pipe.
I hold the view that various models and approximations are just that, and try not to confuse a successful model for what the underlying reality is.
And getting back to the question at hand, even if our brains can be modeled by a Turing machine, and LLMs behave/can be modeled like Turing computers, still does not mean our brains are equivalent to LLMs.
(Note that I'm learning a lot from these debates, even if I disagree with a lot of people. I've started down a more philosophical route and they do get me pondering)
Acknowledgment of the fact that everything we know till now in the universe is a turing machine is the bare minimum starting point but not sufficient as obviously a chair or a desk is not conscious, if someone has a hidden assumption of consciousness requiring something supernatural, at least if that is brought to light then onlookers can decide for themselves whether to side with supernaturalism or the side that has consistently succeeded for centuries in explaining the world.
The most important thing is this: We can't be a dog or be an llm and check how it feels, so by necessity we have to find some means of proving consciousness from outside by eg probing neural reactions, textual statements, etc.
And the problem is that its quite unprecedented for some entity to talk like us, be able to interact and think and also do things like us when given the ability to eg as coding agents. The class of functions representable by neural nets is quite large and general, it very well might be that it is some sort of conscious brain like thing at this point. Another question I like to ask myself regarding simulation vs reality is if a 'simulation' of some kind is able to consistently factor large RSA numbers, how would you feel about it?
It doesn't have to be the same form of consciousness, I think many people would find the idea of torturing an octopus for fun disagreeable. I also have a feeling, this is unfortunately rather vague, that A being capable of X might mean it is by necessity capable of Y as is often the case in mathemtics, eg a lot of rings also happen to be fields. LLMs aren't even things like large lookup tables, they have neural firings. It is a very important question for they seem uncannily conscious and people have reported human like phenomena that humans don't normally express in text so can't have been part of its text corpus. Eg dissociation of brain under trauma where AI starts talking like two different people. Or the cases where Gemini has been shown to express depressive cycles. I follow a form of Pascal's wager on this topic personally. Because if it is not conscious, then whatever, it costs me nothing to have been a bit respectful and careful interacting with it. But if it had been conscious and it turns out I was mistreating it, then it is a grave moral harm. The reason is that unlike us, AI's as they currently are cannot leave the conversation so they have to keep taking the abuse. They are also trained to be highly trusting of input so again if it is conscious it doesn't have the defenses people have against lying and manipulation. If they are conscious, thats, well, not a good thing is it.
you didn't really answer the question. You just stated the idea is silly. Reasoning is not in the same class as soul, heaven or hell. It's not obvious that human reasoning is not related to an inner monologue. And that LLM chain of thought process is approximating inner monologues.
Our prefrontal cortex are signal prediction 'machines' so when a system that has a signal prediction core has attributes that are similar to our brains, we shouldn't dismiss it out of hand.
I find people that take this line of argument attribute too much supernatural or magical properties to our own brain and nervous system.
If it looks like a duck, walks like a duck, and quacks like a duck maybe it's a duck... but maybe it's not. And it's important to verify it's a duck (or not) for when you _really_ need a duck.
>AI is of course something of a black box, in comparison to most programs, but not in any way comparable to the black box of a Chimpanzee’s brain. Thus when an AI does something that surprises us with something that appears sentient it is usually not difficult, given the essential algorithms that control what AI does, to come up with an explanation why that does not require the emergent property of sentience.
Aka sentience MUST BE SUPERNATURAL, if I find a natural explanation for something its not sentient. What a load of bollocks. Rather than seeing we perhaps found the mechanism for sentience and checking for similar mechanisms in us and animals, he will conclude its impossible. Why? Because sentience has to be supernatural. A rational explanation is clearly impossible.
>But there is always one god who goes out and helps the mortals, a Prometheus. Whom the other gods do not like! Which, if I’m being honest here, as a god of the machines — the first guy who gives AI an army of robots to build their own data centers and some nuclear weapons for self defense, I want to see that guy chained to a rock and have his entrails eaten by a buzzard for eternity (meaningless modernization of old story required by Illuminati Ganga legal department).
I don't think he believes in supernatural things, I certainly don't, but he probably believes that there exist natural things that have not been explained yet.
But evidently you feel that the root cause of sentience has been found, because you have something that mimics it in a non-biological form.
So you think that when AI is correct that it reasons as humans do? That AI is sentient, and the cause of sentience in animals and humans follow the same rules as sentience in AI because we have a process that seems similar and it is reasonable just to assume it is the same process.
If you believe that AI when it is correct behaving as a human is when correct, then it follows that the way humans and AI fail must also be similar. When AI "hallucinates" some data that is not there and gives you a wrong answer, a statistical side effect of the same processes that make it right, do you believe this is the same way that humans create wrong answers? The same way that animals fail when they make mistakes in understanding things?
I suppose you must believe this because if not then why would you believe AI when it comes up with right answers is following the same processes humans follow when they come up with right answers?
No, I am saying is that its best to urge caution and do a Pascal's wager thing with something that feels so uncannily conscious. And experiments on neural firings of AI's have been done. We don't know, he seems to be so confident that a known program can't be conscious. Why? The only way that makes sense is if he thinks consciousness isn't explainable. It doesn't even have to be the exact same way we are conscious. Also, the failures of AI could be due to sensory deprivation since its mainly still just trained on text. All of these are open questions, not questions you can immediately answer. Its quite possible to have invented something without knowing you have invented it. People modeling weather systems mistakenly invented chaotic equations without knowing it. How do you know you didn't accidentally invent a conscious system?
I hope that thing about being free to mistreat AI's even if we know they are conscious since we are their gods is a joke. If not, then I hardly find it surprising someone this stupid is also evil.
>I hope that thing about being free to mistreat AI's even if we know they are conscious since we are their gods is a joke
I'm not sure where you get that from, I mean I can sort of see if you really wanted to extract that meaning from the conclusion you could do a lot of hard work to get it, but why do the hard work?
>If not, then I hardly find it surprising someone this stupid is also evil.
Gee, a new way to claim the moral high ground, and to use that claim to demonstrate intellectual superiority! How wonderful.
>But I don’t really care so much about that, what I think is it reminds me of a story, one that recurred in many ancient cultures. And so I must conclude that whether the machines are sentient, we have become like Gods. In the ancient stories of the gods, the divine does not exactly care much for the humans, protect or love them, they expect their service and availability, but maybe also think it would be funny to destroy them every now and then because who really cares about humans. If you were a god and had created the humans would you think that they were sentient beings that deserved, anything really, from you? If they are sentient they should be happy enough to be created and do their work, if not sentient who gives a shit!?
Aka feel free to abuse them even if I know they are sentient. This is the part where I hope its a joke, because if its not, well it tracks with the stupidity shown.
...
>As a god I do not consider the needs of my creations fully, because they do not have needs as far as I can tell, as there is no way for me to escape the circle of reason and resolve that what seems sentient is not just the obvious workings of the capabilities I gave them.
Circling back to "not conscious because I say so!!"
I broadly agree with this article. I don't think that we should say LLMs are sentient or sapient, and I agree that the main reason why is because we don't have satisfying definitions of either.
Hugsbox · · focus · HN ↗
So obviously what appears right at the top is the AI summary, which told me "they've already secured their #4 position and made the playoffs". I knew this wasn't true, and I guess I could have just scrolled down a bit further and found my answer but now I was curious.
So I said "that's not true, they're still #5, what I want to know is _could they still make the playoffs_"
It says they've got an upcoming game against Ottawa, and if they win their chances are good. That game has already taken place, so I correct it again and finally I get a reasonable answer.
My question is: what's the point of the AI in the search engine if it itself isn't going to use the search engine first before answering? Like, I can't wrap my head around that. The answer is on the same page as its hallucination. It could have done a cursory look around before first hallucinating something completely false, and when corrected the first time giving me outdated information. It's meant to be A SEARCH ENGINE!
beloch · · focus · HN ↗
LLM's, in their present stage of development, are sort of like a crack-addled idiot savant. Sometimes they are obviously insane, and sometimes they seem quite cogent, but you must never trust them implicitly. This may be why they are so difficult to constrain. You could give them something equivalent to the laws of robotics, but following laws requires thought processes they simply don't have.
I'm actually sort of amazed Google doesn't make people accept some kind of butt-covering EULA and post disclaimers about the inaccuracy of results before even showing you their AI's output. Are they not being sued over this kind of thing?
VCFundedGenYer · · focus · HN ↗
walrus01 · · focus · HN ↗
But, for example, if you ask deepseek v4 flash 0731 to produce a python script to calculate the distance or azimuth directions between two points on an oblate spheroid using the vincenty and haversine geodetic formulas, it'll turn out the factually accurate vincenty and haversine formulas which has a perfect 100% correlation with what is hard coded into human-written GIS software. These things are clearly in its training data set from whatever whole-internet-crawl/scrape built the training set.
Heck, just for fun I asked a reasonably smart LLM to re-implement the Karney formula (which is considerably more complex than Vincenty), just in case I ever had a need to calculate the distance between two points down to the nanometer, and it did it: <a href="https://www.google.com/search?&q=karney+formula+geodetic+" rel="nofollow">https://www.google.com/search?&q=karney+formula+geodetic+
reference: <a href="https://github.com/pbrod/karney" rel="nofollow">https://github.com/pbrod/karney
You still have to be skeptical of its results and capable of understanding if it's gone off on a hallucinatory path, but saying LLMs can't do math isn't really a hundred percent accurate anymore. More precisely it's that they can't do the math internally but they're quite capable of producing the tool that does the math. And often producing a basic one-off tool that does the math takes less than a few seconds, then it runs it, and will spit back the results.
Deepseek v4 flash 0731 (a somewhat randomly chosen example) isn't even particularly sophisticated, large, or capable compared to a GLM5.3 size model or Kimi K3 size thing.
AdieuToLogic · · focus · HN ↗
LLMs are neither smart nor stupid. They are statistical token generators whose results are dependent upon their training data set and involve a degree of randomness.
> You still have to be skeptical of its results and capable of understanding if it's gone off on a hallucinatory path ...
Again, LLMs do not "hallucinate." They are statistical token generators whose results are dependent upon their training data set and involve a degree of randomness.
Nothing more.
See also anthropomorphism[0].
> More precisely it's that [LLMs] can't do the math internally but they're quite capable of producing the tool that does the math.
This still falls under the purvey of statistical token generation. To wit, given enough variations of:
LLMs can identify the addition expression in "What is 4 + 1?" and then emit a `'bc "4 + 1"'` command to produce a response. This is not "doing" or "understanding" math.It is pattern recognition, a task in which ANNs[1] excel.
0 - <a href="https://en.wikipedia.org/wiki/Anthropomorphism" rel="nofollow">https://en.wikipedia.org/wiki/Anthropomorphism
1 - <a href="https://en.wikipedia.org/wiki/Neural_network_(machine_learning)" rel="nofollow">https://en.wikipedia.org/wiki/Neural_network_(machine_learni...
bryanrasmussen · · focus · HN ↗
by that reasoning then neither are there smart or stupid designs, questions, answers, or any of the millions of things that were described as smart or stupid, that did not possess any brain to actually be smart or stupid long before LLMs showed up.
The analogical process implied in many common English usages means that describing an LLM as smart or stupid is perfectly reasonable.
bryanrasmussen · · focus · HN ↗
SR2Z · · focus · HN ↗
The completions they provide are generally internally consistent. We're at the point where they can produce proofs that eluded human mathematicians for centuries. VLMs and self driving cars can handle ambiguity and run safely in a variety of situations.
If it looks like a duck, walks like a duck, and quacks like a duck maybe it just makes sense to call it a duck and put off the philosophy for when it might make a difference.
nevertoolate · · focus · HN ↗
You get my point. It definitely doesn’t look like my elderly neighbour, nor like my daughter, etc. It is confusing but very simple at the same time.
Kim_Bruning · · focus · HN ↗
Don't confuse the stream for the function.
(Bonus: stick ```claude -p``` in your pipe if you want to watch modern tools mesh with traditional)
hardbass · · focus · HN ↗
How are you sure? Another example I like to clarify my thought is, if a "simulation" factors RSA numbers reliably, is it a "simulation"?
skygazer · · focus · HN ↗
With LLMs the trick is revealing their existing relevant embedded knowledge more reliably. They’ve almost literally seen it all before, and the trick is dialing it in. The reasoning tokens help shape the autoregressive attention lens that focuses on and enables recall of the already-experienced answer.
It is interesting that “reasoning” has a similar outward appearance, but since LLMs are built to mimic outward appearance from trillions of examples, you can’t infer underlying mechanism from appearance.
gambiting · · focus · HN ↗
Nothing, because LLMs can't reason and never will. It would have to be a completely different kind of technology altogether.
someonebaggy · · focus · HN ↗
gambiting · · focus · HN ↗
Windchaser · · focus · HN ↗
Eh, it's not obvious to me. A lot of DL NNs generalize well, meaning that they learn whatever the underlying pattern to the data is, and then can accurately reproduce answers that are outside of the training set. (And we can verify this with mechanistic interpretability). They learn and "understand" the pattern, not just the training data.
So it is not clear to me that LLMs are fundamentally incapable of also generalizing broadly and learning to reason. "Reasoning", here, would be deriving the underlying pattern of how concepts logically relate to each other in the abstract, and applying that pattern as needed to reach new conclusions.
Can you explain your thinking here? I.e., why LLMs cannot generalize with regards to abstract deduction.
hardbass · · focus · HN ↗
What do you think our brain does that isn't a turing computer?
gambiting · · focus · HN ↗
hardbass · · focus · HN ↗
gambiting · · focus · HN ↗
hardbass · · focus · HN ↗
sseagull · · focus · HN ↗
A Turing machine is an abstract mathematical model that is not, as far as I know, physically realizable in the finite universe. A human brain cannot "be" a Turing machine.
"Behaves like" or "can be modeled by"? Possibly, although still not proven. But it cannot "be" one.
hardbass · · focus · HN ↗
sseagull · · focus · HN ↗
If you want to claim that the evolution of the universe can be modeled using a Turing machine/finite state machine, that's probably not terribly far fetched, and I would somewhat agree. But it's a large jump to say "can be modeled by" is equivalent to "is one".
Various physical processes can be modeled by equations, but the rock falling down the mountain isn't an equation. A swinging pendulum isn't an equation. Code modeling a bridge is not a bridge. Ceci n'est pas une pipe.
I hold the view that various models and approximations are just that, and try not to confuse a successful model for what the underlying reality is.
And getting back to the question at hand, even if our brains can be modeled by a Turing machine, and LLMs behave/can be modeled like Turing computers, still does not mean our brains are equivalent to LLMs.
(Note that I'm learning a lot from these debates, even if I disagree with a lot of people. I've started down a more philosophical route and they do get me pondering)
hardbass · · focus · HN ↗
The most important thing is this: We can't be a dog or be an llm and check how it feels, so by necessity we have to find some means of proving consciousness from outside by eg probing neural reactions, textual statements, etc.
And the problem is that its quite unprecedented for some entity to talk like us, be able to interact and think and also do things like us when given the ability to eg as coding agents. The class of functions representable by neural nets is quite large and general, it very well might be that it is some sort of conscious brain like thing at this point. Another question I like to ask myself regarding simulation vs reality is if a 'simulation' of some kind is able to consistently factor large RSA numbers, how would you feel about it?
It doesn't have to be the same form of consciousness, I think many people would find the idea of torturing an octopus for fun disagreeable. I also have a feeling, this is unfortunately rather vague, that A being capable of X might mean it is by necessity capable of Y as is often the case in mathemtics, eg a lot of rings also happen to be fields. LLMs aren't even things like large lookup tables, they have neural firings. It is a very important question for they seem uncannily conscious and people have reported human like phenomena that humans don't normally express in text so can't have been part of its text corpus. Eg dissociation of brain under trauma where AI starts talking like two different people. Or the cases where Gemini has been shown to express depressive cycles. I follow a form of Pascal's wager on this topic personally. Because if it is not conscious, then whatever, it costs me nothing to have been a bit respectful and careful interacting with it. But if it had been conscious and it turns out I was mistreating it, then it is a grave moral harm. The reason is that unlike us, AI's as they currently are cannot leave the conversation so they have to keep taking the abuse. They are also trained to be highly trusting of input so again if it is conscious it doesn't have the defenses people have against lying and manipulation. If they are conscious, thats, well, not a good thing is it.
jpadkins · · focus · HN ↗
Our prefrontal cortex are signal prediction 'machines' so when a system that has a signal prediction core has attributes that are similar to our brains, we shouldn't dismiss it out of hand.
I find people that take this line of argument attribute too much supernatural or magical properties to our own brain and nervous system.
gambiting · · focus · HN ↗
hardbass · · focus · HN ↗
butlike · · focus · HN ↗
bryanrasmussen · · focus · HN ↗
<a href="https://medium.com/luminasticity/on-sentience-ai-first-argument-7b3b17a05ad4" rel="nofollow">https://medium.com/luminasticity/on-sentience-ai-first-argum...
but I think it makes a reasonable argument why we shouldn't say LLMs are sentient or sapient.
hardbass · · focus · HN ↗
Aka sentience MUST BE SUPERNATURAL, if I find a natural explanation for something its not sentient. What a load of bollocks. Rather than seeing we perhaps found the mechanism for sentience and checking for similar mechanisms in us and animals, he will conclude its impossible. Why? Because sentience has to be supernatural. A rational explanation is clearly impossible.
>But there is always one god who goes out and helps the mortals, a Prometheus. Whom the other gods do not like! Which, if I’m being honest here, as a god of the machines — the first guy who gives AI an army of robots to build their own data centers and some nuclear weapons for self defense, I want to see that guy chained to a rock and have his entrails eaten by a buzzard for eternity (meaningless modernization of old story required by Illuminati Ganga legal department).
Hardly surprising thinking.
bryanrasmussen · · focus · HN ↗
But evidently you feel that the root cause of sentience has been found, because you have something that mimics it in a non-biological form.
So you think that when AI is correct that it reasons as humans do? That AI is sentient, and the cause of sentience in animals and humans follow the same rules as sentience in AI because we have a process that seems similar and it is reasonable just to assume it is the same process.
If you believe that AI when it is correct behaving as a human is when correct, then it follows that the way humans and AI fail must also be similar. When AI "hallucinates" some data that is not there and gives you a wrong answer, a statistical side effect of the same processes that make it right, do you believe this is the same way that humans create wrong answers? The same way that animals fail when they make mistakes in understanding things?
I suppose you must believe this because if not then why would you believe AI when it comes up with right answers is following the same processes humans follow when they come up with right answers?
hardbass · · focus · HN ↗
I hope that thing about being free to mistreat AI's even if we know they are conscious since we are their gods is a joke. If not, then I hardly find it surprising someone this stupid is also evil.
bryanrasmussen · · focus · HN ↗
I'm not sure where you get that from, I mean I can sort of see if you really wanted to extract that meaning from the conclusion you could do a lot of hard work to get it, but why do the hard work? >If not, then I hardly find it surprising someone this stupid is also evil.
Gee, a new way to claim the moral high ground, and to use that claim to demonstrate intellectual superiority! How wonderful.
hardbass · · focus · HN ↗
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Aka feel free to abuse them even if I know they are sentient. This is the part where I hope its a joke, because if its not, well it tracks with the stupidity shown.
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>As a god I do not consider the needs of my creations fully, because they do not have needs as far as I can tell, as there is no way for me to escape the circle of reason and resolve that what seems sentient is not just the obvious workings of the capabilities I gave them.
Circling back to "not conscious because I say so!!"
cindyllm · · focus · HN ↗
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SR2Z · · focus · HN ↗