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We need to stop pretending AI is intelligent

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  • I think the self driving is likely to be safer in the most boring scenarios, the sort of situations where a human driver can get complacent because things have been going so well for the past hour of freeway driving. The self driving is kind of dumb, but it's at least consistently paying attention, and literally has eyes in the back of it's head.

    However, there's so much data about how it fails in stupidly obvious ways that it shouldn't, so you still need the human attention to cover the more anomalous scenarios that foul self driving.

    Anomalous scenarios like a giant flashing school bus? 😄

  • I'm summarizing your shitty argument and viewpoint. I never said it was a direct quote.

    Though, at one point even that tired ass quote and your whole way of thinking was put into words by someone for the first time.

    Well you are doing a poor job of it and are bringing an unnecessary amount of heat to an otherwise civil discussion

  • Anomalous scenarios like a giant flashing school bus? 😄

    Yes, as common as that is, in the scheme of driving it is relatively anomolous.

    By hours in car, most of the time is spent on a freeway driving between two lines either at cruising speed or in a traffic jam. The most mind numbing things for a human, pretty comfortably in the wheel house of driving.

    Once you are dealing with pedestrians, signs, intersections, etc, all those despite 'common' are anomolous enough to be dramatically more tricky for these systems.

  • Well you are doing a poor job of it and are bringing an unnecessary amount of heat to an otherwise civil discussion

    That's right. If you cannot win the argument the next best thing is to call for civility.

  • 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.

    Your brain is running on sugar. Do you take into account the energy spent in coal mining, oil fields exploration, refinery, transportation, electricity transmission loss when computing the amount of energy required to build and run AI? Do you take into account all the energy consumption for the knowledge production in first place to train your model?
    Running the brain alone is much less energy intensive than running an AI model. And the brain can create actual new content/knowledge. There is nothing like the brain. AI excel at processing large amount of data, which the brain is not made for.

  • At least in my car, the lane following (not keeping system) is handy because the steering wheel naturally tends to go where it should and less often am I "fighting" the tendency to center. The keeping system is at least for me largely nothing. If I turn signal, it ignores me crossing a lane. If circumstances demand an evasive maneuver that crosses a line, it's resistance isn't enough to cause an issue. At least mine has fared surprisingly well in areas where the lane markings are all kind of jacked up due to temporary changes for construction. If it is off, then my arms are just having to generally assert more effort to be in the same place I was going to be with the system. Generally no passenger notices when the system engages/disengages in the car except for the chiming it does when it switches over to unaided operation.

    So at least my experience has been a positive one, but it hits things just right with intervention versus human attention, including monitoring gaze to make sure I am looking where I should. However there are people who test "how long can I keep my hands off the steering wheel", which is a more dangerous mode of thinking.

    And yes, having cameras everywhere makes fine maneuvering so much nicer, even with the limited visualization possible in the synthesized 'overhead' view of your car.

    The rental cars I have driven with lane keeper functions have all been too aggressive / easily fooled by visual anomalies on the road for me to feel like I'm getting any help. My wife comments on how jerky the car is driving when we have those systems. I don't feel like it's dangerous, and if I were falling asleep or something it could be helpful, but in 40+ years of driving I've had "falling asleep at the wheel" problems maybe 3 times - not something I need constant help for.

  • i dont have anything else going on, man

    There's that... though even when you're bored, you still sleep sometimes.

  • And they made the programs you seem to trust so much.

    Ya... Humans so far have made everything not produced by Nature on Earth. 🤷

  • Anyone pretending AI has intelligence is a fucking idiot.

    Caveat: Anyone who has been scrutinising 'AI'.

    Something i often forget is the vast majority of the population doesnt care about technology, privacy, the mechanics of LLMs as much as i do and I pay attention to.
    So most people read/hear/watch stories of how great it is and how clever AI can do simple things for them so its easy to see how they think its doing a lot more 'thought' logic work than it really is, other than realistically it being a glorified word predictor.

  • No, thats the point of the article. You also haven't really said much at all.

    Do I have to be profound when I make a comment that is taking more of a dig at my fellow space rock companions than at AI itself?

    If I do, then I feel like the author of the article either has as much faith in humanity as I do, or is as simple as I was alluding to in my original comment. The fact that they need to dehumanise the AI's responses makes me think they’re forgetting it’s something we built. AI isn’t actually intelligent, and it worries me how many people treat it like it is—enough to write an article like this about it. It’s just a tool, maybe even a form of entertainment. Thinking of it as something with a mind or personality—even if the developers tried to make it seem that way—is kind of unsettling.

    Let me know if you would like me to write thiis more formal, casual, or persuasive. 😜

  • If you can formulate that sentence, you can handle "it's means it is". Come on. Or "common" if you prefer.

    Yeah, man, I get it. Language is complex. I'm not advocating for the reinvention of English, it was just a conversational observation about a silly quirk.

  • Do I have to be profound when I make a comment that is taking more of a dig at my fellow space rock companions than at AI itself?

    If I do, then I feel like the author of the article either has as much faith in humanity as I do, or is as simple as I was alluding to in my original comment. The fact that they need to dehumanise the AI's responses makes me think they’re forgetting it’s something we built. AI isn’t actually intelligent, and it worries me how many people treat it like it is—enough to write an article like this about it. It’s just a tool, maybe even a form of entertainment. Thinking of it as something with a mind or personality—even if the developers tried to make it seem that way—is kind of unsettling.

    Let me know if you would like me to write thiis more formal, casual, or persuasive. 😜

    I meant that you are arguing semantics rather than substance. But other than that I have no issue with what you wrote or how you wrote it, its not an unbelievable opinion.

  • 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.

  • 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.

    1. Y = 3, X = 1
    2. Y = 4, X = 2
    3. 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.

  • 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.

    1. Y = 3, X = 1
    2. Y = 4, X = 2
    3. 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.

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    So they're doing good work at least.
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    It doesn't seem to be the case. As far as I can tell, the law only covers realistic digital imitations of a person's likeness (deepfakes), with an exception for parody and satire. If you appear in public that is effectively license for someone to capture your image.
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    They've probably just crunched the numbers and determined the cost of a recall in Canada was greater than the cost of law suits when your house does burn down
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    You guys sure display a crazy obsession with "Apple Fanboys" in this sub… The amount of Applephobia… Phew! As if the new release had you all flustered or something… Gotta take a bite and taste the Apple at some point! Can’t stay in the closet forever, ya know?
  • Ispace of Japan’s Moon Lander Resilience Has Crashed

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    $ ls space?
  • Companies are using Ribbon AI, an AI interviewer to screen candidates.

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    I feel like I could succeed in an LLM selection process. I could sell my skills to a robot, could get an LLM to help. It's a long way ahead of keyword based automatic selectors At least an LLM is predictable, human judges are so variable
  • Why doesn't Nvidia have more competition?

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    It’s funny how the article asks the question, but completely fails to answer it. About 15 years ago, Nvidia discovered there was a demand for compute in datacenters that could be met with powerful GPU’s, and they were quick to respond to it, and they had the resources to focus on it strongly, because of their huge success and high profitability in the GPU market. AMD also saw the market, and wanted to pursue it, but just over a decade ago where it began to clearly show the high potential for profitability, AMD was near bankrupt, and was very hard pressed to finance developments on GPU and compute in datacenters. AMD really tried the best they could, and was moderately successful from a technology perspective, but Nvidia already had a head start, and the proprietary development system CUDA was already an established standard that was very hard to penetrate. Intel simply fumbled the ball from start to finish. After a decade of trying to push ARM down from having the mobile crown by far, investing billions or actually the equivalent of ARM’s total revenue. They never managed to catch up to ARM despite they had the better production process at the time. This was the main focus of Intel, and Intel believed that GPU would never be more than a niche product. So when intel tried to compete on compute for datacenters, they tried to do it with X86 chips, One of their most bold efforts was to build a monstrosity of a cluster of Celeron chips, which of course performed laughably bad compared to Nvidia! Because as it turns out, the way forward at least for now, is indeed the massively parralel compute capability of a GPU, which Nvidia has refined for decades, only with (inferior) competition from AMD. But despite the lack of competition, Nvidia did not slow down, in fact with increased profits, they only grew bolder in their efforts. Making it even harder to catch up. Now AMD has had more money to compete for a while, and they do have some decent compute units, but Nvidia remains ahead and the CUDA problem is still there, so for AMD to really compete with Nvidia, they have to be better to attract customers. That’s a very tall order against Nvidia that simply seems to never stop progressing. So the only other option for AMD is to sell a bit cheaper. Which I suppose they have to. AMD and Intel were the obvious competitors, everybody else is coming from even further behind. But if I had to make a bet, it would be on Huawei. Huawei has some crazy good developers, and Trump is basically forcing them to figure it out themselves, because he is blocking Huawei and China in general from using both AMD and Nvidia AI chips. And the chips will probably be made by Chinese SMIC, because they are also prevented from using advanced production in the west, most notably TSMC. China will prevail, because it’s become a national project, of both prestige and necessity, and they have a massive talent mass and resources, so nothing can stop it now. IMO USA would clearly have been better off allowing China to use American chips. Now China will soon compete directly on both production and design too.
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    Where and what is texas?