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Why AI is still dumb and not scary at all (pt. 1)

63 点作者 tejonutella2 个月前

23 条评论

haswell2 个月前
This is a frustrating piece on many levels, but mostly because it doesn&#x27;t really scratch the surface of what is worrisome about AI. It sets up straw men and knocks them down, but not much else.<p>It seems to boil down to:<p>1. LLMs aren&#x27;t actually <i>&quot;learning&quot;</i> the way humans do so we shouldn&#x27;t be worried<p>2. LLMs don&#x27;t actually <i>&quot;understand&quot;</i> anything so we shouldn&#x27;t be worried<p>3. Technology has always been advancing and we&#x27;ve always been freaking out about that, so we shouldn&#x27;t be worried<p>4. If your job is automate-able, it probably <i>should</i> be eliminated anyway<p>What&#x27;s scary is not that these models are smarter than us, but that we are dumb enough to deploy them in critical contexts and trust the output they generate.<p>What&#x27;s scary isn&#x27;t that these models are so good they&#x27;ll replace us, but that despite how limited they are, someone will make the decision to replace humans anyway.<p>What&#x27;s scary isn&#x27;t that LLMs will displace good developers, but that LLMs put the power of development in the hands of people who have no idea what they&#x27;re wielding.<p>&gt; <i>Sure, with a millions upon millions of training examples, of course you can mimic intelligence. If you already know what’s going to be on the test, common patterns for answers in the test, or even the answer key itself, then are you really intelligent? OR are you just regurgitating information from billions of past tests?</i><p>How different are humans from this description in actuality? What are we if not the results of a process that has been optimized by millions upon millions of iterations over long periods of time?
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ed-2092 个月前
A gun is not smart or magical but is nevertheless a powerful tool that can be scary depending on who is holding it. Accordingly, I worry less about my occupation and more about the moral character of those wielding it. Further i worry about &quot;smart&quot; people who have not been acquainted with the dark side of human nature facilitating bad actors.
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magic_hamster2 个月前
This seems to just ignore what&#x27;s going on in the world. Some parts of the software development domain are definitely being affected by AI. I see a particular shift in web development and possibly embedded systems firmware development (or any other field where there is an exact specification of what you&#x27;re supposed to deliver).<p>LLMs don&#x27;t need to be AGI. There&#x27;s a race to adjust testing, architecture and infrastructure to fit AI agents who could possibly change them as needed. Some tools are already pretty good and they will only get better.<p>Long story short, we are definitely going to see massive shift in jobs in the coming years.
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ohgr2 个月前
Dumb stuff is what I want. Classifiers and denoise are really useful.<p>What I don’t want is a shitty chat bot that barely understands what you ask it and generates shitty code by sticking a corpus of shitty code together then leaving me with the unconstrained job of working out if it has any land mines in it. Then multiply that by 50 engineers. Then tell me that’s the future. Because if it is we are totally fucked. Our decline will be noted by the general decline in capacity to do anything.
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ttul2 个月前
Ugh, I really dislike this sort of hand-waving blog post. The author cobbles together an argument dispelling all concerns about AI proliferation by assembling a few Tweets. Don’t mistake this for scholarship. I believe the true answer to the question of whether we should be frightened of these gigantic models is far more nuanced and way less certain.<p>A more honest blog post would read something like this: Big Ai models are interesting and useful. And there’s the potential for danger. We should be cautious and make sure we have some bright scholars studying what might happen if various scenarios play out. Just as we would want to be in response to any similarly massive advancement in technology.
EigenLord2 个月前
&gt;There is no real thinking involved. It’s just math<p>&gt;Implying<p>I&#x27;ll never understand this &quot;They&#x27;re just learning from past experience and making predictions!&quot; argument, as if that doesn&#x27;t constitute thinking in some meaningful, if minimal sense. What I&#x27;m more annoyed about is that for laypeople AI is synonymous with transformers. The fields of AI and machine learning are much vaster, with a rich intellectual history spanning many decades. Blanket statements don&#x27;t apply.
jmyeet2 个月前
The problem is how AI is and will be used and how unaccountable it is.<p>An Ai scans job applicants. Is it biased? Is it conforming with legal requirements? A person&#x27;s bias can be an issue in a lawsuit. AIs are a much more difficult target, at least for now. This is why companies like them.<p>You know what the impact will be? More scandals like Hertz falsely reporting people to the police for stealing cars [1].<p>AI will make financial and lending decisions that could easily become redlining 2.0.<p>Companies are so desperate to eliminate labor. People have rights. They need to be paid. They can strike.<p>If the AI purveyors fulfil their dream, companies will be automated but nobody will have any money because nobody has any jobs anymore.<p>[1]: <a href="https:&#x2F;&#x2F;www.npr.org&#x2F;2022&#x2F;12&#x2F;06&#x2F;1140998674&#x2F;hertz-false-accusation-stealing-cars-settlement" rel="nofollow">https:&#x2F;&#x2F;www.npr.org&#x2F;2022&#x2F;12&#x2F;06&#x2F;1140998674&#x2F;hertz-false-accusa...</a>
ninetyninenine2 个月前
&gt;Humans don&#x27;t need to learn from 1 trillion words to reach human intelligence. What are LLMs missing?<p>A Yann Lecuun quote from the page.<p>LLMs are blank slates. Humans have millions of years of pretraining recorded in the neural network not as weights but as the structure of the neural network itself. Our physical bodies are biased towards living in an oxygen environment with light and ground and our brains are biased in that same direction.<p>If you put humans in a completely different context. Like utterly completely brand new context say like 50 dimensional space where all our sense become useless and logic and common sense is completely overridden with new rules...<p>the Human will perform WORSE then the LLM when trained on the same text.
seydor2 个月前
Crap article with zero insight that wasn&#x27;t worth my time.<p>There are better ways to argue the same position but it&#x27;s probably indefensible.<p>Neural networks are fundamentally approximators, both when they are approximating long-range relations between concepts (like LLMs do) or when they denoise some noise for images. They approximate thought and intelligence, because we have coded it in our writings. Our writings are a complete fingerprint of the thought process, because we are able to pick up any thought process from a book, without ever seeing or otherwise having contact with the author. Therefore there is an increasingly more high-fidelity &quot;real thought&quot; in there.<p>&gt; that in and of itself is a monumental achievement but there is no real thought involved.<p>Pretty much anything that requires our current level of thought is therefore reachable with ANNs now that we know how to train them in depth and width.<p>The real question is whether this is enough. We want ASI, but our texts only have AGI, and everything that comes from biology (including intelligence) is logarithmic in scale. There is zero evidence that language models will ever learn to create abstract entities better than any collection of humans do. AI companies are advertising armies of PhD students, but we already have millions of PhD students , yet our most pressing problems have not made a lot of progress for decades. That&#x27;s what should be worrying to us, not the fact that we will all lose our jobs.
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Herring2 个月前
I’m pretty sure you couldn’t trust me to multiply 20-digit numbers either.
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pshirshov2 个月前
&gt; not scary<p>LLMs are not scary. The people trying to apply them to critical domains are.
jxjnskkzxxhx2 个月前
Anyone else thinks that the argument &quot;it doesnt really think, it&#x27;s just math&quot; is incredibly superficial?
cirrus32 个月前
&gt; Hot take: if your job can be partially or wholly eliminated by AI, that’s a GOOD THING. If your job has patterns that predictable or labor that routine, AI automation is a GOOD THING.<p>The article never says why this is good. It just states it then moves on.<p>&gt; As a whole, I’m sure it’ll give birth to entirely new systems we haven’t even conceived of yet and, one can hope, free up that time and energy towards more meaningful or creative pursuits.<p>The people&#x27;s who job it takes probably don&#x27;t give af about the patterns of their job, or creative pursuits they can do while unemployed. They are probably just trying to pay their bills and feed their kids.
metalman2 个月前
there is scary, as in physicaly dangerous and then there is scarry, as in I cant stand looking at media any more, scary and scary as in my job is threatened or the price fixing scams have unhomed you or the app that provided my job leads, has been super optimised, and is no longer viable and scary as , all of the above can be ignored , defended, as the app &quot;just did it defence&quot; with no one liable for the abuses, scary
r0ckarong2 个月前
The scariest thing about innovation is the inability of a human mob to distinguish between lateral movement and intent.
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esafak2 个月前
This is a shallow and dated article, even when it came out in 2023. LLMs are dumb because they can&#x27;t multiply, and generalize? They can easily write programs and calculate anything you want, and machine learning is all about generalizing.<p><pre><code> Hot take: if your job can be partially or wholly eliminated by AI, that’s a GOOD THING. If your job has patterns that predictable or labor that routine, AI automation is a GOOD THING. </code></pre> What if it lead to widespread under- or unemployment? This social upheaval would lead to people setting aside the niceties of civilization as they fight to meet their basic needs. And such people elect bad governments, which exacerbates the problem.<p>One might also be scared in a physical sense. The race is afoot to develop physical robots on par with humans. Imagine that as your policeman, or soldier, bringing democracy to a country near you.<p><a href="https:&#x2F;&#x2F;www.yahoo.com&#x2F;tech&#x2F;china-tech-contest-features-robotics-093000363.html" rel="nofollow">https:&#x2F;&#x2F;www.yahoo.com&#x2F;tech&#x2F;china-tech-contest-features-robot...</a>
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justlikereddit2 个月前
&gt;AI does not really think, it just seems like it does.<p>Neither does humans.<p>Sorry to disappoint the super-AGI hopeful: we&#x27;re already past that point, because the average human is only a 3B parameter LLM there&#x27;s nothing magic that comes with an AGI.<p>The first time GPT2 autocompleted a sentence involving admitting a previous fault of output we were in the post-human era.<p>Everything we&#x27;ve seen since then have been us living through the legendary post-AGI AI bootstraps launch, but living the future isn&#x27;t exactly living up to the hype huh?<p>That GTP-4.5 model that had the Samaltmanists wriggle on the floor in rapturous ecstatic orgasms just last year? Today it&#x27;s an embarrassment, like the seed-stained lesswrong posters of yore.<p>The singularity was a star trek plot device.<p>What we see today is the real deal and I re-iterate my 2015 predictions: by the time an actually scary god like AI is created(say in 2050). We&#x27;ll have so many thousands or millions of demi-god AI around that the god itself will have to have the good graces to shut up, get a queue ticket in the bare-metal immigration zone with the rest of the rabble. The prospect of true AI divinity will be a (hype-burned) washed out gray with a trace sprinkle of glitter on the already existing background of demi-divine AI.
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robwwilliams2 个月前
Interesting piece but I am much more optimistic.<p>Tejo writes:<p>&gt; At the heart of it, all AI is just a pattern recognition engine. They’re simply algorithms designed to maximize or minimize an objective function. There is no real thinking involved. It’s just math. If you think somewhere in all that probability theory and linear algebra, there is a soul, I think you should reassess how you define sentience.”<p>We have two words we need to define: “sentience” and “thinking”.<p>Sentience can be defined as a basic function of most living systems (viruses excluded). You may disagree but to me this word connotes “actively responsive to perturbations”. This is part of the auopoietic definition of life introduced by Maturana and Valera in the 1970s and 1980s. If you buy this definition then “sentience” is a low bar and not what we mean by AI, let alone by AGI.<p>The word “thinking” implies more than just consciousness. Many of us accept that cats, dogs, pigs, chimps, crows, parrots, and whales are conscious. Perhaps not an ant or a spider, but yes, probably rats since rats play and smile and clearly plan. But few of us would be likely to claim that a rat thinks in a way that we think. Sure, a rat analyzes its environment and comes to decisions about best actions, but that does not require what many of us mean by thinking.<p>We usually think of thinking as a process of reflection&#x2F;recursion&#x2F;self-evaluation of alternative scenarios. The key word here is recursion. and that gets us to “self-consciousness”—a word that embeds recursion.<p>I operationally define thinking as a process that involves recursive review and reflection&#x2F;evaluation of alternatives with the final selection of an “action”—either a physical action or an action that is a “thought conclusion”.<p>What AI&#x2F;LMM transformers do not have is deep enough recursion or access to memory of preceding states. They cannot remember and they do not have a meta-supervisor that lets them modulate their own attentional state. So I would agree that they are still incapable of what most if us call thinking.<p>But how hard is adding memory access to any number of current generation AI systems?<p>How hard us it to add recursion and chain-of-thought?<p>How hard will it be to enable an AI system to attend to its own attention?<p>In my optimistic view these are all close to solved problems.<p>In my opinion the only thing separating us from true AGI are a few crucial innovations in AI architecture—-mainly self-control of attention—-and under 100k lines of code.<p>Please argue! (I’ve had many arguments with Claude on this topic).
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dgfitz2 个月前
AI doesn’t exist. large language models are what they are, language models.
bmitc2 个月前
AI is more scary because it is so dumb.
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dgfitz2 个月前
*why llm models will always be dumb
chrismcb2 个月前
Because it isn&#x27;t AI.
borisk2 个月前
&quot;Change is inevitable. You can’t stop the railroad as they used to say. It’s going to kill some jobs but not all of them.&quot;<p>I personally don&#x27;t worry about jobs. AI is progressing very fast (there are a lof of smart folks working on it, there are a ton of money invested and there&#x27;s a lot of demand from businesses, governments and individuals). Human inteligence stays the same. I think it&#x27;s likely that sometime soon AI models will become more inteligent than an average human. And then more inteligent than the smartest human. And then more inteligent than the whole human race combined.<p>Let&#x27;s say some worms 600 million years ago could think. And they consider should they kill all mutants and stay forever the pinnacle of evolution as they are or allow some of them to evolve into fish, and then mammals and eventually inteligent humans. I think we are in a position like this - we are currently the pinacle of &quot;creation&quot; in the known universe - do we want to stay this way - by blocking AGI progress, or do we want to allow minds far greater than us to evolve from current LLMs at the cost of probable human extinction eventually.