Fundamentally these shortcomings cannot be addressed.
They can and are improved (papered over) over time. For example by improving and tweaking the training data. Adding in new data sets is the usual fix. A prime example 'count the number of R's in Strawberry' caused quite a debacle at a time where LLM's were meant to be intelligent. Because they aren't they can trip up over simple problems like this. Continue to use an army of people to train them and these edge cases may become smaller over time. Fundamentally the LLM tech hasn't changed.
I am not saying that LLM's aren't amazing, they absolutely are. But WHAT they are is an understood thing so lets not confuse ourselves.
I don't understand why this point is NOT getting across to so many on HN.
LLM's do not think, understand, reason, reflect, comprehend and they never shall.
I have commented elsewhere but this bears repeating
If you had enough paper and ink and the patience to go through it, you could take all the training data and manually step through and train the same model. Then once you have trained the model you could use even more pen and paper to step through the correct prompts to arrive at the answer. All of this would be a completely mechanical process. This really does bear thinking about. It's amazing the results that LLM's are able to acheive. But let's not kid ourselves and start throwing about terms like AGI or emergence just yet. It makes a mechanical process seem magical (as do computers in general).
I should add it also makes sense as to why it would, just look at the volume of human knowledge (the training data). It's the training data with the mass quite literally of mankind's knowledge, genius, logic, inferences, language and intellect that does the heavy lifting.
> If you had enough paper and ink and the patience to go through it, you could take all the training data and manually step through and train the same model.
But you could make the exact same argument for a human mind? (could just simulate all those neural interactions with pen and paper)
The only way to get out of it is to basically admit magic (or some other metaphysical construct with a different name).
We do know that they are different, and that there are some systematic shortcomings in LLMs for now (e.g. no mechanism for online learning).
But we have no idea how many "essential" differences there are (if any!).
Dismissing LLMs as avenues toward intelligence just because they are simpler and easier to understand than our minds is a bit like looking at a modern phone from a 19th century point of view and dismissing the notion that it could be "just a Turing machine": Sure, the phone is infinitely more complex, but at its core those things are the same regardless.
I'm not so sure "a human mind" is the kind of newtonian clockwork thingiemabob you "could just simulate" within the same degree of complexity as the thing you're simulating, at least not without some sacrifices.
Can you give examples of how that "LLM's do not think, understand, reason, reflect, comprehend and they never shall" or that "completely mechanical process" helps you understand better when LLM works and when they don't?
Many people are throwing around that they don't "think", that they aren't "conscious", that they don't "reason", but I don't see those people sharing interesting heuristics to use LLMs well. The "they don't reason" people tend to, in my opinion/experience, underestimate them by a lot, often claiming that they will never be able to do <thing that LLMs have been able to do for a year>.
To be fair, the "they reason/are conscious" people tend to, in my opinion/experience, overestimate how much a LLM being able to "act" a certain way in a certain situation says about the LLM/LLMs as a whole ("act" is not a perfect word here, another way of looking at it is that they visit only the coast of a country and conclude that the whole country must be sailors and have a sailing culture).
It's an algorithm and a completely mechanical process which you can quite literally copy time and time again. Unless of course you think 'physical' computers have magical powers that a pen and paper Turing machine doesn't?
> Many people are throwing around that they don't "think", that they aren't "conscious", that they don't "reason", but I don't see those people sharing interesting heuristics to use LLMs well.
My digital thermometer doesn't think. Imbibing LLM's with thought will start leading to some absurd conclusions.
A cursory read of basic philosophy would help elucidate why casually saying LLM's think, reason etc is not good enough.
What is thinking? What is intelligence? What is consciousness? These questions are difficult to answer. There is NO clear definition. Some things are so hard to define (and people have tried for centuries) e.g. what is consciousness? That they are a problem set within themselves please see Hard problem of consciousness.
>My digital thermometer doesn't think. Imbibing LLM's with thought will start leading to some absurd conclusions.
What kind of absurd conclusions? And what kind of non absurd conclusions can you make when you follow your let's call it "mechanistic" view?
>It's an algorithm and a completely mechanical process which you can quite literally copy time and time again. Unless of course you think 'physical' computers have magical powers that a pen and paper Turing machine doesn't?
I don't, just like I don't think a human or animal brain has any magical power that imbues it with "intelligence" and "reasoning".
>A cursory read of basic philosophy would help elucidate why casually saying LLM's think, reason etc is not good enough.
I'm not saying they do or they don't, I'm saying that from what I've seen having a strong opinion about whether they think or they don't seem to lead people to weird places.
>What is thinking? What is intelligence? What is consciousness? These questions are difficult to answer. There is NO clear definition.
You see pretty certain that whatever those three things are a LLM isn't doing it, a paper and pencil aren't doing it even when manipulated by a human, the system of a human manipulating a paper and pencil isn't doing it.
LLM's have surpassed being Turing machines? Turing machines now think?
LLM's are known properties in that they are an algorithm! Humans are not. PLEASE at the very least grant that the jury is STILL out on what humans actually are in terms of their intelligence, that is after all what neuroscience is still figuring out.
> Am I supposed to want to code all the time? When can I pursue hobbies, a social life, etc.
I feel you. It's a societal question you're posing. Your employer (most employers) deal in dollars. A business is evaluated by its ability to generate revenue. That is the purpose of a business and the fiduciary duty of the CEO's in charge.
I tend to agree with your assessment. The increase in demand cannot possibly equal the loss from AI.
Given projections of AI abilities over time AI necessarily creates downward pressure on new job creation. AI is for reducing and/or eliminating jobs (by way of increasing efficiency).
AI isn't creating 'new' things, it's reducing the time needed to do what was already being done. Unlike the automobile revolution new job categories aren't being created with AI.
Lots of users seem to think LLM's think and reason so this sounds wonderful. A mechanical process isn't thinking, certainly it does NOT mirror human thinking. The processes being altogether different.
Humans are probabilistic systems?! You might want to inform the world's top neuroscientists and philosophers to down tools. They were STILL trying to figure this out but you've already solved it! Well done.
I don't think it's a naive response. Perhaps it's obvious to you that human doctors can't produce an "exact correct solution", but quite a lot of people do expect this, and get frustrated when a doctor can't tell them exactly what's wrong with them or recommends a treatment that doesn't end up working.
There's nothing naive about it. Most doctors work off of statistics and probabilities stemming from population based studies. Literally the entire field of medicine is probabilistic and that's what angers people. Yes, 95% chance you're not suffering from something horrible but a lot of people would want to continue diagnostics to rule out that 5% that you now have cancer and the doctor sent you home with antibiotics thinking it's just some infection, or whatever.
They can and are improved (papered over) over time. For example by improving and tweaking the training data. Adding in new data sets is the usual fix. A prime example 'count the number of R's in Strawberry' caused quite a debacle at a time where LLM's were meant to be intelligent. Because they aren't they can trip up over simple problems like this. Continue to use an army of people to train them and these edge cases may become smaller over time. Fundamentally the LLM tech hasn't changed.
I am not saying that LLM's aren't amazing, they absolutely are. But WHAT they are is an understood thing so lets not confuse ourselves.
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