I think AI is neat.
I think LLMs are neat, and Teslas are neat, and HHO generators are neat, and aliens are neat…
…but none of them live up to all of the claims made about them.
HHO generators
…What are these? Something to do with hydrogen? Despite it not making sense for you to write it that way if you meant H2O, I really enjoy the silly idea of a water generator (as in, making water, not running off water).
HHO generators are a car mod that some backyard scientists got into, but didn’t actually work. They involve cracking hydrogen from water, and making explosive gasses some claimed could make your car run faster. There’s lots of YouTube videos of people playing around with them. Kinda dangerous seeming… Still neat.
Thanks! I hadn’t heard of this before, hydrogen fueled cars, sure, but not this. 😄
Knowing that LLMs are just “parroting” is one of the first steps to implementing them in safe, effective ways where they can actually provide value.
LLMs definitely provide value its just debatable whether they’re real AI or not. I believe they’re going to be shoved in a round hole regardless.
I think a better way to view it is that it’s a search engine that works on the word level of granularity. When library indexing systems were invented they allowed us to look up knowledge at the book level. Search engines allowed look ups at the document level. LLMs allow lookups at the word level, meaning all previously transcribed human knowledge can be synthesized into a response. That’s huge, and where it becomes extra huge is that it can also pull on programming knowledge allowing it to meta program and perform complex tasks accurately. You can also hook them up with external APIs so they can do more tasks. What we have is basically a program that can write itself based on the entire corpus of human knowledge, and that will have a tremendous impact.
I feel like our current “AIs” are like the Virtual Intelligences in Mass Effect. They can perform some tasks and hold a conversation, but they aren’t actually “aware”. We’re still far off from a true AI like the Geth or EDI.
I wish there was a term without “Intelligence” in it because LLMs aren’t intelligent.
“AI” is always reserved for the latest tech in this space, the previous gens are called what they are. LMMs will be what these are called after a new iteration is out.
I wish we called them VI’s. It was a good distinction in their ability.
Though honestly I think our AI is more advanced in conversation than a VI in ME.
This was the first thing that came to my mind as well and VI is such an apt term too. But since we live in the shittiest timeline Electronic Arts would probably have taken the Blizzard/Nintendo route too and patented the term.
If an LLM is just regurgitating information in a learned pattern and therefore it isn’t real intelligence, I have really bad news for ~80% of people.
You’ve just described most people…
P-Zombies, all of them. I happen to be the only one to actually exist. What are the odds, right? But it’s true.
It figures you’d say it, it’s probably your algorithm trying to mess up with my mind!
Ok, but so do most humans? So few people actually have true understanding in topics. They parrot the parroting that they have been told throughout their lives. This only gets worse as you move into more technical topics. Ask someone why it is cold in winter and you will be lucky if they say it is because the days are shorter than in summer. That is the most rudimentary “correct” way to answer that question and it is still an incorrect parroting of something they have been told.
Ask yourself, what do you actually understand? How many topics could you be asked “why?” on repeatedly and actually be able to answer more than 4 or 5 times. I know I have a few. I also know what I am not able to do that with.
I don’t think actual parroting is the problem. The problem is they don’t understand a word outside of how it is organized. They can’t be told to do simple logic because they don’t have a simple understanding of each word in their vocabulary. They can only reorganize things to varying degrees.
It doesn’t need to understand the words to perform logic because the logic was already performed by humans who encoded their knowledge into words. It’s not reasoning, but the reasoning was already done by humans. It’s not perfect of course since it’s still based on probability, but the fact that it can pull the correct sequence of words to exhibit logic is incredibly powerful. The main hard part of working with LLMs is that they break randomly, so harnessing their power will be a matter of programming in multiple levels of safe guards.
Few people truly understand what understanding means at all, i got teacher in college that seriously thinked that you should not understand content of lessons but simply remember it to the letter
I am so glad I had one that was the opposite. I discussed practical applications of the subject material after class with him and at the end of the semester he gave me a B+ even though I only got a C by score because I actually grasped the material better than anyone else in the class, even if I was not able to evaluate it as well on the tests.
I’m glad for you) out teacher liked to offer discussion only to shoot us down when we tried to understand something, i was like duh that’s what teachers are for, to help us understand, if teachers don’t do that, then it’s the same as watching YouTube lectures
This is only one type of intelligence and LLMs are already better at humans at regurgitating facts. But I think people really underestimate how smart the average human is. We are incredible problem solvers, and AI can’t even match us in something as simple as driving a car.
Lol @ driving a car being simple. That is one of the more complex sensory somatic tasks that humans do. You have to calculate the rate of all vehicles in front of you, assess for collision probabilities, monitor for non-vehicle obstructions (like people, animals, etc.), adjust the accelerator to maintain your own velocity while terrain changes, be alert to any functional changes in your vehicle and be ready to adapt to them, maintain a running inventory of laws which apply to you at the given time and be sure to follow them. Hell, that is not even an exhaustive list for a sunny day under the best conditions. Driving is fucking complicated. We have all just formed strong and deeply connected pathways in our somatosensory and motor cortexes to automate most of the tasks. You might say it is a very well-trained neural network with hundreds to thousands of hours spent refining and perfecting the responses.
The issue that AI has right now is that we are only running 1 to 3 sub-AIs to optimize and calculate results. Once that number goes up, they will be capable of a lot more. For instance: one AI for finding similarities, one for categorizing them, one for mapping them into a use case hierarchy to determine when certain use cases apply, one to analyze structure, one to apply human kineodynamics to the structure and a final one to analyze for effectiveness of the kineodynamic use cases when done by a human. This would be a structure that could be presented an object and told that humans use it and the AI brain could be able to piece together possible uses for the tool and describe them back to the presenter with instructions on how to do so.
AI can beat me in driving a car, and I have a degree.
Jokes on them. I don’t even calculate when I need to parrot. I am beyond such lowly needs.
As someone who has loves Asimov and read nearly all of his work.
I absolutely bloody hate calling LLM’s AI, without a doubt they are neat. But they are absolutely nothing in the ballpark of AI, and that’s okay! They weren’t trying to make a synethic brain, it’s just the culture narrative I am most annoyed at.
I look at all these kids glued to their phones and I ask 'Where’s the Frankenstein Complex now that we really need it?"
Keep seething, OpenAI’s LLMs will never achieve AGI that will replace people
That was never the goal… You might as well say that a bowling ball will never be effectively used to play golf.
Buddy, nobody ever said it would
Keep seething
Keep projecting
Next you’ll tell me that the enemies that I face in video games arent real AI either!
I said AGI deliberately…
I fully back your sentiment OP; you understand as much about the world as any LLM out there and don’t let anyone suggest otherwise.
Signed, a “contrarian”.
I once ran an LLM locally using Kobold AI. Said thing has an option to show the alternative tokens for each token it puts out, and what their probably for being chosen was. Seeing this shattered the illusion that these things are really intelligent for me. There’s at least one more thing we need to figure out before we can build an AI that is actually intelligent.
It’s cool what statistics can do, though.
That’s actually pretty neat. I tried Kobold AI a few months ago but the novelty wore off quickly. You made me curious, I’m going to check out that option once I get home. Is it just a toggleable opyiont option or do you have to mess with some hidden settings?
Just as I was about to give up, it somehow worked: https://imgchest.com/p/9p4ne9m9m4n I didn’t really do anything different this time around, so no idea why it didn’t work at first.
It’s been about a year since I saw the probabilities. I took another look at it just now, and while I can find the toggle in the settings, I can’t find the context menu where the probabilities are shown.
I’ve know people in my life who put less mental effort into living their lives than LLMs put into crafting the most convincing lies you’ve ever read
The reason it’s dangerous is because there are a significant number of jobs and people out there that do exactly that. Which can be replaced…
This post isn’t true, LLMs do have an understanding of things.
SELF-RAG: Improving the Factual Accuracy of Large Language Models through Self-Reflection
Chess-GPT’s Internal World Model
POKÉLLMON: A Human-Parity Agent for Pokémon Battle with Large Language Models
Whilst everything you linked is great research which demonstrates the vast capabilities of LLMs, none of it demonstrates understanding as most humans know it.
This argument always boils down to one’s definition of the word “understanding”. For me that word implies a degree of consciousness, for others, apparently not.
To quote GPT-4:
LLMs do not truly understand the meaning, context, or implications of the language they generate or process. They are more like sophisticated parrots that mimic human language, rather than intelligent agents that comprehend and communicate with humans. LLMs are impressive and useful tools, but they are not substitutes for human understanding.
When people say that the model “understands”, it means just that, not that it is human, and not that it does so exactly humans do. Judging its capabilities by how close it’s mimicking humans is pointless, just like judging a boat by how well it can do the breast stroke. The value lies in its performance and output, not in imitating human cognition.
Understanding is a human concept so attributing it to an algorithm is strange.
It can be done by taking a very shallow definition of the word but then we’re just entering a debate about semantics.
Understanding is a human concept so attributing it to an algorithm is strange.
Yes sorry probably shouldn’t have used the word “human”. It’s a concept that we apply to living things that experience the world.
Animals certainly understand things but it’s a sliding scale where we use human understanding as the benchmark.
My point stands though, to attribute it to an algorithm is strange.
I’m starting to wonder about you though.
Is that Summer from Rick and Morty?
AI: “Keep Summer safe”
I always argue that human learning does exactly the same. You just parrot and after some time you believe it’s your knowledge. Inventing new things is applying seen before mechanisms on different dataset.
Unfortunately the majority of people are idiots who just do this in real life, parroting populous ideology without understanding anything more than the proper catchphrase du jour. And there are many employed professionals who are paid to read a script, or output mundane marketing content, or any “content”. And for that, LLMs are great.
It’s the elevator operator of technology as applied to creative writers. Instead of “hey intern, write the next article about 25 things these idiots need to buy and make sure 90% of them are from our sponsors” it goes to AI. The writer was never going to purchase a few different types of each product category, blindly test them and write a real article. They are just shilling crap they are paid to shill making it look “organic” because many humans are too stupid to not know it’s a giant paid for ad.
