cross-posted from: https://lemmy.ml/post/2811405
"We view this moment of hype around generative AI as dangerous. There is a pack mentality in rushing to invest in these tools, while overlooking the fact that they threaten workers and impact consumers by creating lesser quality products and allowing more erroneous outputs. For example, earlier this year America’s National Eating Disorders Association fired helpline workers and attempted to replace them with a chatbot. The bot was then shut down after its responses actively encouraged disordered eating behaviors. "
Indeed, and it turns out that in order to predict the next word these things may be thinking about stuff.
There’s a huge amount of complex work that can go into predicting stuff. If you were to try to predict the next word that a person you’re speaking with was going to say, how would you go about it? Developing a mental model of that person’s thought processes would be a really good approach. How would you predict what the next thing that comes after “126+118=” is? Would you always get it exactly correct, or might you occasionally predict the wrong number?
I think you’re starting from the premise that these things can’t possibly be “thinking”, on any level, and are trying to reinterpret everything to fit that premise. These things are largely opaque black boxes, just like human brains are. Is it really so impossible that thought-like processes are going on inside both of them?
Yes, it is impossible. There are no “thoughts”. The bloody thing doesn’t know what an Apple is if you ask it to write a 500 page book about them. It just guesses a word, then from there guesses the next one and so on. That’s why it will very often confidently tell you aggravating bullshit. It has no concept of the things it spits out. It’s a “word calculator” so to speak. The whole thing is not “revolutionary” or “new” by any stretch. What is new is the ability to use tons and tons and tons of reference data which makes the output halfway decent and the GPU power that will make it’s speed halfway decent. Other than that, LLMs are.not.“thinking”.
A rather categorical statement given that you didn’t say anything with regards to how you think.
Maybe wait until we actually know more what’s going on under the hood - both in LLMs and in the human brain - before stating with such confident finality that there’s absolutely no similarities.
If it turns out that LLMs aren’t thinking, but they’re still producing the same sort of interaction that humans are capable of, perhaps that says more about humans than it does about LLMs.
sees a plastic bag being blown by the wind
Holy shit that bag must be alive
I’ve been making the same or similar arguments you are here in a lot of places. I use LLMs every day for my job, and it’s quite clear that beyond a certain scale, there’s definitely more going on than “fancy autocomplete.”
I’m not sure what’s up with people hating on AI all of a sudden, but there seems quite a few who are confidently giving out incorrect information. I find it most amusing when they’re doing that at the same time as bashing LLMs for also confidently giving out wrong information.
Can you give examples of that?
The one I like to give is tool use. I can present the LLM with a problem and give it a number of tools it can use to solve the problem and it is pretty good at that. Here’s an older writeup that mentions a lot of others: https://www.jasonwei.net/blog/emergence
I suspect it’s rooted in defensive reactions. People are worried about their jobs, and after being raised to believe that human thought is special and unique they’re worried that that “specialness” and “uniqueness” might be threatened. So they form very strong opinions that these things are nothing to worry about.
I’m not really sure what to do other than just keep pointing out what information we do have about this stuff. It works, so in the end it’ll be used regardless of hurt feelings. It would be better if we get ready for that sooner rather than later, though, and denial is going to delay that.
They produce this kind of output because they break doen one mostly logical system (language) onto another (numbers). The irregularities language has get compensated by the vast number of sources.
We don’t need to know more about anything. If I tell you “hey, don’t think of an Apple”, your brain will conceptualize an Apple and then go from there. LLMs don’t know “concepts”. They spit out numbers just as mindlessly as your Casio calculator watch.
The engineers of ChatGPT-4 themselves have stated that it is beginning to show signs of general intelligence. I put a lot more value in their opinion on the subject than a person on the Internet who doesn’t work in the field of artificial intelligence.
It’s PR by Microsoft. I am beginning to doubt the intelligence of many humans rather than that of ChatGPT considering these kinds of comments.
That wasn’t the engineers of GPT-4, it was Microsoft who have been fanning the hype pretty heavily to recoup their investment and push their own Bing integration and then opened their “study” with:
An actual AI researcher (Maarten Sap) regarding this statement: