Someone said, "The AI you use today is the worst AI that you will ever use."
Someone could have said "The Google you use today is the worst Google you will ever use" 15 years ago and it may have sounded wise at the time.
What happens when people don't understand how AI works
31–40 of 359 posts
Re: What happens when people don't understand how AI works
#32I agree with the substance, but would argue the author fails to "understand how AI works" in an important way: LLMs are impressive probability gadgets that have been fed nearly the entire internet, and produce writing not by thinking but by making statistically informed guesses about which lexical item is likely to follow another Modern chat-tuned LLMs are not simply statistical models trained on web scale datasets.…
This doesn't follow with my understanding of transformers at all. I'm not aware of any human labeling in the training. What would labeling even do for an LLM? (Not including multimodal) The whole point of attention is that it uses existing text to determine when tokens are related to other tokens, no?
The transformers are accurately described in the article. The confusion comes in the Reinforcement Learning Human Feedback (RLHF) process after a transformer based system is trained. These are algorithms on top of the basic model that make additional discriminations of the next word (or phrase) to follow based on human feedback. It's really just a layer that makes these models sound "better" to humans. And it's a great way to muddy the hype response and make humans get warm fuzzies about the response of the LLM.
Re: What happens when people don't understand how AI works
#33I agree with the substance, but would argue the author fails to "understand how AI works" in an important way: LLMs are impressive probability gadgets that have been fed nearly the entire internet, and produce writing not by thinking but by making statistically informed guesses about which lexical item is likely to follow another Modern chat-tuned LLMs are not simply statistical models trained on web scale datasets.…
Ya I don’t think I’ve seen any article going in depth into just how many low level humans like data labelers and RLHF’ers there are behind the scenes of these big models. It has to be millions of people worldwide.
I'm really curious to understand more about this.
Right now there are top tier LLMs being produced by a bunch of different organizations: OpenAI and Anthropic and Google and Meta and DeepSeek and Qwen and Mistral and xAI and several others as well.
Are they all employing separate armies of labelers? Are they ripping off each other's output to avoid that expense? Or is there some other, less labor intensive mechanisms that they've started to use?
Re: What happens when people don't understand how AI works
#34Everyone, it's just "statistics". Numbers can't hurt you. Don't worry
Numbers can hurt you quite a bit when they are wrong.
For example, numbers are the difference between a bridge collapsing or not
Re: What happens when people don't understand how AI works
#35Re: What happens when people don't understand how AI works
#36Re: What happens when people don't understand how AI works
#37This is a good summary of why the language we use to describe these tools matters[1]. It's important that the general public understands their capabilities, even if they don't grasp how they work on a technical level. This is an essential part of making them safe to use, which no disclaimer or PR puff piece about how deeply your company cares about safety will ever do. But, of course, marketing them as "AI" that's ca…
People are paying hundreds of dollars a month for these tools, often out of their personal pocket. That's a pretty robust indicator that something interesting is going on.
Re: What happens when people don't understand how AI works
#38Someone said, "The AI you use today is the worst AI that you will ever use."
Someone could have said "The Google you use today is the worst Google you will ever use" 15 years ago and it may have sounded wise at the time.
That's a good point. But on the other hand Google search usefulness didn't have "scaling laws" / lines on capability graphs going up and up...
Re: What happens when people don't understand how AI works
#39The thesis is spot on with why I believe many skeptics remain skeptics:
> To call AI a con isn’t to say that the technology is not remarkable, that it has no use, or that it will not transform the world (perhaps for the better) in the right hands. It is to say that AI is not what its developers are selling it as: a new class of thinking—and, soon, feeling—machines.
Of course some are skeptical these tools are useful at all. Others still don’t want to use them for moral reasons. But I’m inclined to believe the majority of the conversation is people talking past each other.
The skeptics are skeptical of the way LLMs are being presented as AI. The non hype promoters find them really useful. Both can be correct. The tools are useful and the con is dangerous.
Re: What happens when people don't understand how AI works
#40This is a good summary of why the language we use to describe these tools matters[1]. It's important that the general public understands their capabilities, even if they don't grasp how they work on a technical level. This is an essential part of making them safe to use, which no disclaimer or PR puff piece about how deeply your company cares about safety will ever do. But, of course, marketing them as "AI" that's ca…
People are paying hundreds of dollars a month for these tools, often out of their personal pocket. That's a pretty robust indicator that something interesting is going on.
One thing these models are extremely good at is reading large amounts of text quickly and summarizing important points. That capability alone may be enough to pay $20 a month for many people.