The speed with which AI models are improving blows my mind. Humans quickly normalize technological progress, but it's staggering to reflect on our progress over just these two years.
Still i find very little use from LLMs in this front, but they do come in handy randomly.
When it works, it's pretty good, and sometimes great. But when failure modes look like the above I'm very wary of accepting its output.
But it still does the tasks you asked for, so that's the part that really matters.
Because.. yea, it is. However.. it keeps expanding, it keeps getting more useful. Yea people and especially companies are using it for things which it has no business being involved in.. and despite that it keeps growing, it keeps progressing.
I do find the "stochastic parrot" comments slowly dwindle in number and volume with each significant release, though.
Still, i find it weirdly interesting to see a bunch of people be both right and "wrong" at the same time. They're completely right, and yet it's like they're also being proven wrong in the ways that matter.
Very weird space we're living in.
If these systems showed understanding we would notice.
No one is denying that this form of intelligence is useful.
We just need more monkeys and it will be the same as a human brain.
More than once these tools fail at tasks a fifth grader could understand
You should re-read that very slowly and carefully and really think about it. Calling anyone that's skeptical a 'denier' is a red flag.
We have been through these AI cycles before. In every case, the tools were impressive for their time. Their limitations were always brushed aside and we would get a hype cycle. There was nothing wrong with the technology, but humans always like to try to extrapolate their capabilities and we usually get that wrong. When hype caught up to reality, investments dried up and nobody wanted to touch "AI" for a while.
Rinse, repeat.
LLMs are again impressive, for our time. When the dust settles, we'll get some useful tools but I'm pretty sure we will experience another – severe – AI winter.
If we had some optimistic but also realistic discussions on their limitations, I'd be less skeptical. As it is, we are talking about 'revolution', and developers being out of jobs, and superintelligence and whatnot. That's not the level the technology is at today and it is not clear we are going to do anything else other than get stuck in a local maxima.
There's the question, "is an LLM just autocomplete"? The answer to that question is obviously no, but the question is also a strawman - people who actually use LLM's regularly do recognize that there is more to their capabilities than randomized pattern matching.
Separately, there's the question of "will LLM's become AGI and/or become super intelligent." Most people recognize that LLM's are not currently super intelligent, and that there currently isn't a clear path toward making them so. Still, many people seem to feel that we're on the verge of progress here, and feel very strongly that anyone who disagrees is an AI "doomer".
Then there's the question of "are we in an AI bubble"? This is more a matter of debate. Some would argue that if LLM reasoning capabilities plateau, people will stop investing in the technology. I actually don't agree with that view - I think there is a lot of economic value still yet to be realized in AI advancements - I don't think we're on the verge of some sort of AI winter, even if LLM's never become super intelligent.
I think calling it intelligent is being extremely generous. Take a look at the following example which is a spelling and grammar checker that I wrote:
https://app.gitsense.com/?doc=f7419bfb27c89&temperature=0.50...
When the temperature is 0.5, both Claude 3.5 and GPT-4o can't properly recognize that GitHub is capitalized. You can see the responses by clicking in the sentence. Each model was asked to validate the sentence 5 times.
If the temperature is set to 0.0, most models will get it right (most of the time), but Claude 3.5 still can't see the sentence in front of it.
https://app.gitsense.com/?doc=f7419bfb27c89&temperature=0.00...
Right now, LLM is an insanely useful and powerful next word predictor, but I wouldn't call it intelligent.
Wouldn't this make chimpanzees and ravens and dolphins unintelligent too? You're asking it to do a task that's (mostly) easy for humans. It's not a human though. It's an alien intelligence which "thinks" in our language, but not in the same way we do.
If they could, specialized AI might think we're unintelligent based on how often we fail, even with advanced tools, pattern matching tasks that are trivial for them. Would you say they're right to feel that way?
Animals have the ability to learn and grow by themselves. LLMs are not intelligent and I don't see how they can be since they just follow the most likely path with randomness (temperature) sprinkled in.
Second, it's wrong. LLMs can learn within their context window. The main issue now is the limited size of their context window; animals have a lifetime of compressed context and LLMs only have approximately one conversation.
It honestly made no sense what you were saying so I didn't respond to that directly as I assumed it would be clear from my explanation as to why animals can be intelligent and LLM are not.
> LLMs can learn within their context window.
They don't learn from the context window as much as they use what is in the context window to define a probabilistic path. If you put something in the context window that it was never trained on, it would spit out BS or say it doesn't know.
If these tools boost tue productivity where is the output spike of all the companies, the spike in revenue and profits?
How often do we lose the benefit auto text generation to the loop of That’s wrong Oh yes of course, here is the correct version Nope, still wrong Prompt editing?