- LLMs can't learn, therefore, LLMs are only good for things on which they are trained.
- Captchas are not friendly with trial and error, so agentic solutions also don't help.
- It's impractical to train LLMs on everything.
- We humans are capable of creating infinite ways of captchas.
While each of these sentences is true, captchas will always win against LLMs.
There are a missing the context: The vibecoded application was written in python while the main code was written manually in C by Torvalds in this side project. He never ever said that AI produces better code than him in the language where he is proficientI.
The LLM usage are disclosed only for the projects where this information is relevant.
By the way there are a lot of farmers that doesn't need the power of tractors to make farming their livehood. Makes sense when you realize that not everything needs to be super fast and efficient, sometimes cheap, slow and constant is enough.
Anthropic is doing changes on their help support pages on what looks like it will be the next pricing change regarding how users will use Opus models on Pro Plan.
Given by the fact that the problem is 60 year old, isn't there a chance this was indirect solved already and the model just crossed informations to figure out the problem?
By looking the website this problem was never discussed by humans. The last comments were about gpt discovering it. I was expecting older comments coming to a 60 year old problem.
Am I missing something?
Great discovery though, there might be problems like that same case that worth a try for a "gpt check"
It's not weird if it comes from ESL. At least in portuguese there's no "it" equivalent for pronouns or any other neutral artifact in the language, in other words, everything has a gender, even an AI model, the same goes for objects e.g.: knife(she), fork(he), spoon(she), plate(he).
People often commit mistakes regarding that, the same way we don't have "they" as pronoun to someone we don't know the gender, so we address to these people as "dele(dela)" (masculine and feminine pronouns).
But if this is coming from someone who has english as a primary language it's definetely weird to treat models as person
Not sure what to think about the first part, but what you said about writing style, I think it's still reasonable to judge developers/engineers by writing style:
- Writing style does reveal how people understand problems and their approach for solving them. People that prioritize direct solutions over complex abstractions are still valuable to catch over engineered code.
- People with "good taste" in code can catch when AI generated code takes shortcuts to accomplish a certain task, this happens every day and we can't ignore it.
The state of AI code can be way better by 6 months or 1 year, or even more (we don't really know), but we're not there yet, and we can't wait until there to hire new people without considering those points.