365 karma · joined April 7, 2021
- Think about versioning early on. Do you want to allow backwards incompatible changes or lock it down? What about dependencies? Will all your components live at the same "level"? Or will some components be used to form bigger components?
- Talk to people. Constantly. You don't want to spend months building something no one will use. Your users are your peers and they're right there. Make sure it solves actual problems, and not just meet the goal of "we now have a component library."
I think the problem is that this premise itself is a big pill to swallow. Do people really believe this to be the case? I'm a minority who holds a severe dislike for cops in general, but I don't think this is something I'd ever agree with.
Maybe once these AI agents get reliable enough, it might be a fun side project to automate the verification process.
See this link for a recent example that's been on my mind: https://en.m.wikipedia.org/wiki/Mnet_vote_manipulation_inves... Basically, they just grabbed a random-looking numerical constant and used its multiples as the difference between vote numbers.
I don't think cilantro preferences are as set in stone as the story alludes.
It is indeed a problem that LLMs can instill a false sense of trust because it will confidently hallucinate. I see it as an education problem. You know and I know that LLMs can hallucinate and should not be trusted. The rest of the population needs to be educated on this fact as well.
Until they encounter a similar animal and get confused, at which point you understand the implicit heuristic they were relying on. (Eg. They confused a dairy cow as a zebra, which means their heuristic was a black-and-white quadrupedal)
Doesn't this seem remarkably close to how LLMs behave with one-shot or few-shot learning? I think there are a lot more similarities here than you give it credit for.
Also, I grew up in South Korea where early math education is highly prioritized (for better or for worse). I remember having to solve 2 dozen arithmetic problems every week after school with a private tutor. Yes, it was torture and I was miserable, but it did expose me to thousands more arithmetic questions than my American peers. All that misery paid off when I moved to the U.S. at the age of 12 and realized that my math level was 3-4 years above my peers. So yes, I think human intelligence accuracy also does improve with more training data.
We need some actual fact-based education around weed.
Thanks Google, for appointing yourself as the Sunday school snitch.