I'm a patient person, but it can be frustrating to have to endure 10 minutes of verbal diarrhea that eventually results in a "no" or "I don't know".
I don't know any Spaniards but I do know Filipinos and the confidence projection is a real thing. The Filipino IT guy confidently declared that my OnePlus Android phone wasn't certified for the software he was trying to install and was getting errors. It is a bog standard application that can be installed on any modern Android phone but the level of confidence he projected, just because he didn't know OnePlus as a brand, made me doubt myself until I turned on the critical hat and pushed back a little with alternative approaches, which solved the problem.
its common playbook for corporate self-development in NA.
- it's difficult
- ok fine but how
- it's difficult
- right i'll see that but how
- it's difficult
But I kid, I have a friend who's the same way. He's an Austrian who grew up in Chicago and was in the army.
I have considered the phenomenon. I somewhat disapprove but I can also see the advantage of always presenting a confident face
LLMs are just generating text, they don't know anything. They can't assess whether there is enough data for an answer. When you add a follow up prompt "This is wrong, why did you lie?" only then is it able to generate text, "I was wrong, I'm sorry," and so forth.
It seems that they are loath to tell anyone “no”, or that something can’t be done, or that an app doesn’t have a feature or can’t be used in a certain way. Especially when a feature has been removed for security reasons.
In fact, it gets so crazy that I simply cannot get a straight answer out of somebody and if I persist in my line of questioning and they become evasive or vague or I just can’t get a straight answer for long enough, ultimately, I suspect that the answer is “no”, and that they're simply not allowed to tell me, and they're paid and trained specifically to avoid uttering the “n-word”.
In my first job, as a network operator, my supervisor admonished me, and said “we must never tell a customer that we don't know something”. He said that we should tell the customer that “I will go ahead and find out for you, and get back to you on that”.
And that is kind of the kind of slippery non-answer I often received in my most recent job, that some manager or supervisor would “look into something” for me and “get back to me”. But the ‘getting back to me’ part never happened, and I began to suspect that it was a platitude meant to satisfy me enough that I would shut up for a while, and stop pressing the issue.
Asimov's Multivac at least had the dignity to wait.
They com like that from factory. Hardcoded to never say no.
Non?? Only those with sh*tty code, surely.
There's nothing inherently non-deterministic about inference.
It's not a guaranteed way to control their behavior, but you can more than move the needle.
Steering an LLM with a prompt is way less reliable than steering a car with a steering wheel, but there's still control. It's just not absolute.
I've been trying to work on a new LLM code editor that does just that. When you instruct it to do something, it will evaluate your request, try to analyze the action part of it, the object, subject, etc, and map them to existing symbols in your codebase or, to expected to be created symbols. If all maps, it proceeds. If the map is incomplete, it errors out stating that your statement contained unresolvable ambiguity
I think there is a real benefit here, and it might be the actual next beneficial grounded AI sustainable use in programming. Since I the current "Claude code and friends" are but a state of drunkenness we fell into after the advent of this new technology, but it will prove, with time, that this is not a sustainable approach
There's lots of people with lots of opinions, but you (often) have to pay for the good ones.
That's not an unfair take, I think. Again, just IME, they expect too much because the tool is oversold: it does not deliver that well. And we always hear, this new model is so much better, it's tiring.
I think we should all learn to use LLMs but we should still carefully review what they did. And that is what the employers don't quite get: the review still takes a lot of time. So, gains are not 10x but more like... 10%? Maybe 50 for boiler plate. Still gains are there, I guess.
And unfortunately a lot of people will say it’s their reports’ fault for not properly utilizing it (even as they barely use it) because otherwise they would have to admit that they bought a tool without any plan for how to deploy it. So regardless of what is or isn’t a fair take, the results are the same. We are burdened with utilizing a thing whether it is useful or not and the results are generally not what is measured, but rather “are you using it?”
I’m just glad I work at a company that has more reasonable expectations and has been very slowly, thoughtfully rolling it out to individuals at the company and assessing what is and isn’t good for. They are interested in getting me in line, but as somebody in video production to be perfectly honest the use case for Claude is a bit tricky to navigate. We don’t write a lot of scripts and I already have bespoke software for organizing/maintaining footage that isn’t on a subscription basis. The work I’m also doing doesn’t call for these speed-editing solutions that generate tik tok chaff. All our stuff is hours long and it’s high volume. Any video-centric AI service costs an arm and a leg.
I do think it could be useful for writing some terminal scripts and such, but as far as a daily tool we are still scratching our heads and thinking about it. But it’s nice to be able to do that without somebody saying “why aren’t you using it?” every meeting.
Maybe hackernews is becoming reddit...