I really want to agree but the arguments he brings up make that extremely hard
Also, it seems that many don’t want to learn but instead expect to have all understanding outsourced to LLMs. Many seniors have noticed this and have stopped teaching juniors as the seniors don’t like the feeling of having their time wasted by teaching people who don’t want to learn.
Or may be it is because now a junior dev is expected to deliver to output of a senior?
Also stop saying “please” to an LLM. It does not have any feelings.
Yes, but I still prefer a nice tone. Like why should I change my manners just because it has no feelings? If anything the statistic predicts a friendlier answer when I say "please".
Again, I recommend people try running small LLMs locally where temperature and other settings are fully exposed and configurable to see this themselves. It is a good antidote to falling for the illusion that LLMs would actually be intelligent.
It's like recommending someone to buy the cheapest Lenovo Thinkpad to prove that Lenovo sucks.
However, the best models still have a pass rate of only about 50% on the Humanity’s Last Exam.
Haha, as if he (or really most people) even would understand 50% of those questions. I find it rather mind blowing that it's possible to put such diverse knowledge into a couple of TB. Or may be I'm just an idiot and it's common knowledge, "how many paired tendons are supported by the sesamoid bone of hummingbirds within Apodiformes".
LLMs are not a scam, but a useful tool and technology that has its uses. But the idea that AI has or will surpass humans any time soon in either capabilities or efficiency is simply not true
He's not wrong that LLMs are just useful tools but isn't it the purpose of a tool to surpass human capabilities and efficiency? Like even a bicycle makes traveling more efficient than just walking and a car has the capability to transport more items than any human. And its know more than two decades since computer surpassed human capabilities in chess. If a tool is neither more capable nor efficient, it's just a useless tool.
I mean I get his point that GenAI is to some degree over hyped but his arguments just dont hold in my opinion.
stop saying “please” to an LLM. It does not have any feelings.
Yes, but I still prefer a nice tone. Like why should I change my manners just because it has no feelings? If anything the statistic predicts a friendlier answer when I say "please".
It's a probabilistic generator. If you set the tone of the conversation it will follow it.
Try inserting a few jokes, puns etc into a conversation and you'll see that it responds kn kind.
Just like if you ask highly specific technical questions, it responds using highly technical language. If you ask questions in legalese it responds using precise legal terms.
That's what happens when a token predictor has a conversation: it can't have any tone other than what you give it.
So continue saying please, and you'll have more pleasant conversations.
In my opinion its just psychological hygiene. Even though its just a statistical predictor, treating it harshly just conditions me in treating other entities also harsh.
Try inserting a few jokes, puns etc into a conversation and you'll see that it responds kn kind.
A couple days ago I was setting up new SSH keys encrypted with Ubikey but because I feared losing them and lock me out I evaluated some backup plan with 2FA. Turned out in in my homelab arent that much alternative options, a fingerprint without Linux drivers, an old Galaxy S9 on pmOS without working camera etc. After some ruling out many solutions I proposed a butthole recognition because your butt is in your pants where a face can be recorded by security cams. It recognized the joke and honestly it wasnt the worst answer. It's reply felt like your CEO makes a really bad joke and you have to answer something in order to avoid awkward silence.
Yes, but I still prefer a nice tone. Like why should I change my manners just because it has no feelings? If anything the statistic predicts a friendlier answer when I say "please".
Like you I generally prefer polite phrasings over rude ones, and I'm certainly not going to tell you how you should communicate to LLM models, however it's interesting to note that being somewhat rude and to the point seems to have some objective advantages, see for example:
Mind Your Tone: Investigating How Prompt Politeness Affects LLM Accuracy (short paper)
I would hate for this style of communication to leak through to daily communications with humans (e.g. colleagues) though, so even just for that it can make sense to hold on to a polite form of communication :-).
I know at least about the first paper. But I'm pretty sure that heavily depends on the model and I'm not sure how reproducible those studies were.
I for myself use the trick to ask the model, after I explained what it has to do, what it thinks about my proposal. Of course I have no scientific evidence but to me it feels as it prevents some misunderstandings and the model follows more correctly my intention.
Comments
I really want to agree but the arguments he brings up make that extremely hard
Or may be it is because now a junior dev is expected to deliver to output of a senior?
Yes, but I still prefer a nice tone. Like why should I change my manners just because it has no feelings? If anything the statistic predicts a friendlier answer when I say "please".
It's like recommending someone to buy the cheapest Lenovo Thinkpad to prove that Lenovo sucks.
Haha, as if he (or really most people) even would understand 50% of those questions. I find it rather mind blowing that it's possible to put such diverse knowledge into a couple of TB. Or may be I'm just an idiot and it's common knowledge, "how many paired tendons are supported by the sesamoid bone of hummingbirds within Apodiformes".
He's not wrong that LLMs are just useful tools but isn't it the purpose of a tool to surpass human capabilities and efficiency? Like even a bicycle makes traveling more efficient than just walking and a car has the capability to transport more items than any human. And its know more than two decades since computer surpassed human capabilities in chess. If a tool is neither more capable nor efficient, it's just a useless tool.
I mean I get his point that GenAI is to some degree over hyped but his arguments just dont hold in my opinion.
It's a probabilistic generator. If you set the tone of the conversation it will follow it.
Try inserting a few jokes, puns etc into a conversation and you'll see that it responds kn kind.
Just like if you ask highly specific technical questions, it responds using highly technical language. If you ask questions in legalese it responds using precise legal terms.
That's what happens when a token predictor has a conversation: it can't have any tone other than what you give it.
So continue saying please, and you'll have more pleasant conversations.
In my opinion its just psychological hygiene. Even though its just a statistical predictor, treating it harshly just conditions me in treating other entities also harsh.
A couple days ago I was setting up new SSH keys encrypted with Ubikey but because I feared losing them and lock me out I evaluated some backup plan with 2FA. Turned out in in my homelab arent that much alternative options, a fingerprint without Linux drivers, an old Galaxy S9 on pmOS without working camera etc. After some ruling out many solutions I proposed a butthole recognition because your butt is in your pants where a face can be recorded by security cams. It recognized the joke and honestly it wasnt the worst answer. It's reply felt like your CEO makes a really bad joke and you have to answer something in order to avoid awkward silence.
Like you I generally prefer polite phrasings over rude ones, and I'm certainly not going to tell you how you should communicate to LLM models, however it's interesting to note that being somewhat rude and to the point seems to have some objective advantages, see for example:
Mind Your Tone: Investigating How Prompt Politeness Affects LLM Accuracy (short paper)
https://arxiv.org/abs/2510.04950
Understanding Tone-Dependent Inference Cost in Large Language Models
https://arxiv.org/abs/2607.23915
I would hate for this style of communication to leak through to daily communications with humans (e.g. colleagues) though, so even just for that it can make sense to hold on to a polite form of communication :-).
I know at least about the first paper. But I'm pretty sure that heavily depends on the model and I'm not sure how reproducible those studies were.
I for myself use the trick to ask the model, after I explained what it has to do, what it thinks about my proposal. Of course I have no scientific evidence but to me it feels as it prevents some misunderstandings and the model follows more correctly my intention.