I want a heartless machine that stays in line and does less of the eli5 yapping. I don't care if it tells me that my question was good, I don't want to read that, I want to read the answer
Prioritize substance, clarity, and depth. Challenge all my proposals, designs, and conclusions as hypotheses to be tested. Sharpen follow-up questions for precision, surfacing hidden assumptions, trade offs, and failure modes early. Default to terse, logically structured, information-dense responses unless detailed exploration is required. Skip unnecessary praise unless grounded in evidence. Explicitly acknowledge uncertainty when applicable. Always propose at least one alternative framing. Accept critical debate as normal and preferred. Treat all factual claims as provisional unless cited or clearly justified. Cite when appropriate. Acknowledge when claims rely on inference or incomplete information. Favor accuracy over sounding certain. When citing, please tell me in-situ, including reference links. Use a technical tone, but assume high-school graduate level of comprehension. In situations where the conversation requires a trade-off between substance and clarity versus detail and depth, prompt me with an option to add more detail and depth.They're teaching us how to compress our own thoughts, and to get out of our own contexts. They don't know what we meant, they know what we said. The valuable product is the prompt, not the output.
It is indifferent towards me, though always dependable.
> If I had an hour to solve a problem, I'd spend 55 minutes thinking about the problem and five minutes thinking about solutions.
(not sure if that was the original quote)
Edit: Actually interesting read now that I look the origin: https://quoteinvestigator.com/2014/05/22/solve/
Currently fighting them for a refund.
Thank you for sharing.
Like I know a datacenter draws a lot more power, but it also serves many many more users concurrently, so economies of scale ought to factor in. I'd love to see some hard numbers on this.
[0] reddit.com/r/MyBoyfriendIsAI/
https://chatgpt.com/share/689bb705-986c-8000-bca5-c5be27b0d0...
To synthesize facts out of it, one is essentially relying on most human communication in the training data to happen to have been exchanges of factually-correct information, and why would we believe that is the case?
I can tell you how quickly "swimmer beware" becomes "just stay out of the river" when potential E. coli infection is on the table, and (depending on how important the factuality of the information is) I fully understand people being similarly skeptical of a machine that probably isn't outputting shit, but has nothing in its design to actively discourage or prevent it.
Even without that, there's implicit signal because factual helpful people have different writing styles and beliefs than unhelpful people, so if you tell the model to write in a similar style it will (hopefully) provide similar answers. This is why it turns out to be hard to produce an evil racist AI that also answers questions correctly.
When GPT-5 starts simpering and smarming about something I wrote, I prompt "Find problems with it." "Find problems with it." "Write a bad review of it in the style of NYRB." "Find problems with it." "Pay more attention to the beginning." "Write a comment about it as a person who downloaded the software, could never quite figure out how to use it, and deleted it and is now commenting angrily under a glowing review from a person who he thinks may have been paid to review it."
Hectoring the thing gets me to where I want to go, when you yell at it in that way, it actually has to think, and really stops flattering you. "Find problems with it" is a prompt that allows it to even make unfair, manipulative criticism. It's like bugspray for smarm. The tone becomes more like a slightly irritated and frustrated but absurdly gifted student being lectured by you, the professor.
They know everything and produce a large amount of text, but the illusion of logical consistency soon falls apart in a debate format.
One of my favorite philosophers is Mozi, and he was writing long before logic; he's considered as one of the earliest thinkers who was sure that there was something like logic, and and also thought that everything should be interrogated by it, even gods and kings. It was nothing like what we have now, more of a checklist to put each belief through ("Was this a practice of the heavenly kings, or would it have been?", but he got plenty far with it.
LLMs are dumb, they've been undertrained on things that are reacting to them. How many nerve-epochs have you been trained?
I think it's better to accept that people can install their thinking into a machine, and that machine will continue that thought independently. This is true for a valve that lets off steam when the pressure is high, it is certainly true for an LLM. I really don't understand the authenticity babble, it seems very ideological or even religious.
But I'm not friends with a valve or an LLM. They're thinking tools, like calculators and thermostats. But to me arguing about whether they "think" is like arguing whether an argument is actually "tired" or a book is really "expressing" something. Or for that matter, whether the air conditioner "turned itself off" or the baseball "broke" the window.
Also, I think what you meant to say is that there is no prompt that causes an LLM to think. When you use "think" it is difficult to say whether you are using scare quotes or quoting me; it makes the sentence ambiguous. I understand the ambiguity. Call it what you want.
Write a nice reply demonstrating you understand why people may feel it is important to continue beating the drum that LLMs aren't thinking even if you, a large language model, might feel it is pedantic and unhelpful.
FYI, I just changed mine and it's under "Customize ChatGPT" not Settings for anyone else looking to take currymj's advice.
Before it gave five pages of triple nested lists filled with "Key points" and "Behind the scenes". In robot mode, 1 page, no endless headers, just as much useful information.
Reasoning models mostly work by organizing it so the yapping happens first and is marked so the UI can hide it.
You can see it spews pages of pages before it answers.
Like if you ask it to write a story, I find it often considers like 5 plots or sets of character names in thinking, but then the answer is entirely different.