Your comment made me ask myself: "Then why remove it? If it really is just a system prompt, I can't imagine tech debt or maintenance are among the reasons."
My best guess is this is product strategy. A markdown file doesn't require maintenance, but a feature's surface area does. Every exposed mode is another thing to document, support, A/B test, and explain to new users who stumble across it. I'm guessing that someone decided "Study Mode isn't hitting retention metrics", and decided to kill it. As an autodidact, I loved the feature, but as a software engineer I can respect the decision.
What I'm wondering about is whether there's a security angle to this as well. Assuming exposed system prompts are a jailbreak surface, if users can infer the prompt structure, would it make certain prompt injection attacks easier? I'm not well-versed in ML security, and I'd be curious to hear from someone who is.
There used to be a “Custom GPT” feature which basically just creates a prompt wrapper with some extra functionality like being able to call web APIs for more data. Can’t seem to find that menu right now, but it would have easily replicated the study feature. Maybe it was limited to paid accounts only.
Yeah custom gpts are only for paid users. However u can create a new project under "Projects", name it, then when u create it, you can see on the top right the three dots button, click it, open project settings, and there u can place your system prompt under instructions. Every chat you start in that project would send those instructions as a system prompt to the model you are chatting with. so essentially "Study Mode" could be recreated with this approach, or at least it should.
Has ChatGPT gotten worse over past few months or is it I just have seen other things higher quality, or they stopped caring about user or something?
All of a sudden feels like it gives me boilerplate and boiler plate of PR and cheesy reasoning, and like no actual answers - worse even - highly confident wrong answers that it then seeks to justify or explain (like it doesn't seem humble enough to be like "Actually, got that wrong" or if challenged it just caves over, accepts too readilythe assumptions in what the user is asking, or just blindly accepts a premise of the question) it's almost useless, like before it used to seem like could get it to emulate the way a certain writer or discourse speaks, now it seems like this derpy highschool just wants to be in kid that went into public relations and the language no matter what the topic seems always the same, it's really spammy feeling,
I could be asking it questions about like how medieval monks talked about light and the breath in latin and it will be replying like I'm interested in monetising or improving my lifestyle or some b.s. I don't think it used to be this way?
reminds of a circa 2003-6 wordpress sites - blackhat seo - feeling to generate back links to push affiliate links or something, with markov generated content designed to push back links for the actual human written landing page
It's not like this on the other llms, something's up.
Or maybe they have just found the niche and it is a bunch of people who do think like that - like I dunno - middle management the world over
that is scary ... bonus ghastly incantations of the epistemology of middle management
people have been talking about "models of models" for arbitration opportunity in inference for about 1.5 yrs.
Arbitration idea: if a user doesn't need high QOS of newest LLM, slip them a cheaper LLM, run their query at reduced quality. measure if they cost you fewer $s in the lower QOS. => profit.
For chatgpt the arbitration opportunity looks more like "we could allocate this amount of gpu to training or inference, we are losing money if we offer the highest quality infra"
In addition there's other interesting economics scaling that can be done outside of "models of models" that are far more profitable. I won't go over all of them (and some of them I feel are quite powerful) but the laziest one is that subscription models count on some zombie users as a counterweight to highly expensive single users, and as a source of stable cashflow.
Zombie users are ones that are paying for sub but not actively or barely using the service
I think you have it set to the wrong mode. If you set it to Thinking with “Extended” thinking effort, is it slower but almost never wrong (because it searches the web to get verify all its assumptions and answers).
I tried it a few times and always found it disappointing. It typically started off like a structured "lesson" but as I chatted with it, it would forget the syllabus is had proposed and we never "completed" the thing we set out to learn.
they do it with other stuff to i feel like they see how much users actually interact with those features and base their decsisoins kinda like how google owuld remove some features at random..
I remember videos with titles like "OPENAI CHANGED STUDYING COMPLETELY WITH THIS ONE SUPER UPDATE!" and obnoxious thumbnails on youtube when it was first launched. I guess studying changed it.
Also discussed on HN. Yeah I can ignore them, but a lot of people watch those videos and fall for the grift (going by their views) and that's sad. It personally annoys me also when yt recommends them to me because it thinks I'm interested in software
I make sure to hit not interested the second I see anything I very much don't want pop up in me feed. I don't want mine to drift towards the average feed of the lowest effort, sensationalist garbage.
Before this Sora, and before that large government contracts. I don't think they care so much for the random consumer anymore. They use anything and everyone for PR but they get closer to IPO they are focusing what actually might make them profitable.
I was concerned about big players offering the same functionality when building listendock.com, but maybe there is a place for specialized apps like that.
Anecdotally, I did not even know it was a thing. I either went to tutor me explicitly or purposefully explored a given branch with custom prompts ( + book recommendations on the subject ).
My best guess is this is product strategy. A markdown file doesn't require maintenance, but a feature's surface area does. Every exposed mode is another thing to document, support, A/B test, and explain to new users who stumble across it. I'm guessing that someone decided "Study Mode isn't hitting retention metrics", and decided to kill it. As an autodidact, I loved the feature, but as a software engineer I can respect the decision.
What I'm wondering about is whether there's a security angle to this as well. Assuming exposed system prompts are a jailbreak surface, if users can infer the prompt structure, would it make certain prompt injection attacks easier? I'm not well-versed in ML security, and I'd be curious to hear from someone who is.
I think this is pretty much the entirety of study mode. Never used it before but as long as there's no UI changes, yes, it's 100% replicable.
All of a sudden feels like it gives me boilerplate and boiler plate of PR and cheesy reasoning, and like no actual answers - worse even - highly confident wrong answers that it then seeks to justify or explain (like it doesn't seem humble enough to be like "Actually, got that wrong" or if challenged it just caves over, accepts too readilythe assumptions in what the user is asking, or just blindly accepts a premise of the question) it's almost useless, like before it used to seem like could get it to emulate the way a certain writer or discourse speaks, now it seems like this derpy highschool just wants to be in kid that went into public relations and the language no matter what the topic seems always the same, it's really spammy feeling,
I could be asking it questions about like how medieval monks talked about light and the breath in latin and it will be replying like I'm interested in monetising or improving my lifestyle or some b.s. I don't think it used to be this way?
reminds of a circa 2003-6 wordpress sites - blackhat seo - feeling to generate back links to push affiliate links or something, with markov generated content designed to push back links for the actual human written landing page
It's not like this on the other llms, something's up.
Or maybe they have just found the niche and it is a bunch of people who do think like that - like I dunno - middle management the world over
that is scary ... bonus ghastly incantations of the epistemology of middle management
Arbitration idea: if a user doesn't need high QOS of newest LLM, slip them a cheaper LLM, run their query at reduced quality. measure if they cost you fewer $s in the lower QOS. => profit.
For chatgpt the arbitration opportunity looks more like "we could allocate this amount of gpu to training or inference, we are losing money if we offer the highest quality infra"
In addition there's other interesting economics scaling that can be done outside of "models of models" that are far more profitable. I won't go over all of them (and some of them I feel are quite powerful) but the laziest one is that subscription models count on some zombie users as a counterweight to highly expensive single users, and as a source of stable cashflow.
Zombie users are ones that are paying for sub but not actively or barely using the service
Also discussed on HN. Yeah I can ignore them, but a lot of people watch those videos and fall for the grift (going by their views) and that's sad. It personally annoys me also when yt recommends them to me because it thinks I'm interested in software
You can use ublock to remove the sidebar completely
TL;DR: bet on stuff being removed