ChatGPT Pro
331–340 of 1001 posts
Re: ChatGPT Pro
#332The main difficulty when pricing a monthly subscription for "unlimited" usage of a product is the 1% of power users who use have extreme use of the product that can kill any profit margins for the product as a whole. Pricing ChatGPT Pro at $200/mo filters it to only power users/enterprise, and given the cost of the GPT-o1 API, it wouldn't surprise me if those power users burn through $200 worth of compute very, very…
Is compute that expensive? An H100 rents at about $2.50/hour, it's 80 hours of pure compute. Assuming 720 hours a month, 1/9 duty cycle around the clock, or 1/3 if we assume 8-hour work day. It's really intense, constant use. And I bet OpenAI spend less on operating their infra than the rate at which cloud providers rent it out.
Re: ChatGPT Pro
#333[flagged]
> In other words, it's a con. A con like that wouldn't last very long. This is for people who rely enough on ChatGPT Pro features that it becomes worth it. Whether they pay for it because they're freelance, or their employer does. Just because an LLM doesn't boost your productivity, doesn't mean it doesn't for people in other lines of work. Whether LLM's help you at your work is extremely domain-dependent.
Bernie Madoff ran his investment fund as a Ponzi scheme for over a decade (perhaps several decades)
Re: ChatGPT Pro
#334Re: ChatGPT Pro
#335Re: ChatGPT Pro
#336Re: ChatGPT Pro
#337[flagged]
> In other words, it's a con. A con like that wouldn't last very long. This is for people who rely enough on ChatGPT Pro features that it becomes worth it. Whether they pay for it because they're freelance, or their employer does. Just because an LLM doesn't boost your productivity, doesn't mean it doesn't for people in other lines of work. Whether LLM's help you at your work is extremely domain-dependent.
Re: ChatGPT Pro
#338Earlier quoted context omitted.
If a model is good enough (I’m not saying this one is that level) I could imagine individuals and businesses paying 20,000 a month. If they’re answering questions at phd level (again, not saying this one is) then for a lot of areas this makes sense
Let me know when the models are actually, verifiably, this good. They're barely good enough to replace interns at this point.
Re: ChatGPT Pro
#339Re: ChatGPT Pro
#340[flagged]
Wouldn't you say the same thing for most of the people? Most of the people suck at verifying truth and reasoning. Even "intelligent" people make mistakes based on their biases. I think at least LLMs are more receptive to the idea that they may be wrong, and based on that, we can have N diverse LLMs and they may argue more peacefully and build a reliable consensus than N "intelligent" people.
I think there's a huge difference because individuals can be reasoned with, convinced they're wrong, and have the ability to verify they're wrong and change their position. If I can convince one person they're wrong about something, they convince others. It has an exponential effect and it's a good way of eliminating common errors.
I don't understand how LLMs will do that. If everyone stops learning and starts relying on LLMs to tell them how to do everything, who will discover the mistakes?
Here's a specific example. I'll pick on LinuxServer since they're big [1], but almost every 'docker-compose.yml' stack you see online will have a database service defined like this:
services:
app:
# ...
environment:
- 'DB_HOST=mysql:3306'
# ...
mariadb:
image: linuxserver/mariadb
container_name: mariadb
environment:
- PUID=1000
- PGID=1000
- MYSQL_ROOT_PASSWORD=ROOT_ACCESS_PASSWORD
- TZ=Europe/London
volumes:
- /home/user/appdata/mariadb:/config
ports:
- 3306:3306
restart: unless-stopped
Assuming the database is dedicated to that app, and it typically is, publishing port 3306 for the database isn't necessary and is a bad practice because it unnecessarily exposes it to your entire local network. You don't need to publish it because it's already accessible to other containers in the same stack.Another Docker related example would be a Dockerfile using 'apt[-get]' without the '--error-on=any' switch. Pay attention to Docker build files and you'll realize almost no one uses that switch. Failing to do so allows silent failures of the 'update' command and it's possible to build containers with stale package versions if you have a transient error that affects the 'update' command, but succeeds on a subsequent 'install' command.
There are tons of misunderstandings like that which end up being so common that no one realizes they're doing things wrong. For people, I can do something as simple as posting on HN and others can see my suggestion, verify it's correct, and repeat the solution. Eventually, the misconception is corrected and those paying attention know to ignore the mistakes in all of the old internet posts that will never be updated.
How do you convince ChatGPT the above is correct and that it's a million posts on the internet that are wrong?
1. https://docs.linuxserver.io/general/docker-compose/#multiple...