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ChatGPT Pro

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Re: ChatGPT Pro

#371

Earlier quoted context omitted.

>Whether LLM's help you at your work is extremely domain-dependent. I really doubt that, actually. The only thing that LLMs are truly good for is to create plausible-sounding text. Everything else, like generating facts, is outside of its main use case and known to frequently fail.

LLMs have become indispensable for many attorneys. I know many other professionals that have been able to offload dozens of hours of work per month to ChatGPT and Claude.

As a customer of legal work for 20 years, it is also way (way way) faster and cheaper to draft a contract with Claude (total work ~1 hour, even with complex back-and-forth ; you don't want to try to one-shot it in a single prompt) and then pay a law firm their top dollar-per-hour consulting to review/amend the contract (you can get to the final version in a day).

Versus the old way of asking them to write the contract, where they'll blatantly re-use some boilerplate (sometimes the name of a previous client's company will still be in there) and then take 2 weeks to get back to you with Draft #1, charging 10x as much.

Re: ChatGPT Pro

#373
post #278

The price seems entirely reasonable. $200 is about 1-2 hours of a professional's time in the USA. It's in everyone's interest for the company to be a sustainable business.

This doesn't increase my salary and if you are consultant it reduces your billable hours. No thanks.

Re: ChatGPT Pro

#374

If one makes $150 an hour and it saves them 1.25 hours a month, then they break even. To me, it's just a non-deterministic calculator for words. If it getting things wrong, then don't use it for those things. If you can't find things that it gets right, then it's not useful to you. That doesn't mean those cases don't exist.

Serious question: Who earns (other than C-level) $150 an hour in a sane (non-US) world?

US salaries are sane when compared to what value people produce for their companies. Many argue they are too low.

Re: ChatGPT Pro

#377
post #179
post #123

Yesterday, I spent 4.5hrs crafting a very complex Google Sheets formula—think Lambda, Map, Let, etc., for 82 lines. If I knew it would take that long, I would have just done it via AppScript. But it was 50% kinda working, so I kept giving the model the output, and it provided updated formulas back and forth for 4.5hrs. Say my time is $100/hr - that’s $450. So even if the new ChatGPT Pro mode isn’t any smarter but is…

> so I kept giving the model the output, and it provided updated formulas back and forth for 4.5hrs I read this as: "I have already ceded my expertise to an LLM, so I am happy that it is getting faster because now I can pay more money to be even more stuck using an LLM" Maybe the alternative to going back and forth with an AI for 4.5 hours is working smarter and using tools you're an expert in. Or building expertise…

I agree going back and forth with an AI for 4.5 hours is usually a sign something has gone wrong somewhere, but this is incredibly narrow thinking. Being an open-ended problem solver is the most valuable skill you can have. AI is a huge force multiplier for this. Instead of needing to tap a bunch of experts to help with all the sub-problems you encounter along the way, you can just do it yourself with AI assistance.

That is to say, past a certain salary band people are rarely paid for being hyper-proficient with tools. They are paid to resolve ambuguity and identify the correct problems to solve. If the correct problem needs a tool that I'm unfamiliar with, using AI to just get it done is in many cases preferable to locating an expert, getting their time, etc.

Re: ChatGPT Pro

#378
post #244

Earlier quoted context omitted.

> 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.

> A con like that wouldn't last very long. That's not a problem. OpenAI need to get some cash from its product because the competition is intense from free models. Moreover, since they supposedly used most of the web content and pirated whatever else they could, improvements in training will likely be only incremental. All the while, after the wow effect passed, more people start to realize the flaw in generative AI.…

> the competition is intense from free models

Models are about to become a commodity across the spectrum: LLMs [1], image generators [2], video generators [3], world model generators [4].

The thing that matters is product.

[1] Llama, QwQ, Mistral, ...

[2] Nobody talks about Dall-E anymore. It's Flux, Stable Diffusion, etc.

[3] HunYuan beats Sora, RunwayML, Kling, and Hailuo, and it's open source and compatible with ComfyUI workflows. Other companies are trying to open source their models with no sign of a business model: LTX, Genmo, Rhymes, et al.

[4] The research on world models is expansive and there are lots of open source models and weights in the space.

Re: ChatGPT Pro

#379
post #13
post #10

thats a big jump from 20 to 200 bucks (chatgpt plus vs chatgpt pro). What can pro do that would justify the 10x price increase?

Sounds like there’s the potential of asking it a question and it literally spending hours thinking about it.

Worth keeping in mind that performance on benchmarks seems to scale linearly with log of thinking time (https://openai.com/index/learning-to-reason-with-llms/). Thinking for hours may not provide as much benefit as one might expect. On the other hand, if thinking for hours gets you from not solving the one specific problem instance you care about to solving that instance, it doesn't really matter - its utility for you is a step function.

Re: ChatGPT Pro

#380
post #314
post #140

Earlier quoted context omitted.

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.

are you assuming that you can do o1 inference on a single h100?

Good question. How many H100s does it take? Is there any way to guess / approximate that?
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