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ChatGPT Pro

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651–660 of 1001 posts

Re: ChatGPT Pro

#651

Earlier quoted context omitted.

Startup I'm at has generated a LOT of content using LLMs and once you've reviewed enough of the output, you can easily see specific patterns in the output. Some words/phrases that, by default, it overuses: "dive into", "delve into", "the world of", and others. You correct it with instructions, but it will then find synonyms so there is also a structural pattern to the output that it favors by default. For example, if…

> if we tell it "Don't start your writing with 'dive into'", it will just switch to "delve into" or another synonym. LLMs can radically change their style, you just have to specify what style you want. I mean, if you prompt it to "write in the style of an angry Charles Bukowski" you'll stop seeing those patterns you're used to. In my team for a while we had a bot generating meeting notes "in the style of a bored teen…

Of course the "delve into" and "dive into" is just its default to be corrected with additional instruction. But once you do something like "write in the style of...", then it has its own tells because as I noted below, it is, in the end, biased towards frequency.

Re: ChatGPT Pro

#652

OpenAI is racing against two clocks: the commoditization clock (how quickly open-source alternatives catch up) and the monetization clock (their need to generate substantial revenue to justify their valuation). The ultimate success of this strategy depends on what we might call the enterprise AI adoption curve - whether large organizations will prioritize the kind of integrated, reliable, and "safe" AI solutions Open…

"whether large organizations will prioritize the kind of integrated, reliable, and "safe" AI solutions"

While safe in output quality control. SaaS is not safe in terms of data control. Meta's Llama is the winner in any scenario where it would be ridiculous to send user data to a third party.

Re: ChatGPT Pro

#653

I actually pay 166 Euros a month for Claude Teams. Five seats. And I only use one. For myself. Why do I pay so much? Because the normal paid version (20 USD a month) interrups the chats after a dozen questions and wants me to wait a few hours until I can use it again. But Teams plan gives me way more questions. But why do I pay that much? Because Claude in combination with the Projects feature, where I can upload two…

Are the limits applied to the org or to each individual user?

Re: ChatGPT Pro

#654

Earlier quoted context omitted.

Is their valuation proposition self fulfilling: the more people pipe their queries to OpenAI, the more training data they have to get better?

I don't think user submitted question/answer is as useful for training as you (and many others) think. It's not useless, but it's certainly not some goldmine either considering how noisy it is (from the users) and how synthetic it is (the responses). Further, while I wouldn't put it past them to use user data in that way, there's certainly a PR/controversy cost to doing so, even if it's outlined in their ToS.

In enterprise, there will be long content or document be poured into ChatGPT if there isn't policy limitation from company, which can be a meaning training data.

At least, there's possibility these content can be seen by staff in OpenAI as bad case, there's still existing privacy concerns.

Re: ChatGPT Pro

#655

Earlier quoted context omitted.

The problem is that OpenAI don't really have the enterprise market at all. Their APIs are closer in that many companies are using them to power features in other software, primarily Microsoft, but they're not the ones providing end user value to enterprises with APIs. As for ChatGPT, it's a consumer tool, not an enterprise tool. It's not really integrated into an enterprises' existing toolset, it's not integrated int…

This remind me why enterprise don't integrated OpenAI product into existing toolset, trust is root reason. It's hard to provide trust to OpenAI that they won't steal data of enterprise to train next model in a market where content is the most valuable element, compared office, cloud database, etc.

This is what the Azure OpenAI offering is supposed to solve, right?

Re: ChatGPT Pro

#656

The big question is if OpenAI will achieve "general" AI before their investors get fed up. I wonder if they used the success of ChatGPT to imply that they have a path to it. I don't see how else they achieved such a high valuation.

Spoiler alert: They will not.

Anyone claiming they're anywhere near something even remotely resembling AGI is simply lying.

What happened to "we're a couple years away from AGI"? Where's the Scaaaaaaryyyyyyy self aware techno god GPT-5? It's all BS to BS investors with. All of the rumored new models that were supposed to be out by now are nowhere to be seen because internally the improvement rate has cratered.

Re: ChatGPT Pro

#657

I actually pay 166 Euros a month for Claude Teams. Five seats. And I only use one. For myself. Why do I pay so much? Because the normal paid version (20 USD a month) interrups the chats after a dozen questions and wants me to wait a few hours until I can use it again. But Teams plan gives me way more questions. But why do I pay that much? Because Claude in combination with the Projects feature, where I can upload two…

Yep, I have 2 accounts I use because I kept hitting limits. I was going to do the Teams to get the 5x window, but I got instantly banned when clicking the teams button on a new account, so I ended up sticking with 2 separate accounts. It's a bit of a pain, but I'm used to it. My other account has since been unbanned, but I haven't needed it lately as I finished most of my coding.

Re: ChatGPT Pro

#658

I just bought a pro subscription. First impressions: The new o1-Pro model is an insanely good writer. Aside from favoring the long em-dash (—) which isn't on most keyboards, it has none of the quirks and tells of old GPT-4/4o/o1. It managed to totally fool every "AI writing detector" I ran it through. It can handle unusually long prompts. It appears to be very good at complex data analysis. I need to put it through i…

> Aside from favoring the long em-dash (—) which isn't on most keyboards Interesting! I intentionally edit my keyboard layout to include the em-dash, as I enjoy using it out of sheer pomposity—I should undoubtedly delve into the extent to which my own comments have been used to train GPT models!

On my keyboard (en-us) it's ALT+"-" to get an em-dash.

I use it all the time because it's the "correct" one to use, but it's often more "correct" to just rewrite the sentence in a way that doesn't call for one. :)

Re: ChatGPT Pro

#659

Earlier quoted context omitted.

> Aside from favoring the long em-dash (—) which isn't on most keyboards Interesting! I intentionally edit my keyboard layout to include the em-dash, as I enjoy using it out of sheer pomposity—I should undoubtedly delve into the extent to which my own comments have been used to train GPT models!

delve? Did ChatGPT write this comment for you?

FYI: It's trivial to fix any LLM's "slop" properties: https://github.com/sam-paech/antislop-sampler

https://openreview.net/forum?id=FBkpCyujtS&nesting=2&sort=da...

Re: ChatGPT Pro

#660
post #272

Earlier quoted context omitted.

I pay for both GPT and Claude and use them both extensively. Claude is my go-to for technical questions, GPT (4o) for simple questions, internet searches and validation of Claude answers. GPT o1-preview is great for more complex solutions and work on larger projects with multiple steps leading to finish. There’s really nothing like it that Anthropic provides. But $200/mo is way above what I’m willing to pay.

I have several local models I hit up first (Mixtral, Llama), if I don’t like the results then I’ll give same prompt to Claude and GPT. Overall though it’s really just for reference and/or telling me about some standard library function I didn’t know of. Somewhat counterintuitively I spend way more time reading language documentation than I used to, as the LLM is mainly useful in pointing me to language features. Afte…

Right on, I like to use local models - even though I also use OpenAI, Anthropic, and Google Gemini.

I often use one or two shot examples in prompts, but with small local models it is also fairly simple to do fine tuning - if you have fine tuning examples, and if you are a developer so you get the training data in the correct format, and the correct format changes for different models that you are fine tuning.

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