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ChatGPT Enterprise

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131–140 of 532 posts

Re: ChatGPT Enterprise

#132
post #15
post #12

Earlier quoted context omitted.

Which part of that is new, because I was pretty sure they were saying "we do not train on your business data or conversations, and our models don’t learn from your usage" already. Maybe the SOC 2 and encryption is new?

They don't train on data when you either use the API or disable chat history, which is inconvenient.

yes, this is terrible. I want chat history, but I don't want them to use my data. Can't have both, even though I am paying $20/month!

Re: ChatGPT Enterprise

#133
post #129

Earlier quoted context omitted.

Ollama is very neat. Given how compressible the models are is there any work being done on using them in some kind of compressed format other than reducing the word size?

Yes, AutoGPTQ supports this (8, 4, 3, and 2 bit quantization/"compression" of weights + inference). GPTQ has also been merged into Transformers library recently ( https://huggingface.co/blog/gptq-integration ). GGML quantization format used by llama.cpp also supports (8,6,5,4,3, and 2 bit quantization).

'other than'...

Re: ChatGPT Enterprise

#134
post #113
post #65

Earlier quoted context omitted.

Also I'd heard anecdotally on the internet (Ethan Mollick's twitter I think) that 'code interpreter' was better than GPT 4 even for tasks that weren't code interpretation. Like it was more like GPT 4.5. Maybe it was an experimental preview and only enterprises are allowed to use it now. I never had access anyway.

I still have access in my $20/m non-Enterprise Pro account, though it has indeed just updated its name from Code Interpreter to Advanced Data Analysis. I haven't personally noticed it being any better than standard GPT4 even for generation of code that can't be run by it (ie non-Python code).

I've been using it heavily for the last week - hopefully it doesn't become enterprise only... it's very convenient to pass it some examples and generate and test functions.

And it does seem "better" than standard 4 for normal tasks

Re: ChatGPT Enterprise

#135

How is this different from using GPT api on Azure? I thought that allowed you to keep you data corpus/documents private as well, ie not get sent to their servers for training

One is a product. One is an API. Both can be useful, and both can come with privacy guarantees.

Re: ChatGPT Enterprise

#136
post #59

Earlier quoted context omitted.

I saw it, but it only mentions "applications" (whatever that means) and not bare documents. Does this mean companies might be able to upload, say, PDFs, and fine-tune the model on that?

Pretty unlikely. Generally you don't use fine-tuning for bare documents. You use retrieval augmented generation, which usually involves vector similarity search. Fine-tuning isn't great at learning knowledge. It's good at adopting tone or format. For example, a chirpy helper bot, or a bot that outputs specifically formatted JSON. I also doubt they're going to have a great system for fine-tuning. Successful fine-tunin…

When I first started working with GPT I was disappointed in this. I thought like the previous commentor that I could fine tune by adding documents and it would add it to the "knowledge" of GPT. Instead I had to do what you suggest is vector similarity search, and add the relevant text to the prompt.

I do think an open line of research is some way for users to just add arbitrary docs in an easy way to the LLM.

Re: ChatGPT Enterprise

#139
post #49

"Unlimited access to advanced data analysis (formerly known as Code Interpreter)" Code Interpreter was a pretty bad name (not exactly meaningful to anyone who hasn't studied computer science), but what's the new name? "advanced data analysis" isn't a name, it's a feature in a bullet point.

In my account it now says "Advanced Data Analysis" instead of "Code Interpreter". Looks like it is the new name.
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