Earlier quoted context omitted.
Same. I've been putting off joining their Discord though (just because I don't use Discord often), maybe there's some info about that there.
Premium has not be released yet.
What will be the difference with Premium?
Tell HN: ChatGPT is fantastic for finding and solving issues in logs
171–180 of 184 posts
Re: Tell HN: ChatGPT is fantastic for finding and solving issues in logs
#172Re: Tell HN: ChatGPT is fantastic for finding and solving issues in logs
#173Earlier quoted context omitted.
I keep seeing anecdotes like this, and I wonder: How do you feel about the privacy aspect of this? To do this, you had to feed your email into GPT-4, right?
Why do you think your email is private? Is your email provider more aligned with your interests or more secure than OpenAI? I doubt either Google or Microsoft care about your privacy (no difference).
Mine isn't private. I hand my email out to anyone who wants it, including search engines and presumably AIs. It's right there on my website. If you want my email, I'll happily give it to you.
Emails are "personally identifiable".
Your email can be used to link almost every online purchase you've ever made for example. That is what makes them dangerous, and it's what we need to change to improve privacy. It should be possible for companies to send invoices and shipping notices without linking the order to the customer's email address (or their name, or street address, or any other personally identifiable information).
We're a long way from being able to do that with invoices and shipping notifications but there's a lot of other systems where emails aren't necessary and shouldn't be associated with a record - even though emails are not private.
Re: Tell HN: ChatGPT is fantastic for finding and solving issues in logs
#174[deleted]
Re: Tell HN: ChatGPT is fantastic for finding and solving issues in logs
#175Earlier quoted context omitted.
I think there's a widely held misconception that anything you paste into GPT-4 will be used as raw training data by the model. Some people even seem to believe that it's learning continuously, so something you paste in could show up in an answer for another user a few minutes later. My mental model of how this works is somewhat different: - It takes months to train a model on raw data, and OpenAI train new ones (that…
Could you imagine if they did? Someone might ask it: "How do you I figure out if this person killed someone?" and it responds: "I can't be certain if they killed them but last week they asked me where they should hide the body." But seriously, I think best argument for this is that the EU(or other euro nations) would not hesitate to go after a US company for collecting user data in violation of their data privacy law…
> last week they asked me where they should hide the body.
ChatGPT is a static model and has zero memory. It can't even "remember" anything word-to-word as it generates its output! It starts its processing over from scratch for each word.
Re: Tell HN: ChatGPT is fantastic for finding and solving issues in logs
#176Earlier quoted context omitted.
Were you able to paste his writings all in one prompt without exhausting token space? Or did you have to do something tricky to get around that?
The summary of his world building wasn't super huge, so it was just large enough to fit the ~8000 token limit for the GPT-4 model on OpenAI after I trimmed it a bit. I, too, would like to know how to properly get around these technical limitations.
I know it is something along these lines: Install a vector database. Use the API to get vector embeddings for the manuscript, by getting them in chunks. Apparently this is possible the with API even though it's not with normal ChatGPT? Then, think of the query you want to ask. Use the API not to answer the query, but to get the vector embedding for the query. Then, do a search in the vector database to get the vectors that are "near" the vector for the query. Then, finally send the query's vector, and all the "near" vectors to the API. And then you'll get your answer.
I don't know how to do any of that yet. So far it seems like milvus might be the easiest vector db to install locally. But vectors for text passages are very large, so I'm not sure why I'd expect the final query of multiple vectors to be small enough for the token limit. And I'm not really sure yet how to send a query to ChatGPT in vector form.
(Ideally this could work against an open model that isn't ChatGPT.)
Re: Tell HN: ChatGPT is fantastic for finding and solving issues in logs
#177Earlier quoted context omitted.
Why do you think your email is private? Is your email provider more aligned with your interests or more secure than OpenAI? I doubt either Google or Microsoft care about your privacy (no difference).
Mine isn't private. I hand my email out to anyone who wants it, including search engines and presumably AIs. It's right there on my website. If you want my email, I'll happily give it to you. Emails are "personally identifiable". Your email can be used to link almost every online purchase you've ever made for example. That is what makes them dangerous, and it's what we need to change to improve privacy. It should be…
I think they meant email contents not email address. As in, your provider reading your email.
Re: Tell HN: ChatGPT is fantastic for finding and solving issues in logs
#178Earlier quoted context omitted.
The summary of his world building wasn't super huge, so it was just large enough to fit the ~8000 token limit for the GPT-4 model on OpenAI after I trimmed it a bit. I, too, would like to know how to properly get around these technical limitations.
I know it is something along these lines: Install a vector database. Use the API to get vector embeddings for the manuscript, by getting them in chunks. Apparently this is possible the with API even though it's not with normal ChatGPT? Then, think of the query you want to ask. Use the API not to answer the query, but to get the vector embedding for the query. Then, do a search in the vector database to get the vector…
Ask GPT-4 to compress the prompt in several shots, do one last shot with the compressed chunks
Re: Tell HN: ChatGPT is fantastic for finding and solving issues in logs
#179Earlier quoted context omitted.
You should turn this into a product (or open source it). I'd imagine this is a pain point for many, myself included.
Thanks for the feedback. I think I will just throw it up onto GitHub. It’s really a hastily thrown together dump of Python code. One of the ugliest things I ever produced from my keyboard. Then again, it does work.
still interested 2 days later!
Re: Tell HN: ChatGPT is fantastic for finding and solving issues in logs
#180Earlier quoted context omitted.
That log line ( with the four space at the front for HN formatting) is 40 tokens [1]. You can easily fit several hundred log lines with GPT4 8k context and with the incoming 32K context, you'll be able to fit close to a thousand log lines. That's a lot of context, especially if you can prefilter from relevant services, nodes, etc. or provide a multi-node trace [1] https://platform.openai.com/tokenizer
200 lines @ 40 tokens per line equates to 8,000 tokens. That costs $1.60. for one query.
Without even trying to check the math, I can tell you this is wrong. Cost is way way less. With 8k context i havent even been close to 1USD a day even with huge prompts. Yes i have API access to GPT-4