Viewing profile — nnechm

Had a similar experience with meta. Extremely opaque decision making, terrible UX. Account permanently disabled ... did not follow community standards, literally on sign up to get …

Feels more and more like it's the best of times and the worst of times... Things feel off,but you have (mostly well-off) people talking about how great things are going to be and a…

Thank you for the advice, will implement accordingly.

I am assuming this is on Cofin and not on beatandraise.com, if so, please let me know, I shall fix it. You have 20 chats etc.

:) I guess its not very odd to say investment research is a lot of reading and LLMs are already very good at reading. So there is little doubt that LLMs will change the investment …

I don't think excel can be defeated :) I certainly do not expect financial professionals to switch to a chat interface. When you login into capitaliq or factset or look at a bloomb…

I think you are referring to the more hyped version where somehow LLMs can figure out how to get the most relevant information from 10Ks and do most of the investment process. My m…

Yes, information retrieval is hard :) A lot of people ask for 'can you get Apple's revenues by product category for all of 2020', how do you get the smallest piece of text that has…

That's a good question, for e.g if you want to get Microsoft's revenues by product category or apple's revenues in greater China. https://imgur.com/a/LdQkt7j You can also do this a…

A few things on prompting: 1. Get me google cloud revenues fails, because somehow gpt4 thinks i am talking about an entity called google cloud and not google :) 2. So in order to f…

Thanks for letting me know, i guess you use a different strategy of querying by company and by document. I see this when I try to get Apple's rest of asia pacific revenues for e.g …

Yes, they are definitely not primitive, but considering how the breakthrough in LLMs happened, i.e MSFT, GOOGL were working on it, even as late as 2021, Google's BERT was not reall…

Hi, Thanks for bringing that concern up. I shall keep it in mind and change it based on feedback from customers if it is an issue. Typically, people search for a company after a pr…

It would be possible for example to get AMD's revenues over time like this, it's tedious because of context size, but it's unrestricted, so you can get whatever datapoint you want.…

The functions tend to fail when the prompt is complex and the user asks for a lot of fields, and typically the last field in the json is not closed i.e missing a }, i guess openai …

As the answers are from the text, we can avoid hallucinations for the most part. I have not experienced made up numbers, instead errors are numbers that are typically misplaced, wh…

Yes, I think the broader point is you have these readers available on call via api, so you can do all that you suggested and more...

I am using openai's latest functions api, so you can get it to return arguments that will ensure that you get a json, it works pretty well most of the time. The json would then be …

Embeddings did not really work well enough for me, let us say you are looking for numerical text, so for e,g get me AMD's revenue from March 2022. The embedding representation need…

I am using openai's functions as that is a more reliable form of extracting json, but even that can fail sometimes as the response misses a "'" or a }

You can try it out for yourself... :) Here's an example, that asks for AMD's cash and makes an arbitrary calculation on total liabilities, the ai is smart enough to sum up everythi…

You are probably right, but there has been nothing like gpt4 before, having seen some versions before I would wager that their entire application can probably be redone for a fract…

I am not using inline XBRL, instead relying on gpt's ability to read tables.

I don't do handle news articles, and was just focusing on filings, so my answer would look for a filing. That's why it looks the way it does :)

Thanks, I don't feed the whole report in, unless necessary. Context size is a real limiting factor :), so you need to split it up into chunks that are meaningful on their own and f…