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True. Microsoft's all in, Apple's all in, Nvidia is selling shovels, insurance companies are all in, police & military are all in, education is all in, office m
by mouse_ 2y ago
True. Microsoft's all in, Apple's all in, Nvidia is selling shovels, insurance companies are all in, police & military are all in, education is all in, office management is all in. Who is left to pump line up?
- guerrilla 2y agoAs far as I know, finance is not all in. I see Goldman Sachs doing experiments, for example, but it doesn't feel like they're convinced yet.
- K0balt 2y agoFinance is basically all of the reasons not to use (generative, LLM based) AI , all in one vertical. The poster child of determinism.
- baq 2y agoFinance is all in on reading 10-Ks and generating summaries. If you have decisions in mind, I’ll be referring to IBM 1979 slide until an HR LLM fires me.
- guerrilla 2y agoThat's not finance, that's just a generic application, and I think it's a terrible idea that won't last anyway.
- eru 2y agoCould you please explain? Finance is a big industry, and they are doing lots of different things.
- oblio 2y agoNobody wants to lose money (savings) or go bankrupt because of hallucinations.
- eru 2y agoThat's one small part of finance. (And essentially solved mechanically with index funds.) There's a lot more to finance outside of that.
- oblio 2y agoAt the end of the day, the hard limit in finance is defaulting. Everything outside that is financial poetry (or engineering :-p). I know every segment of finance loves to pretend that's not the case, because their jobs (and high salaries) frequently rely on that not being true (see the subprime mortgage crisis).
- eru 2y ago> At the end of the day, the hard limit in finance is defaulting. Everything outside that is financial poetry (or engineering :-p). You are forgetting all about regulations and taxation (and how to work with / around them). And how to cleverly read documents, and exploit loop holes in contracts. There's so much more to finance. (And for eg stocks or commodities, there's not even any notion of defaulting. Defaulting only really makes sense when you have fixed obligations. 'Fixed income' is only one part of finance.) > (see the subprime mortgage crisis) That's actually a more nuanced topic than you think. See eg https://kevinerdmann.substack.com/p/subprime-bank-runs-and-the-global https://kevinerdmann.substack.com/p/subprime-bank-runs-and-t... and other posts by Kevin Erdmann on the topic.
- K0balt 2y agoSure, there’s lots of room for LLMs in helping to do clerical work, HR, that kind of thing. I was actually thinking of the direct management of funds and investments. So yeah, like probably all businesses, the ancillary functions can probably improve productivity using Generative AI with a minimal hit to quality.
- eru 2y agoYou are right about the clerical work, but even pure finance is a lot more than 'direct management of funds and investments'. Have a look at Matt Levine's Money Stuff newsletter for a taste. And I'm not quite sure why you mention determinism in the grandfather comment? Finance people have been using Monte Carlo simulations for ages. (And removing non-determinism from LLMs by fixing the seed of any pseudo-random number generator used wouldn't really change anything, would it?)
- asdev 2y agono one is successfully using LLMs for anything other than customer service related things and text generation(coding, writing)
- mode80 2y agomere trillian dollar industries. so far.
- bongodongobob 2y agoRubbish. I built a pipeline to handle document classification that successfully took care of ~70TB of mostly unstructured and unorganized data, by myself, in a couple weeks, with no data engineering background whatsoever. This was quite literally impossible a couple years ago. The amount of work that saved was massive and is going to save us a shit ton of money on storage costs. Decades worth of invoices and random PDFs are now siloed properly so we can organize and sort them. This was almost intractable a few years ago.
- aitchnyu 2y agoCould you describe your stack and how its much more effective than two years ago? I heard of printed-table OCR and doc classification years back.
- mewpmewp2 2y agoBut LLM is obviously able to organize documents and data much more intelligently than any ML algorithm from the past.
- bongodongobob 2y agoTagging with in house metadata like division, job code, who was the project manager etc.
- musha68k 2y agoVery interesting. If I may ask: how are you handling the correctness issue? What's the workflow there if even able to spot a mishap?