Why are both AI giants choosing to pay attention specifically to this space out of all other spaces they could choose to focus on?

Because, like engineers, their work requires intelligence and would benefit from highly adaptable software.

Finance and engineering both have a degree of verifiably. Building evals around finance is easier than, e.g., marketing work.

Because they have the money.

I just don't see the value prop for LLM for financial markets specifically but I guess I'm not familiar with the workflows of analysts.

"Backtest this for me"

"Analyze this"

"Find a pattern"

"Beat the market"

I'd imagine the main use case is to whitewash insider trading signals ...

Your imagination is pretty bad then

Reading tons of reports, no?

> Reading tons of reports, no?

  Reading != Understanding

Sure. I'm not saying it's a good idea. It was a glaring omission from the provided list.

It is an excellent idea - the first useful LLM most in finance have / will interact with is to throw the 1000's of daily reports into a vector database and query against that.

"Whats the consensus in todays research about AAPL?" Out comes a distilled report with clickable links back to the ai slop Goldmans et al sent out this morning.

> a distilled report with clickable links back to the ai slop Goldmans et al sent out this morning.

A summary with links back to AI slop is a _useful_ outcome? Why?

> Ai slop summary with links back to AI slop is a _useful_ outcome? Why?

Saves the junior from coming in at 4am to spend 3 hours doing it. They can spend more time fixing the slide deck.

Are you being sarcastic, or does finance really involve this much garbage-in/garbage-out?

Two reasons come to mind. 1. AI hype is the hottest it will ever be, better to sell into as many industries as you can now while everyone is excited about it. 2. There are a lot of unknowns as to what these tools will be best at, or which workflows it will improve or supplant. Better to get more people in more industries using the tool now to uncover these use cases.

It’s a $37B+ opportunity. 325k financial analysts * $113k / year.

Much of the work is repetitive or formulaic or error prone. Plus it’s all digital.

https://www.bls.gov/oes/2023/may/oes132051.htm

I need a product like this(currently using a limited in-house version), but I'm not paying $125k/year/seat to get locked into a black box ecosystem that might change or get shut down in a year.

We are using LLMs to analyze corporate filings/voice memos in real time to find anomalies/correlations. This works and was previously impossible. We also use LLMs for other financial stuff. And, no, LLMs don't make financial decisions, they only point us to check X.

Because large customers in this vertical are going nuts over AI and are willing to spend massive amounts of money on stuff like this

More revenue to be made than other industries?

Salaries are higher in Finance than other industries for the same job, as it is well known.

But also, budgets for everything else is also higher.

These companies will sign 3 year deals for support, have you onsite implementing and training + app and API subscriptions.

"Why are both AI giants choosing to pay attention specifically to this space out of all other spaces they could choose to focus on?"

how can you ask this question, it literally called "financial". its screams money all over the place

Money, will happily lay off staff for a buck the next morning.

If all the hedge funds think their workers will have an edge if they are llm powered cybernetics, it will be an amazingly profitable arms race for the AI firms.

Hedge funds are often small companies. And will have tech wizz kids aplenty.

The title is 'Financial Services' which is a broader sector.

It's way easier to do market manipulation if your product is the one fucking things up.