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.

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

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.

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

A lot of cross pollination between employees. Smart people who like maths and getting paid a lot of money used to go to HFT firms. Now they go to AI labs.