| ▲ | jodacola an hour ago | |||||||
I won't over-generalize here, because maybe your statement is true in some cases, but I will provide a counterpoint: this is not true (in my experience) in real estate title insurance and escrow services. I've consulted for and led large teams for real estate title insurance and escrow companies for many years, and the domain expertise is so incredibly deep, nuanced, and multivariate (especially depending on jurisdiction) that building valuable and viable products in the space is incredibly difficult - before LLMs, and even now, with LLMs. Without getting too deep into it, I'm pretty bullish on AI (and have been very close to it and deep in it for a long time, while also very apprehensive about the effects it'll have on society), and I can tell you, from extensive attempts from myself and many on my teams to leverage the latest frontier LLMs to bring deep domain experience to bear to help drive valuable products: we have not yet seen success. It's not helping engineering folks, it's not helping product folks. It's creating a ton of questionable output and hasn't resulted in real ROI, and it's not capable of accurately answering deep domain questions without hallucinations or assuming what works in one jurisdiction works in all. I've seen success in many other areas, but not this domain - and, importantly, the regulatory environment in which title insurance operates is incredibly complex and strict, meaning you can't just YOLO LLM output into production (as much as we'd love to try so we can learn at a faster clip). And the kicker: we've found the way for us to build the best products is still going out into the field, sitting with escrow and title folks, watching them work, asking them questions, and designing for the real world, the regulatory nuances, the local client nuances, etc. You can't get that from an LLM. | ||||||||
| ▲ | globalnode an hour ago | parent [-] | |||||||
Agree with you there. What you are working on and the commenter below talking about surgery, they are all valid counter examples where the degree of expertise is quite extreme. But most people are not living on the edge of domain expertise. Im guessing 80% of the domain knowledge out there is up for grabs. For example: I dont have to go get a job at a security software company to figure out how security camera systems work and the principles involved, I can ask probing questions of an LLM and get most of it. The domain knowledge is embedded in the model. | ||||||||
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