alt Hacker NewsOne example: I've been working for a couple years (not full time) on a high performance FOSS address matcher: https://github.com/moj-analytical-services/uk_address_matche...
Until recently LLMs have been really bad at this task. I always knew it was coming, but with GPT 5.6 they've suddenly become good. It's pretty clear to me that it won't be long before most of my work on this is rendered pointless because the LLM can either do the classification itself (when given agentic access to the canonical list of addresses), or write a classifier itself if given enough labelled data. Of course these two are complementary
Given it is being trained on your project, the latter isn't that surprising. For the former, you could use LLMs yourself for the probabilistic matching as alternative method? Probably you don't because the trade-offs (like performance) are not worth it...