beveradb

Char count for same functionality is still at least double in java vs python. It just feels like a chore to me. jetbrains helped, but still python is just so light

I've built a couple of useful products which leverage LLMs at one stage or another, but I don't shout about it cos I don't see LLMs as something particularly exciting or relevant to consumers, to me they're just another tool in my toolbox which I consider the efficacy of when trying to solve a particular problem. I think they are a new tool which is genuinely valuable when dealing with natural language problems. For example in my most recent product, which includes the capability to automatically create karaoke music videos, the problem for a long time preventing me from bringing that product to market was transcription quality / ability to consistently get correct and complete lyrics for any song. Now, by using state of the art transcription (which returns 90% accurate results) plus using an open weight LLM with a fine tuned prompt to correct the mistakes in that transcription, I've finally been able to create a product which produces high quality results pretty consistently. Before LLMs that would've been much harder!