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Easy. The article asks us to believe. There's a handy list to check against the article here: https://dmitriid.com/everything-around-llms-is-still-magical-and-
by troupo 1y ago
Easy. The article asks us to believe.
There's a handy list to check against the article here: https://dmitriid.com/everything-around-llms-is-still-magical-and-wishful-thinking https://dmitriid.com/everything-around-llms-is-still-magical... starting at "For every description of how LLMs work or don't work we know only some, but not all of the following"
- johnfn 1y agoIt seems to me like we have the answers to all those questions. - Do we know which projects people work on? It's pretty easy to discover that OP works on https://livox.com.br/en/ https://livox.com.br/en/, a tool that uses AI to let people with disabilities speak. That sounds like a reasonable project to me. - Do we know which codebases (greenfield, mature, proprietary etc.) people work on The e2e tests took 2 hours to run and the website quotes ~40M words. That is not greenfield. - Do we know the level of expertise the people have? It seems like they work on nontrivial production apps. - How much additional work did they have reviewing, fixing, deploying, finishing etc.? The article says very little.
- troupo 1y ago> The article says very little. And that's the crux, isn't it. Because that checklist really is just the tip of the iceberg. Some people have completely opposite experiences: https://news.ycombinator.com/item?id=45152139 https://news.ycombinator.com/item?id=45152139 Others question the validity of the approach entirely: https://news.ycombinator.com/item?id=45152668 https://news.ycombinator.com/item?id=45152668 Oh, don't get me wrong: I like the idea. I would trust LLMs with this idea about as far as I could throw them.