roveo
Joined 7 years ago
Joined 7 years ago
When I stopped reading X, I had this thought one morning:
> The political crisis, the bloody war, the looming apocalypse only exist to distract you from the fact that you didn't fold the laundry.
The longer I live news-free, the more I find it true.
After a while they just stopped trying and decided that it's less reputational damage to just let it be.
I've been thinking about this a lot lately. I'm a data analyst and all these "give GPT you data warehouse schema, let it generate SQL to answer user's queries" products completely miss the point. An analyst has value as a curator of organizational knowledge, not translator from "business" to SQL. Things like knowing that when a product manager asks us for revenue/gmv, we exclude canceled orders, but include purchases made with bonus currency or promo codes.
Things like this are not documented and are decided during meetings and in Slack chats. So my idea is that in order to make LLMs truly useful, we'll create "hybrid" programming languages that are half-written by humans, and the part that's written by LLMs when translating from "human" language is simple enough for LLMs to do it reliably. I even made some weekend-prototypes with pretty interesting results.
Modern English lost the "n" part, but it was present in Middle English, milne.
Or you could make a "check your input one more time before confirming" step and display typos in e.g. names/emails there.
If the project is not throwaway, this first set of iterations is critical, without guidance LLMs will just bolt on things and produce special-cased spaghetti, even the very-frontier models.
Once the framework is established, it's smooth sailing.
But I haven't gotten to "very large" size yet, I expect it produces another kind of coherence problems.