TypeSafe AI: Reliable decisions rely on code, not decision models
TypeSafe AI responds to "why not call Jev a decision model": when faced with complex data, the model itself cannot guarantee reliable decisions; reliability requires code, and reliable decisions come from composing reliable judgments in code. It adds that you can hide semantic logic in string additional conditions, embedding vectors, and various ML, but data distributions are always stranger than you can imagine, so you must be clear about what you need to know and confirm that reading the data directly is sufficient.
View original postWhy don't we at TypeSafe call Jev a decision model? If you think of Jev's questions as making *decisions*, I believe you'll use it at the wrong layer of abstraction and your reliability will suffer. I wrote all about this on our site 🧵👇 https://t.co/CfY5W84NqA
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Why don't we at TypeSafe call Jev a decision model? If you think of Jev's questions as making *decisions*, I believe you'll use it at the wrong layer of abstraction and your reliability will suffer. I wrote all about this on our site 🧵👇 https://t.co/CfY5W84NqA
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so we heard you like decision models
but how do you make reliable decisions against gnarly data with a model?
you don't: reliability requires code, and so reliable decisions are made by composing reliable judgments in code
Jev makes reliable judgments