CompleteSkeptic

we've been public about this before the category was even created

of all comments, "enterprise" taste is among those I'd least expect

intentional to make it fun (:

typesafe ai | ONSITE in SF | basically all forms of engineering (front-end / back-end / infra)

help make jev!

typesafe.ai/careers

yes and can do many of those in parallel

unfortunately all hand-written :( my chief-of-staff does unironically handwrite em dashes though

the edit is right - jev would be cheaper, faster, and more self-consistent (in general)

we actually use astra (and fable) in this way for our evals: evals.typesafe.ai

someone on the team cooked hard on that and it shows example traces comparing our model to opus/sol

1. yes a general model 2. no training at all 3. but it is focused on "System 1" tasks (more human judgment, less math reasoning)

strings (and all sequential data structures) are not allowed at all - this is how we make sure all outputs can be computed in parallel (thus no output token cost)

They don't like adding stealth startups :(

very accurate!

the one nuance I'd get into is I'd call it "zero-shot" over "instruction-tuned" (the latter often implies a particular distribution), but very safe for sharing

> Type safety is not factual correctness.

I very much agree with this and want to hone in on where do actually disagree. Would you say a linear classifier hallucinates?

inputs are structured program state. there is an example at around second 30 of the doom demo

(though ideally everyone gets off the waitlist and can try it out for themselves )

we hope so! the bigger hope is to not just eat LLM market share, but to allow for people to use AI much more in the inner loop of software