I like that they're being up front about this. Benchmarks are a metric that can be gamed. They give you an approximate estimate of where things land, but you really need to test for your use case.
show comments
tyushk
Cool to see another model with support for bounding boxes on images. Really wish to see segmentation in a future release; Gemini 3.5 Flash-Lite is mandatory in my use case as it's the best model for semantic image segmentation in my experience.
show comments
120bits
Slightly unrelated, but I really like the website styling. Looks like an improved version of Linux From Scratch dos.
Sounds like an incremental change with context size change, new "box" type, and composable images.
As it's minor change did not expect much, but having a higher context helps for sure. I will own the errors for passing bigger context.
show comments
jofzar
Interesting way to release this, I'm not sure how to say this, but this has a real "enterprise"/old school taste to it verses how all the other models/AI companies are releasing things.
Very refreshing.
hexasquid
I'm curious what people are building with these models
show comments
kypro
I'm aware this is an unproductive comment, but why are all their releases so cringe? It's like they're written by a Reddit mod or something...
> For the builders AND dreamers
> Enter the danger zone at your own risk.
> Size does matter, apparently
> We’re trying something new out here: we’re going to treat you guys like adults
> Lots of people love to ask what kind of sci-fi we’re releasing next
That said, their docs are great and don't seem to include all the Reddit cringe.
show comments
matt3210
How does JEV prevent distillation?
show comments
benaduggan
So they held back a bunch of features because they knew they had basically no moat, and now they're trickling out a bit more functionality to try to convince people they are better than others and move fast? And using Apple advert slogans to show how cool they are?
> Warning: AI benchmarks. Please don't trust them
I like that they're being up front about this. Benchmarks are a metric that can be gamed. They give you an approximate estimate of where things land, but you really need to test for your use case.
Cool to see another model with support for bounding boxes on images. Really wish to see segmentation in a future release; Gemini 3.5 Flash-Lite is mandatory in my use case as it's the best model for semantic image segmentation in my experience.
Slightly unrelated, but I really like the website styling. Looks like an improved version of Linux From Scratch dos.
In case you need something a bit more lightweight, or want privacy. You can get amazing (better in a lot of cases) accuracy and performance from local models that run and train on CPU: https://jeffyclassify.com/blog/when-llms-fail-at-classificat...
Sounds like an incremental change with context size change, new "box" type, and composable images.
As it's minor change did not expect much, but having a higher context helps for sure. I will own the errors for passing bigger context.
Interesting way to release this, I'm not sure how to say this, but this has a real "enterprise"/old school taste to it verses how all the other models/AI companies are releasing things.
Very refreshing.
I'm curious what people are building with these models
I'm aware this is an unproductive comment, but why are all their releases so cringe? It's like they're written by a Reddit mod or something...
> For the builders AND dreamers
> Enter the danger zone at your own risk.
> Size does matter, apparently
> We’re trying something new out here: we’re going to treat you guys like adults
> Lots of people love to ask what kind of sci-fi we’re releasing next
That said, their docs are great and don't seem to include all the Reddit cringe.
How does JEV prevent distillation?
So they held back a bunch of features because they knew they had basically no moat, and now they're trickling out a bit more functionality to try to convince people they are better than others and move fast? And using Apple advert slogans to show how cool they are?