Posted by albelfio 14 hours ago
FAQ: Is Jev just a smaller LLM?
Jev is neither small nor an LLM, hence being off the intelligence Pareto curve.
Image in documentation: https://mintcdn.com/ts-docs/aFVnpmCIX68NpsV1/images/ai-prime...
While this model may share much with GPT-style models on the encoder side, it clearly has a different decoder architecture. So is a high-parameter count language model an LLM even when it doesn't have a GPT-style decoder? The definitions are in flux.
They claim it's not an LLM, which I read as "not an auto-regressive token generator". I assume they are still using a transformer, otherwise they would be talking about the thing that's not a transformer, instead of all the fluff on the linked page. But they emphasize parallel generation, so is it like a text diffusion model?
you pass in your "prompt" and options (described in natural language) that it can respond with, in addition to your input. it gives back that option set with a probability assigned to each one
Rip there goes my excitement. I have a task that something like this would be great for but the list of options is a zero or two larger than that xd
Typesafe.AI sounds like some typescript/structured output type of tool…
What even is “system one” ?
IMO the product/tech is really there, just needs better communication.
I definitely agree it's underexplained in type safe.ai's materials.
I have to assume it's a reference to the fast, heuristic, intuitive "system 1" process in humans, as opposed to the slow, procedural, reasoning "system 2".
This theory is recognized, among others, in Daniel Kahneman 2002 Nobel prize on Economics.
I think that this specific part is not super interesting if your harness just recovers from invalid LLM outputs.
The latency and cost - yes, those are super interesting.
I'm very curious how much ressources are needed to run such a model. This could be a complete game changer for local applications.
The doom demo is quite cool
Instrument your game to output properties of entities near the player and the output is the various control inputs - moment to moment gameplay gets solved. Maybe augment with a tick-by-tick controlled stepping mode if particularly twitchy - an LLM can take care of the higher level reasoning then.
I suppose this is the same video as the one from the parent comment, but I don't know for sure - I don't have a twitter account and the above link doesn't work for me.
I can see the individual tweets in the browser while not signed in though.
It's in the parent article under a section named "Doom" in case that asset URL ever changes.
That would be the litmus test.
"Does not hallucinate" is not the same as "is never wrong".
So the ATC test could be the benchmark.
Just joined the waitlist, excited to try it out!
OpenAI has been teasing how fast computer use is with their models running on Cerebras chips but the difference here is a burning hole in your pocket.
https://developer.apple.com/library/archive/documentation/Ac...
