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Posted by albelfio 19 hours ago

Introducing System One Models and Jev(typesafe.ai)
1582 points | 438 commentspage 9
petesergeant 18 hours ago|
This is basically a zero-shot classifier that can accept raw text (or structured text) as an input, and is able to classify that text as accurately (they claim) as a frontier-level LLM. I have workflows this would be useful for, looking forward to it showing up on OpenRouter.
CompleteSkeptic 18 hours ago|
exactly right!
whazor 17 hours ago||
A question I have, with the type { output: string }, would the model not become a LLM? And if it does, shouldn’t it cost the same as a LLM for output?
speedping 17 hours ago||
I don’t see this as an option in their website

You could theoretically ask “what is the next appropriate character?” and add the entire ascii charset but i doubt it’d work well and you’d be implementing autoregressive churn across network latency…

CompleteSkeptic 17 hours ago||
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)
sreekanth850 7 hours ago||
This is best thing to use for decision making, evaluation, classification. If I'm not wrong.
johnecheck 16 hours ago||
This makes me think of Expressions of Change [1], a project that aimed to make updates to a program a first-class primitive in a programming language. A model like this can't output code directly, but perhaps it would be well suited to select from the small set of discrete operations on code envisioned by the EoC author?

[1]: www.expressionsofchange.org

Imanari 7 hours ago||
> AI Map Reduce over Big Data

> Search for relevant information over giant corpuses

Do you mean as an alternative to embeddings?

faizshah 11 hours ago||
I think I missed why is this faster? What I’m reading here is it’s similar to constrained decoding but I’m not seeing the explanation of why it’s able to get those results.
cooljoseph 15 hours ago||
A few questions:

1. Do you provide any kind of largest common subtree caching for cheaper input?

2. Have you tried auto-generating Lisp programs structurally?

3. Have you tried augmenting a Lisp language with a `choice` function that makes choices given a prompt, the environment, and the continuation stack?

zenlikethat 14 hours ago|
(1) Nope, it's always the same input token cost

(2-3) No, but that's kind of a sick cook ... Want to get access and try it? nathan@typesafe.ai

cooljoseph 12 hours ago||
Thanks for the early access! I was testing the Lisp idea out in the playground, but I don't think the model is smart enough right now to generate actual code. I tried having Jev finish generating the code for a Fibonacci number function, but it kept wanting to create a literal number instead of refer to a variable which is a number. This happened both when I gave Jev the current program as a string and when I gave Jev the program as structured data.

Maybe I'm just not doing a very good job at prompting Jev, but I think right now it's not quite capable enough to generate Lisp code.

Link: https://console.typesafe.ai/playground?share=shr_148e1248984...

moffers 18 hours ago||
So is it a structured data-based language model? Or is there a model and a harness? Hopefully they’ll open up and explain more.
CompleteSkeptic 18 hours ago|
it is just a model, no harness yet ;)

it is a structured data model, but technically not a language model (it doesn't generate language)

nelaggy 10 hours ago|
insane doom demo i wonder what the limits of its intelligence are? i'm guessing it's not great at reasoning tasks, it seems breaking down the problem helps significantly, but how much does a problem need to be broken down for reliable performance? also this would be huge if it could run locally but it seems like there's no intention to do that at the moment
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