It's the digital equivalent of Morty speaking with the death crystal: https://youtu.be/YjepJlvkdKs?t=51. The crystal shows him how he will die, so he iteratively determines his speech based on whether he sees himself dying with the life he wants.

>> write me a short story

> a story

I think this is the first time I’ve knowingly laughed at a model’s joke.

We’ve come full circle to “BERT has a mouth and it must speak” https://arxiv.org/abs/1902.04094

I went for a slightly different approach, described in this thread: https://bsky.app/profile/bernd.wachter.fi/post/3mvv2g4zxp22v

No code published currently, but if somebody is interested I can clean that up next weekend and throw it on github.

There might be some practical applications of this sort of idea like in situations where you want/have a heavily restricted vocabulary to build from. You can already do this with LLMs but they can get very... "distressed" if you force logits, whereas this would not.

Come to think of it, I'm now curious if it would do well at building SQL queries, say. (30 minutes later: I tried it, and it can do it reasonably well, but a normal model and linting will outperform it, though the inherent guard rails of a limited vocab are still intriguing.)

Given Jev does System 1 thinking, this would be equivalent to your ADHD heavy friend.

The worst part about this is someone still using poetry for python development.

Lousy chatbots are still surprisingly useful for prototyping. Wonder if Jev's structured data actually helped or hindered that process.

I saw a lot of ppl think about what jev could use under the hood and could someone explain why this can't just be an embedding model where we just embed all the input + decisions and give back the cosine (or whatever) similarities?

Try returning a short list of word options by lookup based on the current word completion. Would save some turns.

ha i just tried making a sort of ouija board for jev this morning. it struggled. i look forward to reading how this one works.

i think the next step is make Jev a emoji bot... The architecture and its limitations would work well in that regime imo better then human language.

> We know Jev.

I honestly don't.

Jev has taught me the same lesson three times over now.

When it first came out, I thought "this weekend, I'll do a little open-source Jev based on single-token prediction and the token logit output", but of course when it came to it, there were at least 5 that had already been done between me thinking that and getting around to it.

So I wrote up[0] what other people had done, but wasn't happy with how weak the benchmarks were, but in the time between writing the first word and the last few, two excellent sets of benchmarks had been written, so I was able to incorporate those. I published the article, and one of the authors of one of the implementations commented that I'd beaten him to doing the write-up he'd wanted to.

This morning I thought "huh, you could have some fun giving Jev a single letter or token at a time, turning it into a chatbot", but as the time of looking two people had already done this (and taken the gag further than I would have), and ... this is isn't either of the ones I'd found. I bet if you scratch the surface there already at leat 5.

Time from idea to output has dropped off a fucking cliff.

0: https://sgnt.ai/p/jev/

Codex and I were trying to infer why Jev gave a certain parameter a given score. So I asked codex to produce a list of like 30 plausible reasons Jev might've selected that and then presented Jev with the initial prompt, followed by "You scored this with XYZ. What was your reasoning for doing this?" And then allowed it to do a noul value for each of the reasons codex generated. Felt like those people that give their dogs the buttons to push.

i am having a bad day and the examples really cheered me up