161–170 of 261 posts
I'm honestly surprised that they even had the inclination to attempt creating a model. I guess it's bullish that a municipal IT department had the guts to try this?
I like the [dead] comment theory that they proposed a huge LLM training budget to the government, kept most of the money, and released a cheap merge to justify the grift.
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Lying about model capability is right now the lingua franca of the cloud AI business model, almost; they yes-and each other's lies because they are in a position of needing to generate interest, including going as far as needing to trigger regulatory capture. (It's not news to anyone who has worked in sales-led businesses that salespeople are prone to believing the claims of other salespeople, I guess).
> Lying about model capability is right now the lingua franca of the cloud AI business model Lying about your lab's capabilities != Lying about model capability Exaggerating the capabilities of a new model that you've actually trained in press bulletins can be called marketing. Merging two models and claiming that you trained a new model is plain lazy.
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I'm honestly impressed that this even happened at all. "Rio de Janeiro's homegrown LLM" is probably the last headline I ever expected to read on HN.
Worth reminding everyone that Lua was also created in Rio, though admittedly at PUC rather than by the government. Rio has a strong engineering talent pool, along with many other major capitals in Brazil
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I'm honestly impressed that this even happened at all. "Rio de Janeiro's homegrown LLM" is probably the last headline I ever expected to read on HN.
Worth reminding everyone that Lua was also created in Rio, though admittedly at PUC rather than by the government. Rio has a strong engineering talent pool, along with many other major capitals in Brazil
What Brazil doesn't have is a history of properly rewarding talent, which often causes it to migrate elsewhere. So it's definitely surprising when any sort of technological development happens in Brazil: it implies someone who stayed managed to get something done, most likely for much less than what that something is actually worth, while also being crushed by extremely high taxes that essentially doubles the cost of computer hardware.
This is fascinating that it worked though. Can we just merge all the open weight models and get something better?
It's absolutely insane to me that we are now at a point where the top of the front page of hacker news is a random GitHub issue about attribution to some random LLM merge, written in just the most disgusting AI slop style. I would like to downvote this please.
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I don't think your last point is correct. Ablation, when done correctly, seems to increase the quality and typically also the performance too.
Abliterarion is a brute force technique that removes or silences parts of the model. It reduces performance because the abliterated elements aren’t perfectly isolated to censorship so other aspects suffer. Many of the “uncensored” model providers also do some fine tuning on the models. Some of them target better benchmarks or other measures, but outside of the benchmarks and metrics they’re fine tuned for they are ge…
I have no affiliation with them but here's what I think happened: 1. They claim the official model is based on Qwen 397B. It's likely they didn't disclose Nex Pro at all because Nex itself is based on the same base model (not saying they shouldn't). 2. The improvement would come from merging the weights PLUS on-policy distillation. The confusion is that the uploaded model didn't have the distillation at all. 3. It's…