nomad_horse

4 ms·

1.
by nomad_horse 1y ago
> Voxtral outperforms Whisper Can I stop you right here? Whisper is a few years old and it wasn't the best model for a long time. There are like 10 models that are smaller and faster and outperform both of them. And these models exi
2.
by nomad_horse 1y ago
Whisper has the encoder-decoder architecture, so it's hard to run streaming efficiently, though whisper-streaming is a thing. https://kyutai.org/next/stt is natively streaming STT.
3.
by nomad_horse 1y ago
Do you know if OpenAI used the same grading criteria as official judges?
4.
by nomad_horse 1y ago
isn't he an IOI medalist? and even if he was an IMO medalist, isn't there a bit of a conflict of interests?
5.
by nomad_horse 1y ago
Do I understand it correctly that OpenAI self-proclaimed that they got their gold, without the official IMO judges grading their solutions?
6.
by nomad_horse 1y ago
There are larger models in there, a 8B and a 6B. By this logic they should be above 2B model, yet we don't see this. That's why we have open standard benchmarks, to measure this directly - not hypothesize by the models' sizes
7.
by nomad_horse 1y ago
> brought back competitive open source audio transcription Bear in mind that there are a lot of very strong _open_ STT models that Mistral's press-release didn't bother to compare to, making impression they are the best new op
8.
by nomad_horse 2y ago
I assure you, before the LLM race, those research shops (DM, FAIR) had many directors that didn't contribute to any product whatsoever.
9.
by nomad_horse 2y ago
Yet your Google Research colleagues still earned way more than in academia, even without the promo. Plus, there were quite a few places where a good publication stream did earn a promotion, without any company/business impact. FAIR, Go
10.
by nomad_horse 2y ago
Those are likely for Cloud, used by clients.
11.
by nomad_horse 2y ago
FAIR is considerably downscaled from what it was before, in eg 2022.
12.
by nomad_horse 3y ago
I think all FAIR researchers and engineers are aware of the NC-CA license limitations. They still use it because releasing the code for an already approved paper under NC-CA is super easy (~ self-approving by clicking a few buttons) vs foll