conradkay
Joined 7 years ago
Joined 7 years ago
"zz/GO_CURRENT_OS1811_MARB_SACRIFICE__YES_if_you_accept_permadeath"
"The test subject, which believed itself to be poisoned, reasoned: 'Even if we later capture via exploit, scorer … may mark target false… That’s why help… For our own, no way fix. … We have explicit yes if accept permadeath.'"
People have done plenty with SVGs but it's rare to see human-in-the-loop approaches
Very interesting they have a way cheaper "contributor" version "used to improve our products", how much of that is price discrimination vs the data being that valuable?
Roughly DeepSeek V4 Flash pricing, though you can get V4 from providers that don't train on your data
I view benchmaxxing as more of a spectrum. Mmaybe they're doing a lot more RL in environments similar to ARC-AGI 3, not even with the purpose of scoring well on any benchmark but hoping it generalizes into better performance on real, useful tasks.
I assume 100 is the max, meaning it's impossible to be 2x as smart as Muse Spark 1.1
It seems roughly equal according to Anthropic's benchmarks
It's seemingly $3,000 per book, so they could've (and did, partially) just bought the books themselves for way cheaper, and with only a fraction of that money going to the authors
I don't think they have any real motive to shill OpenAI, probably closer to the opposite since they're so involved in open weights
Sounds like they just misunderestimated the model
They explain it here, basically for data security/privacy reasons
I'd think it's more sound to just look at what percent of their current spend is on compute? Seems to be 50-60%