7 appearances on the backlist front page in the last 30 days.
hey isn't it kind of messed up that API customers of Opus 4.7 and Opus 4.8 are paying ~1.41x as much for general english output (when measured against a consistent tokenizer baseline) vs Opus 4.6? from THE ONLY lab that's cagey about releas
anthropic pricing docs claim: "This new tokenizer may use up to 35% more tokens for the same fixed text." my measurements claim: the average inflation appears to be higher than their ceiling. and this is... general english, not arabic or so
q: "why don't Sora-like models learn compositional physics understanding or do ICL like how language models learn compositional semantics?" a: every attempt to date heavily leaks information from the future. some even bake it into the bottl
it's very well possible that they finally invested hard in some form of context distillation (anthropic circa instructgpt era flavored or opd flavored, take your pick, latter is the hot shit right now sooo?)
fascinating. 5.5 is the only model here that doesn't seem to improve monotonically on my problem with test time compute scaling
lol i think i whipped up the simplest, dumbest agent env that a. (broadly) sorts the wheat from the chaff b. also shows you if a model has strong overthinking tendencies by default as is usual, v4 flash is busy paretomogging w.r.t the cost/
you can in fact frame this as a compression problem where a generator learns to summarize some prior sequence in such a way that minimizes the conditional distribution drift (as measured by kldiv) instead of bolting on a summary prompt post