ardata

5 ms·

1. 1.▲
   by ardata 10mo ago

   risk? certainty. it's pretty much guaranteed. the most capable models are already behind closed doors for gov/military use and that's not ever changing. the public versions are always going to be several steps behind whatever
2. 2.▲
   by ardata 10mo ago

   for backtesting trading strategies this could be useful... i've had sims give different results across machines and never knew if it was real or fp drift. how is the performance on real-world sized datasets?
3. 3.▲
   by ardata 10mo ago

   I've built trading bots that run monte carlo sims on historical data... numpy works but gets slow on large backtests, and pytorch feels like overkill when I just want fast array math without managing GPU memory. If this can drop in and
4. 4.▲
   by ardata 10mo ago

   Does the guess cache sync across machines at all, or is it purely local? I jump between my laptop and desktop for AoC and it'd be annoying to resubmit a 'too low' answer I already tried elsewhere.
5. 5.▲
   by ardata 10mo ago

   Ran clean for me: === Prima Veritas OSS — Hash Check (iris) === normalized → MATCH Expected: EF28EA082C882A3F9379A57E05C929D76E98899E151A6746B07D8D899644372F Actual: EF28EA082C882A3F9379A57E05C929D76E98899E151A6746B07D8D899644372F