@tshevl@Polymarket@Kalshi@_Mantic_AI METR is the wrong analogy, the markets themselves are rapidly becoming more accurate because these very systems are trading on them. Mantic is approximately level with FutureSearch which is a public API, as long as that's true it can't reach $1M volume accuracy.
@patrykperduta Hey, I want to publish a short rhythm game with this as the audio track, of course linking to your YT and crediting you. Is that OK with you?
Astra doesn't beat Fable 5.1 on code or forecasting (the things actually important for RSI), the reason the benchmarks feel that way is that any release includes only the winning benchmarks
I have a genuine question.
Anthropic has probably been working on Fable 5.1 for a very long time. OpenAI has probably been working on GPT-6 Astra for just as long. These labs are almost certainly building in parallel, not reacting to each other in real time of course.
So why does Fable 5.1 launch just a couple of days before Astra, and then Astra beats it on almost every benchmark by a good margin?
And this isn't a one-off.
Every single launch follows the same pattern: when Anthropic ships a new model, it beats all of OpenAI's previous models.
When OpenAI ships a new model, it beats all of Anthropic's previous models. Now they are actually beating what the other just launched days earlier.
Benchmarks are completely vanity metrics.
@scaling01 this is a different sort of sacrifice vs what you seem to be describing in your quote, not sacrificing short term gain for long term gain, but sacrificing your own utility for another's
@timfduffy I doubt they are doing this in practice, they are scaring people away from using Claude for frontier work by simply suggesting silent sabotage as a possibility
@LatosLouis@dwarkesh_sp You can implement backpropogation as a local operation, the gradient at each node depends only on the gradients of the node it is connected to in the next layer (i.e. has non zero weight toward)