Vitalik Buterin: “...But currently, I see zero plans for how to deal with an ASI transition that are not naive. Perhaps humanity is stuck with a choice between naive and naive squared (or maybe even naive squared and…
Interesting. But if you are upgrading your embedding model, wouldn't you want to re-embed to get its benefits on old entries?
Very nice! How did you implement your rain effect?
Nice. So is the js/lean interface using exact rationals?
Is the web demo compiled from the lean?
Have you tried just using a faster tokenization library? Github's BPE crate (https://crates.io/crates/bpe) advertises >10x speedup relative to HF, as do others.
"Writing the question WAS the lesson" Indeed!
This seems exactly right. Its pretty common to watch your agent making the same mcp tool call again and again as it works through a list. These kinds of cases are solved by letting the agent just call any of its mcp…
Vitalik Buterin: “...But currently, I see zero plans for how to deal with an ASI transition that are not naive. Perhaps humanity is stuck with a choice between naive and naive squared (or maybe even naive squared and…
Interesting. But if you are upgrading your embedding model, wouldn't you want to re-embed to get its benefits on old entries?
Very nice! How did you implement your rain effect?
Nice. So is the js/lean interface using exact rationals?
Is the web demo compiled from the lean?
Have you tried just using a faster tokenization library? Github's BPE crate (https://crates.io/crates/bpe) advertises >10x speedup relative to HF, as do others.
"Writing the question WAS the lesson" Indeed!
This seems exactly right. Its pretty common to watch your agent making the same mcp tool call again and again as it works through a list. These kinds of cases are solved by letting the agent just call any of its mcp…