June Park

“My bet, it's a bit of a hot take, is my bet is in the early days of agent development, I think we'll see a lot of progress that's going to be made first in sort of the soft edge problem spaces.”

“I think ultimately getting to that degree of accuracy in the simulation might be sort of the next step to these kind of simulation-based work.”

“Larger context window does confuse models, right? So we, some of my colleagues are actually doing more rigorous studies on this, where You can have a really long prompt, but model really focuses on the first few lines and the last few lines, and whatever comes…”

“Philosophically, to some extent, I think this is akin to creating the operating system around learned language model in the way we sort of, we are prompting learned language model.”

“For instance, if you're, in fact, some of the places that I'm visiting now are More places like banks, like the Bank of England and so forth, where these places, they need to test their policies before they run roll out new comic policies, or many of my collea…”

“And even if that limitation were to go away in the future, processing a lot of really long-term context window is really inefficient and also ineffective when you're trying to prompt these models for a really narrowly defined behavioral assets.”