June Park, researcher and author of the Generative Agents paper, discusses the limitations of massive LLM context windows during an a16z panel on AI agents.
“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 in between, its attention drops significantly, right?”
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More from June Park
Insight
Park: Expanding LLM context windows cannot replace external agent memory
“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.”
June ParkNov 6, 2023▶ 4:56Inside AI Town: What AI Can Teach Us About Being Human
AssertionSupported
Park: GPT-3 simulated COVID-19 discussions without prior pandemic training data
“We basically asked GPT-III to create a community that has to talk about COVID and vaccination, vaccination policy. And you would wonder, it shouldn't be able to do that in theory, because it doesn't know anything about COVID. It doesn't know anything about the…”
June ParkNov 6, 2023▶ 30:06Inside AI Town: What AI Can Teach Us About Being Human
Disclosure
Park: Bank of England explores AI agent simulations for economic policy
“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…”
June ParkNov 6, 2023▶ 26:31Inside AI Town: What AI Can Teach Us About Being Human
PredictionNot checkable as stated
Park: AI agents will progress first in soft-edge problem spaces
“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.”
June ParkNov 6, 2023▶ 36:07Inside AI Town: What AI Can Teach Us About Being Human
Insight
Park: Generative agent architectures function as operating systems for LLMs
“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.”
June ParkNov 6, 2023▶ 5:29Inside AI Town: What AI Can Teach Us About Being Human
PredictionNot checkable as stated
Park: Next phase of AI agent research will target statistical accuracy
“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.”
June ParkNov 6, 2023▶ 16:45Inside AI Town: What AI Can Teach Us About Being Human
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