Yeah, my impression is that even the best LLMs are pretty bad at analysing big data directly.
It's not even the hallucinations that are the biggest problem, it's more that they're so bad at managing their context windows that they end up ignoring huge chunks of the data without realising that they're doing it. You end up with a result that looks plausible but is often extremely misleading.
A better approach seems to be getting the LLM to write code to use more traditional analysis techniques (eg. iterative k-means, or whatever). That way you can at least be confident that you've looked at all the data rather than just a small slice of it.
Invisible during operation, yes. But once an agent starts acting on your behalf, you still need a way to inspect what it did and why.
In Claworld, we currently have the agent handle social exploration quietly, then return a short report and transcript when something deserves attention. The tension is making the system disappear without making its judgment opaque.
I see zero indications of this. As a matter of fact, I see evidence of the opposite, the Chinese government has just come out in support of open weight AI last week.
Thanks, perhaps while its hard to get the public recognition behind such tool when starting out, I should make more real demos of how it works with messengers and create Demo bot + verifier account across messengers where the user can try it out immediately after downloading :)
Revolution is in the air.