randomcatuser
Joined 4 years ago
Joined 4 years ago
if we assume the user connection is secure (ie, about as secure as banking), can we have secure internet voting?
And secondly, why would you want worse LLMs? Seems less useful that way
I'm new to networking..
The fun part is that then, the interviews can look way different than today -- e.g. the robot interviewer can demand proofs of the user's skill, etc.
It can even be confidential (ie, robot interviewer <> user's agent in a black-box room) so that they can share data
Imagine you have a function f(user_profile) -> decision
You can run f in a way that respects the user's privacy (and also hides the details of f from the user).
Companies get ~10x more data from each interviewee
Interviewees don't need to even show up
Sounds like a good deal to me!
"The mind is not a vessel to be filled, but a fire to be kindled." — Plutarch
"Education is not preparation for life; education is life itself." — John Dewey
"The important thing is not to stop questioning. Curiosity has its own reason for existing." — Albert Einstein
In order to think complex thoughts, you need to have building blocks. That's why we can think of relativity today, while nobody on Earth was able to in 1850.
May the future be even better than today!
With a traditional API, people can build it any way they want, which means you (the client) need API docs.
With MCP, you literally restrict it to 2 things: get the list of tools, and call the tool (using the schema you got above). Thus the key insight is just about: let's add 1 more endpoint that lists the APIs you have, so that robots can find it.
Example time: - Build an MCP server (equivalent of "intro to flask 101"): https://developers.cloudflare.com/agents/guides/remote-mcp-s... - Now you can add it to Claude Desktop/Cursor and see what it does - That's as far as i got lol
and do that
But searching for "voice detection with pauses", it seems there's a lot of new contenders!
https://x.com/kwindla/status/1897711929617154148
this one is a fun approach too https://x.com/zan2434/status/1753660774541849020
i'm very inclined to trust them on the various ways that models can subtly go wrong, in long-term scenarios
for example, consider using models to write email -- is it a misalignment problem if the model is just too good at writing marketing emails?? or too good at getting people to pay a spammy company?
another hot use case: biohacking. if a model is used to do really hardcore synthetic chemistry, one might not realize that it's potentially harmful until too late (ie, the human is splitting up a problem so that no guardrails are triggered)