My wife was working in a BSL-3 facility with COVID and other viruses that were causing serious health issues in humans and were relatively easy to spread. This is the type of lab where you wear positive pressure suits.
To have access to such a facility, you need to take training in safety measures, which takes about a month, and successfully pass the exam - only after that can you enter. People who were working there, of course, were both intelligent and had master's or doctoral degrees in some field related to biology or virology.
So, in essence, we have hi...
Hello. I've created it. It's more about information processing, but useful to understand some communication-related stuff too. It's not finished because LW doesn't allow me to add more than five posts a day, but the main part is here:
https://www.lesswrong.com/s/JsGa9AHEG3EgEq45s
I think, that sharing is like testing that your Idea is good and new.
In programming, we have a concept named "Fail Fast strategy". That means, that after some mistake program should fail as fast as possible. In ideal case - not even compile. Because the far your mistake stepping by "deploy ladder" - the more it costs. If your program does not compile then you set the wrong value to some variable - you'll pay seconds for correcting. If it was found during QA tests - you'll pay for switching from your current task to this one, ...
I was experimenting with exactly the same thing using GPT-4. Only 20 top questions, result - more or less equal to community.
But then it came to numeric estimations like “how much people will die due to covid” - it was outperforming humans giving highly accurate predictions (i was asking not for values but for ranges with quartiles, and results of humans had much higher dispersion comparing to GPT)
Also I was comparing only results of community predictions for January 2022 since gpt-4 was trained on sept 2021, and its unfair to compare predictions if people had a lot of additional evidence which gpt doesnt have.
if it’s interesting I can share methodology, results and dataset.