biophysboy

Let’s go back to the good ol days when half of movies were about cowboys.

If only we had all had such principled foresight. Thank you for this great lesson.

It is not an ad account - the other reply is stupid. I am saying ad accounts deal with this crap from FB all the time. Add this instance to the pile. It is the price of surrendering comms and marketing to a gigantic behemoth.

Autobans happen to ad accounts on FB all the time.

I am 99% sure it was an automated system false positive, but it is annoying that we all have to rely on these capricious systems. That is in itself a problem with massive scale platforms. It confirms my silly hot take that all online communities should not be bigger than 10k people. That keeps the number of bad eggs legible to an actual human moderator, and keeps the discussion less mob like

Yes, and I think over time there will be a blatant inequality in who is commoditized and who isn’t.

If AI engineers didn’t create the data to produce the models, and they increasingly don’t write the code to produce the models either, then why are they treated as the agents of change rather than the subjects of change, like mathematicians are?

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I have been kind of disappointed by AI science-wise. I was anticipating more advancement. Experiments do take time, so I suppose they could be pending.

What attracted you to the field? (I’ll see myself out)

Same experience. The question "what is your most memorable experience" also kind of annoyed me, because I see AI mostly as a tool. It is like asking me what my most memorable experience with my iphone is. I'm sure I could cook up something, but it felt like they were mining users for happy PR.

People start with this prior in the examples you gave when they are completely uncertain and have no better mental model. It is not a good starting point for an event that has never happened and can only happen once.

Uninformative priors are a part of Bayesian models, which are useless if they cannot be updated with real or simulated data?

> But research has shown that people translate vague phrases like "a decent chance" into probabilities in inconsistent ways.

That is not a bad thing. It captures uncertainty, unlike the fake number.

> For an ML researcher who is already used to dealing in next-token probabilities that aren't rigorously determined, just stating a probability estimate directly is very natural.

Exactly, it is a rhetorical device to persuade a technically-inclined audience. It works because it implies that a quantitative model exists. I want a clear, incisive set of mathematical arguments. Otherwise, I’m ignoring predictions as the ramblings of arrogant idiot rich kids.