Retrospective: I found this particularly helpful
Watch podcast interviews. Pay attention to how the host asks questions.
Retrospective: I found this particularly helpful
The best way to sound smart is to spend hours preparing something and present it as if you made it up on the spot. Really smart people will have a ton of prepared phrases, so many that they can talk on a wide variety of topics by saying something they already know how to say and just modifying it a little.
I think you can 80/20 all this stuff by being "moderately active" instead of "an athlete".
Average BMI in the United States increased from 25.2 in 1975 to 28.9 in 2014, so a 3 point increase. Compare an average 1975 person with an average 2014 person. It's far more likely that the 3 point increase is due to overeating, rather than other explanations like packing on muscle (3 whole points of muscle is a lot) or variation in bone mass (this is likely negligible). Overeating is the path of least resistance in wealthy Western countries. So yes, technically BMI is not the same thing as fatness, but they are highly correlated.
Also as Rockenots points out, the direction of your height claim is going in the wrong way. BMI is an underestimate for fatness for very tall people. For example, a healthy weight 6'2" man's BMI might be 17 or 18, which according to the standard BMI scale is underweight. That's why measures like better BMI exist.
AI capabilities are advancing rapidly. It's deeply concerning that individual actors can plan and execute experiments like "give a LLM access to a terminal and/or the internet". However I need to remember it's not worth spending my time worrying about this stuff. When I worry about this stuff, I'm not doing anything useful for AI Safety, I am just worrying. This is not a useful way to spend my time. Instead it is more constructive to avoid these thoughts and focus on completing projects I believe are impactful.
Wow thanks for sharing. I might steal the NFC / walk scheduling ideas -- those sound like they could be useful.
Long shot but you haven't happened to figure out how to get Tasker to interface with "Focus Mode" have you? That's one thing I haven't managed to get Tasker to detect yet.
"Don't make us look bad" is a powerful coordination problem which can have negative effects on a movement. Examples:
And that’s -- coordination's a very hard thing to do. People have very
strong incentives to defect. If you're an activist going out and saying a very
controversial thing, putting it out there in the most controversial, least
favorable light so that you get a lot of negative attention. That's mostly
good for you. That's how you get attention. It helps your career. It's how
you get foundation money. [...]
And we really noticed that all of these campaigns, other than, I guess, Joe
Biden, were embracing these really unpopular things. Not just stuff around
immigration, but something like half the candidates who ran for president
endorsed reparations, which would have been unthinkable, it would have
been like a subject of a joke four years ago. And so we were trying to figure
out, why did that happen? [...]
But we went and we tested these things. It turns out these unpopular
issues were also bad in the primary. The median primary voter is like 58
years old. Probably the modal primary voter is a 58-year-old black woman.
And they're not super interested in a lot of these radical sweeping policies
that are out there.
And so the question was, “Why was this happening?” I think the answer
was that there was this pipeline of pushing out something that was
controversial and getting a ton of attention on Twitter. The people who
work at news stations -- because old people watch a lot of TV -- read
Twitter, because the people who run MSNBC are all 28-year-olds. And
then that leads to bookings.
And so that was the strategy that was going on. And it just shows that
there are these incredible incentives to defect.
One takeaway: a moderate democrat like Joe Biden suffers because the crazier looking democrats like AOC are "making him look bad", even if his and AOC's goals are largely aligned. I can only assume that the republican party faces similar issues (not discussed in this podcast episode though)
Are there more examples of "don't make us look bad" coordination problems like these? Any examples of overcoming this pressure and succeeding as a movement?
How much to extreme people harm movements? What affects this?
This seems interesting and important.
This is a good point concerning current gait recognition technology. However, I don't doubt it will improve. On longer timescales, this should happen naturally as compute gets cheaper and more data gets collected. On shorter timescales, this can be accelerated using techniques such as synthetic data generation.
Perhaps there is a natural limit to gait recognition, if it turns out that people can't be uniquely identified from their gait, even in the limit of perfect data. But if there isn't, then in 10 years, "94%" will turn into "99.999%", or whatever is needed for gait recognition to be worth thinking about.
In this situation (and in the situation where I leave my phone at home), this question becomes relevant again.
I could see the spotlight being unpleasant because the brightness differences might cause eye strain, unless the light is really perfectly placed. Sunlight (or even shade) seems much better in this regard. Interesting idea though—I'm surprised how affordable that spotlight is.
Retrospective: This comment was helpful
Haven't done the "record yourself" part but I have since started deliberately practicing explaining particular concepts. Typically I will practice it 5 times in a row, and after each time think carefully about what went well/poorly. Multiple comments suggested practice but I think this one resonated with me best (even though I'm not into focusing stuff)