We're on Amazon!! https://t.co/U7kHDYogIe
If anybody is curious about machine learning on graphs, check out this textbook. Lots of cool methods w fundamental linear algebra!
(trying to avoid looking at the answer or the internet for this)
This is a binomial distribution with p=0.5 and n=100
We want the sum in the p.m.f of all values greater than (but not equal to) 50.
There are a few ways to calculate. brute force would be to directly sum (n k) * .5^k * .5^(n-k) over all k > 50.
Better, you could take advantage of the fact that the binomial is symmetric. So the highest-mass bin would be at k=50.
Due to symmetry, we can say that the sum of all k from 0 to 49, plus pmf(50)/2, = 0.5
Also due to symmetry, our answer then is .5 - pmf(50)/2
So the exact answer (after some algebra) is
0.5 - ((100 choose 50) * .5^100) = approx 0.42
@fchollet But it's cloudy always (I grew up there). That being said Seattle is the best place in the country to live bar none and anybody who says otherwise is wrong.
I have experienced this. Here were some of my solutions:
a) have Claude implement papers for me, but have it lead important parts of the codebase to build by hand
b) have a personal project that I play with on weekends / downtime as largely a way to upskill
c) have Grok send me a daily papers feed summarizing what papers people are talking about on X
@wolfiesch@tszzl There probability of another independent human landing on this specific combination of words it's also ~0, and roon's probability of making the same post again if his memory were erased. So what you're saying is true but trivial
@francoisfleuret There are plenty of simple reasonable heuristics. What are the norms of all the layers? If you run activations through what is the per-layer distribution of various statistics about them? Etc
@TrueAIHound@pmddomingos@Susan16Park Domingos is correct and you are wrong. Go look at all of the good things America has done and then weigh the balance rather than cherry picking bad things.
@bennyzhu84@nikitabier Oh wow, I'm seeing it now. People talking in French, Indonesian, and Vietnamese inside this thread and everyone can understand each other. Cool!
@ArthurB@Aella_Girl I don't think that's a strong meta-argument when you consider the cultural context. LessWrong and EA discourse has been obsessively developing their arguments and counterarguments for a decade; the people arguing against usually don't care to the same degree.
Calling attention to an exciting "deception detection" hackathon we're planning this summer! w @NDIF and @CadenzaLabs.
Recruiting red teams now, blue teams later. Red teams, time is short: proposals due Mar 31. $10K stipend + compute, $15K finals prize.
https://t.co/Lzbh5ThTBT
Makes sense theoretically, but is empirically not true. The Buddhists spent around 2000 years exploring this empirically and the conclusion they came to is that you need to sit with emotions to release them. This is a very obvious truth for someone who has actually done this before.
I mean it's not strong evidence but
a) it's definitely weak evidence
b) given the above, the onus is sort of on the doomers to make a strong argument that something bad will happen when thing scale more
You can't just randomly say "the world is about to explode" with 0 empirical evidence. It's just death cult energy at that point.
Many of the doomer arguments I read also feel like they are written by people who don't actually build stuff, and therefore have no actual substantive understanding of the system they are talking about.
@tricksthatstick@eudaemonea@SecWar Or the united states could just go use another model provider instead of labeling a US company a foreign adversary because they couldn't strong-arm them into submission.