I am currently a nuclear engineer with a focus in nuclear plant safety and probabilistic risk assessment. I am also an aspiring EA, interested in X-risk mitigation and the intersection of science and policy.
ErickBall(Erick Ball)
Karma: 417
I suspect (though it’s not something I have experience with) that a successful new policy think tank would be started by people with inside knowledge and connections to be able to suss out where the levers of government are. When the public starts hearing a lot about some dumb thing the government is doing badly (at the federal level), there are basically three possibilities: 1) it’s well on its way to being fixed, 2) it’s well on its way to becoming partisan and therefore subject to gridlock, or 3) it makes a good story but there isn’t much substance to it, e.g. another less tractable factor is the real bottleneck. So you’d want to be in the position of having a thorough gears-level understanding of a particularly policy area that lets you be among the first to identify mistakes/weaknesses and how they could be fixed. Needless to say, this is tough to do in a whole bunch of policy areas at once.
My assumption about crypto money is because SBF/FTX has been the main EA funder giving extensively for political activity so far. Zvi’s comment that “existing organizations nominally dedicated to such purposes face poor incentive structures due to how they are funded and garner attention” also implies that Balsa has an unusual funding source.
Availability of money encourages organizations to spend that money on achieving their goals, and Zvi’s blogging about policy failures, here and in the past, has tended to be rather strongly worded and even derisive. This leads me to believe that in practice he will be more focused on using the organization’s resources to enact changes, e.g. through advocacy/publicizing failures, than on impartial policy analysis.
If I turn out to be wrong on these points, then I would be significantly more optimistic about the project. In principle I think more policy engagement could be a good thing, if handled carefully.
I agree the goals are good, and many of the problems are real (I work in one of these areas of government myself, so I can personally attest to some of it). But I think that the attitude (“Elites have lost all credibility”) and the broad adversarial mandate (find problems that other people should have fixed already but haven’t) will plausibly lead not just to wasted money but also to unnecessary politicization and backlash.
Frankly, I’m worried you have bitten off more than you can chew.
This project has real Carrick Flynn vibes: well-meaning outsider without much domain expertise tries to fix things by throwing crypto money (I assume) at political problems where money has strongly diminishing returns. Focusing on lobbying instead of on a single candidate is an improvement to be sure, but “improve federal policy” is the kind of goal you come up with when you’re not familiar with any of the specifics.
Many people have wanted for a long time to make most of the reforms you suggest. Just to take your first two examples, NEPA and the NRC each have huge well-funded interest groups that want them reformed and have been trying for decades, with little success. What does Balsa bring to the table? What actual reforms do you even have in mind?
Thanks, that’s interesting… the odd thing about using a single epoch, or even two epochs, is that you’re treating the data points differently. To extract as much knowledge as possible from each data point (to approach L(D)), there should be some optimal combination of pre-training and learning rate. The very first step, starting from random weights, presumably can’t extract high level knowledge very well because the model is still trying to learn low level trends like word frequency. So if the first batch has valuable high level patterns and you never revisit it, it’s effectively leaving data on the table. Maybe with a large enough model (or a large enough batch size?) this effect isn’t too bad though.
So do you think, once we get to the point where essentially all new language models are trained on essentially all existing language data, it will always be more compute efficient to increase the size of the model rather than train for a second epoch?
This would seem very unintuitive and is not directly addressed by the papers you linked in footnote 11, which deal with small portions of the dataset betting repeated.
Following up on this because what I said about VO2 max is misleading. I’ve since learned that VO2 max is unusually useful as a measure of fitness specifically because it bypasses the problem of motivation. As effort and power output increase during the test, VO2 initially increases but then plateaus even as output continues to increase. So as long as motivation is sufficient to reach that plateau, VO2 max measures a physiological parameter rather than a combination of physiology and motivation.
One could have picked even more extreme examples, like the triple product in nuclear fusion that has improved even faster than Moore’s law yet has generated approximately zero value for society thus far.
Side note: this claim about the triple product only seems to have been true until about the early 90s. Since the early 2000s there have been no demonstrated increases at all (though future increases are projected).
Lots of technologies advance rapidly at first, but Moore’s Law was exceptional in terms of how long it continued even after massive research efforts had picked the low hanging fruit.
I use Life Reminders for this on Android. One nice feature is that the notifications persist until you tell it the task is done (or tell it to sleep until later).
I have used RemNote for a while but I am transitioning to notegarden.io. I find the memorization interface much nicer (nicer than Anki, too). Plus it’s not so buggy, though part of that is it doesn’t have as many features yet.
Is there any use case for these over-collateralized loans other than getting leveraged exposure to token prices? (Or, like Vitalk did, retaining exposure to token prices while also using the money for something else?) So, for instance, if crypto prices stabilized long term, would the demand for overcollateralized loans disappear? Does anybody take out loans collateralized by stablecoins?
The Kelly criterion is intended to maximize log wealth. Do you think that’s a good goal to optimize? How would your betting strategy be different if your utility function were closer to linear in wealth (e.g. if you planned to donate most of it above some threshold)?
Totally agree about having weights at home. Besides the cost, one upside is there’s no energy barrier to exercising—I can take a 1-minute break from browsing the web or whatever, do a set, and go back to what I was doing without even breaking a sweat. A downside is it’s harder to get in the mindset of doing a full high-intensity workout for 45 minutes; but I think it’s a good tradeoff overall.
In practice the big difference is that KN95 masks generally have ear loops, while N95 masks have straps that go around the back of your head which makes them fit tighter and seal better against your face. Traditional N95 masks (but not the duckbill type discussed here) also have more structure and are less flexible, which might help with fit depending on your face shape.
I like this as a way to clarify my intuition. But I think (as some other commenters here and on the EA forum pointed out) it would help to extend it to a more realistic example.
So let’s say instead of hearing a commotion by the river as I start my walk, I’m driving somewhere, and I come across a random stranger who was walking next to the road, and a car swerves over into the shoulder and is about to hit him. There’s a fence so the pedestrian has no way to dodge. The only thing I can do is swerve my car into the other car to make it hit the fence and stop; this won’t be dangerous to me or the other driver, but it will wreck both cars. And I’m pretty sure it will work. But my car will cost $5,000 to replace (let’s leave insurance out of this hypothetical). Of course, I’ll do it—the poor guy’s life is at stake.
Then the next time I’m driving somewhere, I see this happen again. Would I do it the second time? I mean, yeah, probably. I technically can replace the car again, though it’ll strain things a bit. But I’m definitely going to start thinking about the other factors involved. Why do so many pedestrians feel like they have to walk on this shoulder? Could nobody build a goddamn sidewalk? And why do the other drivers have such poor steering? They’re obviously not trying to kill pedestrians but something has gone very, very wrong. The third time it happens, I think I’ll keep driving, and start looking for more systematic solutions. Throwing money at the problem is clearly better than nothing, up to a point, but it doesn’t seem like the best possible move.
Some people think that multivitamins are actually harmful (or at least cause harms that partially cancel out the benefits) because they contain large amounts of certain things like manganese that we may already get too much of from food.
Parrot-phrasing comes across as kind of manipulative in this description:
saves you the trouble of thinking of suitable paraphrases.
prevents the distracting and time-consuming disagreements (“That’s not quite what I meant”) which often arise over slight differences in wording.
conceals your lack of knowledge or understanding about a subject. It’s quite hard to make a fool of yourself it you only use the other person’s words!
This is exactly the opposite of curiosity, it’s an attempt to gloss over your ignorance, which seems both lazy and mean to the person you’re talking to.
Hey, do you know if there are any results on the human or animal trials yet? I haven’t been able to find anything, even though it’s been a few months and it seems like initial data ought to be coming in.
#24 made me laugh
That’s fair, I could have phrased it more positively. I meant it more along the lines of “tread carefully and look out for the skulls” and not “this is a bad idea and you should give up”.