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>Also the "Palestine" side of the warrants are against Hamas which also feels weird (Hamas is also not a signatory nation and many suggest that Hamas != Palestine).

The ICC prosecutes individuals not states, so there's no contradiction here.

>Given Palestine is a signatory does it mean they have to take action to extradite the Hamas leadership to face trial?

Yes

>What consequences do they face if they fail to do that?

There's no penalties built into the statute. It tends to have diplomatic blowback. See [1] for a prior example.

[1]: https://press.un.org/en/2018/sc13623.doc.htm


I'd answer this from two perspectives.

As a forecaster: It's fun! It's an interesting way to learn about the world -- rather than gathering inert facts, you're forced to integrate them into a mental model, and then your model is tested for its validity empirically. It's also difficult and competitive, if you like that sort of thing.

As a consumer of forecasts: There's good research that prediction markets and other forecast aggregators are the best technology we have as a society for quantifying uncertainty. Not everyone will listen to them, just like not everyone eats their veggies, but c'est la vie.

I don't think there's too much risk of self-defeating forecasts (where a low forecast lulls decision makers into a false sense of security) - at least not yet. They're still pretty niche.


I think the article focused on base rates because they're a relatively unusual and legible "trick" to coming up with a forecast, but really they're only one element of a forecast; typically a forecaster will think about many different ways to "attack" a question and synthesize them (somehow!). Choice of denominator for your base rate is very important also and can radically change the answer you get.

The sites which host these forecasting competitions correct for the bias against rare events through what's called "proper scoring" rules -- there's some specific maths to it, but the short version is that you're exponentially rewarded for being a correct contrarian and exponentially punished for being confidently wrong.

There are limits to that too, of course -- the folks in the article will "only" have made on the order of mid hundreds to low thousands of predictions, so roughly speaking, you can expect these people to be calibrated for 1% or 0.5% odds but probably not 0.1% odds.


Base rates work pretty well, at least for all cause mortality... hurricane counts per year, and financial markets (over very short time periods). I was using the Good Judgment project as motivation to practice R programming for a while, until one day I saw that literally EVERY person forecasting the ending value of the Hang Seng index tied to my probabilities. Therefore, EVERYONE was calculating base cases from historical market data and entering those results.


Yes, serious forecasters predict on hundreds of questions & the relevant websites prominently feature "binary calibration" plots.

This is mine on Metaculus (mentioned in the article):

https://imgur.com/a/d3s67xk

There's still a bit of noise at 205 predictions but you can see a pattern emerging!


But if you can pick what you’re predicting on and pick the percentage you assign to an event, I fail to see how that gives you a calibration.


Because you make lots of predictions, and smooth out the numbers. If the events you give 8% probability actually happen 35% of the time, you aren't as calibrated as you are if they happen 10% or 5% of the time. The calibration numbers measure how much you are off by.


This makes no sense. If I have 1000 predictions and vary my estimates from 0-10%, that’s only 100 samples assuming you round to the nearest whole percent. And there’s no correlation between any of those samples. For example, I could say the probability of a lightning storm tomorrow is 1% and the probability of a war with China in the next year is 1% - calibrating amount those 1% events is clearly non sensical. You could try to calibrate among similar events but then you have no way of estimating that a 10% war between US and China vs a 1% of war between Russia and China.

Basically this is an exercise of garbage in and garbage out.


I think youre kind of right, its not really meaningful to know “im right about things that happen 5% of the time!”. But if a lot of things you bet on structurally happen to be low probability and of the same type (eg you bet on one type of catastrophic event like pandemic, crop disease, or war etc) then its useful


Or you’ve just learned how to optimize your score on the game you’re playing but the game isn’t actually about predicting the future.


Proper scoring rules like Brier mean that any attempt to optimize your score by definition mean that you are improving your calibration.


I don't have any knowledge of IFTTT's budget, but the truth value depends on the exact framing of cost.

Your framing is "the marginal cost of any given request rounds to zero" which is probably true.

Another likely true framing is "there are substantial numbers of users on legacy plans who in aggregate cost more to serve than they pay".


$26 billion (Q4 2022 through Q3 2023)


The primary goal of most large organisations' dev blog is to attract potential candidates to the top of the recruitment funnel.

This picture appears to be (presumably) the actual team doing a team building activity.

This is both a reasonable choice given the inferred instrumental goals of the blog, and a honest reflection of (one part of) the team life, assuming it's a photo of the real team.



I've just learned, the term of art for energy cost factoring in labor, infrastructure, replacement, etc is "levelized cost" or LCOE and by that metric utility solar is indeed already cheaper than fossil fuels and nuclear power:

https://www.lazard.com/media/2ozoovyg/lazards-lcoeplus-april...

It looks like utility solar is currently ~33% the LCOE price per kwh of nuclear or 85% of the price of gas (CCGT).

This is an increase relative to 2021 (20% of nuclear / 60% of gas)

(As I understand it, the cost increase between 2021 and 2023 is from cost of capital and shipping)

Naively projecting out the LCOE trajectory, it indeed does not look like it's going to get to be 'dirt cheap' soon - eyeballing, the LCOE curve over time appears to be flattening towards a 5% or smaller cost reduction year over year.


how: ice cores (I don't know the answer re: 1600s)


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