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Effective Altruism charity maximizes impact per dollar by creating an interactive prophecy for the arrival of the singularity (https://www.reddit.com/r/SneerClub/comments/142qq9p/effective_altruism_charity_maximizes_impact_per/)
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EpochAI is an Effective Altruism charity funded by Open Philanthropy. Like all EA orgs their goal is to maximize quantifiable positive impact on humanity per charitable dollar spent.

Some of their notable quantified impacts include

Epoch received .96 million in funding from Open Philanthropy. That’s equivalent to the lifetime income of roughly 20 people in Uganda. Epoch got 350k Twitter impressions, and 350k is four orders of magnitude greater than 20, so this illustrates just how efficient EAs can be with charitable funding.

Epoch’s latest project is an interactive prophecy for the arrival time of the singularity. This prophecy incorporates the latest advances in Bayesian eschatology and includes 12 user-adjustable input parameters.

Epoch’s prophecy model for the arrival time of the singularity

Of these parameters, 6 have their default values set by the authors’ guesswork or by an “internal poll” at Epoch. This gives their model an impressive estimated 0.5 MITFUC (Made It The Fuck Up Coefficient), which far exceeds the usual standards in rationalist prophecy work (1.0 MITFUC).

The remainder of the parameters use previously-published trends about compute power and costs for vision and language ML models. These are combined using arbitrary probability distributions to develop a prediction for when computers will ascend to godhood.

Epoch is currently asking for .64 million in additional funding. This is equivalent to the lifetime incomes of about 25 currently-living Ugandans, whereas singularity prophecies could save 100 trillion hypothetical human lives from the evil robot god, once again demonstrating the incredible efficiency of the EA approach to charity.

[edited to update inaccurate estimates about lifetime incomes in Uganda, fix link errors]

So they got .96M already – that’s probably like 6 full time staff at most? Do you know how many rationalists that would torture if it was given directly to me?

Literally none of these are net positive “charities” in any way other than providing “jobs” to tech-space failures who are (personally) vastly overpaid already. You’ve missed this from dividing by Ugandan life-worths, of course, instead of annual income of “working” on “AI processing of surgical videos”.

Aside: If there is anything I trust an LLM to do, it’s surgery.

You mean rationalist godmen who deserve every penny they get because of their superior wikipedia education genetics? They’re practically working class you know.
Thats where this went for me too, but thinking here too long (minutes) always makes me want to effectively drill altru my skull. They are working class, only made to pretend to be elite by the eternal crippling of the K-12 system. Computer literacy is modern literacy, and pretending actual working people **couldn't** code is frankly abhorrent.
I'm a progammer on £120k, and I could teach anyone to do my job in like a month of training. The worst part is they only look for those with a degree in the relavent fields but honestly I was a better programmer before university than after. The worst part is that you wouldn't even have to pay people that much to switch jobs, the benifits of WFH, no manual labour, and let's be honest, an easier job are more than enough reasons to switch. Like I deserve to be paid less than nurses & teachers, my job is easier and requires less skills and knowledge.
Do grifting dilettantes count as working class? Is grifting labor?
I mean in Marxist analysis criminals are usually part of the underclass or lumpenproletariat, but I don't know that grifters fall into that category since their class interest lies in maximizing the amount of money their marks can give them. Said marks are usually capitalists or petite bourgoisie since the most basic grift involves convincing investors to make bad investments and running away with the dough. That would generally make them members of the petite bourgoisie themselves I think, but if you're not actively seeking grants and are working at one of these grift hubs for a wage then I guess that counts as wage labor? Except the product of your labor is rich capitalists feeling better about themselves?
A working class person actually depends on working for a wage, various skilled professionals (i.e. programmer) meanwhile can go into small business or whatever very easily. It's a meaningfully different situation and is why the distinction was made originally.
Thats my point: These are working class people pretending to be something else because of a contemporary fluke. Industry has figured it out, and the pandemic made a huge dent in the anomaly; just salespeople filling out forms, so to say.
Can you elaborate on how the pandemic affected things?
The artificial scarcity of "people capable of typing series of characters into a terminal" ended, or was made to end, by one of the largest and widest recruitment efforts of all time. The snap back was seen with the "post" pandemic layoffs of hundreds of thousands. Industry has learned what another commenter said: there is nothing inherently special about humans who can ~~read~~ code, and you don't need to spend 200K each to teach humans to ~~write~~ code, either.
They know that last point. Many of them were only rabidly Trump to protect their own jobs. Some of them even went back to pretending to be leftist after that lol.

Epoch received .96 million in funding from Open Philanthropy. That’s equivalent to the lifetime income of roughly 3 people in Uganda.

Paywalled and I’m too lazy to get around it, but this is a ludicrously bad estimate. Your typical Ugandan makes less than 200 USD a month. That’s 20 people’s lifetime income if you assume they’re earning that for 40 years.

Typically this kind of systematic bias comes when the stats website collects data from glassdoor or another western jobs board, which in a third world country will list the very “tip of the iceberg”, the kinds of jobs which pay 10 times the average salary.

Thanks great note, I've updated the figures. I thought the number seemed low but I didn't think to question Statista...
oh god always question Statista, it's a toilet

The remainder of the parameters use previously-published trends about compute power and costs for vision and language ML models. These are combined using arbitrary probability distributions to develop a prediction for when computers will ascend to godhood.

This discourse around “scaling laws”, as something of more than ephemeral technical relevance is hilarious btw, cuz in industry its understood by everyone for obvious reasons that they are invalidated by modelling progress.

Want a simple example of what I mean? Convolutional networks work for images cuz of a very strong prior (convolution) that fits the actual distribution of image data.

If in some world everyone was using fully-connected neural networks for images and having some ludicrous expense as the image resolution grows, that is now your “scaling law”.

But now someone invents convolutions – and the new situation will not just be “all our models are more efficient”, it will be an asymptotically slower growth of compute needed – cuz of ur innovation of convolving.

In the same way, new network architectures with good robust priors for i.e. language modelling or reasoning means wow now all your “scaling laws”, are invalidated cuz we don’t use that kind of model anymore.

This is actually an example of the way these people misunderstand the "bitter pill" btw -- the whole point why people work on new models, losses, training algorithms, etc etc is cuz our knowledge indicates its i.e. a prior which probs matches what we're tryna learn. If training compute and training data are infinite then k-nearest neighbours is the universal approximator -- but it isn't and people work within the constraints they have. The actual lesson of the bitter pill is just that the compute and data you have access to in some problem domains can increase over time -- and in that case the most effective solution might change. Just let's not pretend today's vision and language models have simple priors that don't involve problem-domain knowledge -- Just the idea that "a transformer could model language pretty well!" Is a counterexample.
[Three of their model parameters](https://epochai.org/blog/direct-approach-interactive-model#algorithmic-progress) are used to try to account for this, two of which are ~~completely made up~~ determined by an internal company poll.
I can, of course, perfectly predict future technological progress from past technological progress in a field that took off 20 years ago and regarding technology invented in 2017.
Can you explain this in simpler terms? I kind of understand it but some parts don't make sense to me

I think these people have inadvertently created a really interesting cultural moment with all the AI millenarianism stuff. Will be fun to look at in a couple years

fantastic to see Make A Wish still being a more efficient charity than EA’s little favourites

I found a beta chart for the next iteration of the prophecy:

https://imgur.com/EsPs6x5