FYI you can edit your original comment to add this in.
Cautiously considering taking chanca piedra as a prophylactic yourself (especially if there is a history of kidney stones in your family) or as an acute treatment if you already have kidney stones.
Have you guys thought about what the optimal dosing protocol might be based on current research for use as a prophylactic? Daily for one month per year?Really cool post, thanks!
Part A Estimating the Impact of Donating 10% of My Lifetime Income
I’ve always been fascinated by the idea that a single decision, like where to donate money, could have an impact that stretches across communities and even generations. If I were to donate 10% of my lifetime income, say $100,000, I’d want to ensure it goes somewhere it can do the most good. I explored three top charities recommended by GiveWell the Against Malaria Foundation (AMF), Malaria Consortium, and Helen Keller International. And here is what i would go for.
Against Malaria Foundation (AMF)
AMF distributes insecticide-treated bed nets to protect people from malaria, one of the world’s deadliest diseases. According to GiveWell, it costs around $3,000 to $5,500 to save one life through AMF’s programs.If I donated $100,000, that could save about 18 lives, preventing families from losing loved ones to an entirely preventable disease.
Malaria Consortium
This organization runs a program called Seasonal Malaria Chemoprevention (SMC), which provides preventive medication to children during peak malaria seasons. Studies suggest that SMC significantly reduces malaria cases and deaths.While the exact number of lives saved per dollar isn’t as clearly defined as AMF’s, a donation of $100,000 would protect thousands of children and prevent untold suffering.
Helen Keller International
This charity focuses on fighting vitamin A deficiency, which causes blindness and weakens immune systems in children. Their supplementation programs are cost-effective and have been linked to significant reductions in child mortality.A donation of $100,000 could fund vitamin A supplements for hundreds of thousands of children, improving their health and chances of survival.
Part B Where Would I Donate $1,000?
If I had to choose just one of these organizations to donate $1,000 to, I would pick the Against Malaria Foundation (AMF).
Why? Because AMF has a well-documented track record, and the cost-effectiveness of their work is clear. Knowing that a simple bed net could mean the difference between life and death for a child makes this an easy decision for me. Even with just $1,000, I could contribute to protecting dozens of people from malaria, and that’s a tangible impact I’d feel good about.
Part C Applying This Approach to Other Life Decisions
This exercise made me think about how I can use a similar approach in my own life, beyond charitable giving. Here are some decisions I will be using a cost benefit analysis to
Career Choices I will compare potential salaries, job satisfaction, and long-term stability when deciding on a career path. A high-paying job might look great on paper, but if it comes at the expense of happiness and well-being, is it really worth it?
Education Investments Before enrolling in a degree or training program, i will weigh the cost of tuition against potential earnings. Some degrees have a much higher return on investment than others.
Major Purchases Should I buy a house or keep renting? Instead of going with gut feeling, I will break down the numbers, mortgage costs, market trends, and long term benefits.
Health & Wellness Preventive healthcare might seem like an unnecessary expense in the moment, but if it reduces the risk of major illnesses down the road, it’s actually a great investment.
Thanjs, Nuño.
In particular, it seems likely to me that how much you should value animals is not an objective fact of life but a factor that values across people.
I think it is both an objective fact of life, and also a factor that varies across people. For example, for valuations of human welfare as a function of e.g. country of birth, there are objective biological differences between humans born in different countries (which I think have a negligible impact on their capacity for welfare), and also different levels of nationalism.
Seems true assuming that your preferred conversion between human and animal lives/suffering is correct, but one can question those ranges. In particular, it seems likely to me that how much you should value animals is not an objective fact of life but a factor that values across people.
The Legacy of Njalira Kassim, A Good Ancestor
In the vast, rolling plateaus of Eastern Uganda, where the morning mist clings to the golden rice fields and the rivers hum with life, the name Njalira Kassim is spoken with deep respect. He was more than just a man; he was a visionary, a guide, and a builder of a future he knew he would never see. But his legacy? That would live on forever.
Njalira Kassim my great-grandfather was the man who brought Islam to our village, not just as a religion, but as a path to morality, discipline, and unity. In a time when conflicts brewed over simple disputes, and people lost their way in the absence of strong values, he stood firm, teaching that true strength lay in kindness, honesty, and faith. Under the shade of an ancient fig tree, he gathered the community and spoke of compassion, justice, and humility. His words took root, and over time, they transformed the very fabric of our village.
But his wisdom stretched far beyond faith. He saw the land for what it was a gift, not just for his time, but for generations yet to come. The vast swamps that now nourish our rice fields might have been lost if not for his foresight. He worked tirelessly to protect them, ensuring that the people who relied on them would always have food, stability, and dignity. Today, when I walk through those same green paddies, I know they are more than just fields; they are his enduring promise to us.
He believed in the power of the soil and the hands that tilled it. “The land will never betray you if you respect it,” he would say, urging the community to embrace farming as a way of life. And they listened. To this day, agriculture remains the backbone of our village’s economy, just as he envisioned. He gave people a purpose, a livelihood, and most importantly, a future they could build with their own hands.
As I walk through the village, I feel the sensation of dazzling hues of birds and towering trees swaying in the breeze, whispering reminders of the great name I carry and adore Njalira Kassim. His spirit lingers in the rustling leaves, in the songs of the birds that welcome each new dawn, and in the fields that stretch endlessly, still feeding the generations he never met.
To be a good ancestor, like my great-grandfather, is to think beyond oneself to plant trees under whose shade we may never sit, to shape a world that is kinder, fairer, and more sustainable for those who follow. He lived with foresight, knowing that the choices he made would echo through time. He valued knowledge and wisdom, ensuring that his people were equipped not just to survive, but to thrive. He led with humility, understanding that true leadership is found in service, not power.
Even now, as I stand beneath the same sky he once did, I hope that one day, I too will leave behind something that matters. That I will not only be remembered for what I achieved but for what I gave to those who come after me.
Like Njalira Kassim, I, too, hope to be a good ancestor.
This is my understanding too – some crucial questions going forward:
How useful are AIs that are mainly good at these verifiable tasks?
How much does getting better at reasoning on these verifiable tasks generalise to other domains? (It seems like at least a bit e.g. o1 improved at law)
How well will reinforcement learning work when applied at scale to areas with weaker reward signals?
Pretty sure o1 and Gemini have access to the internet.
The main way it’s potentially misleading is that it’s not a log plot (most benchmark results will look like exponentials on a linear scale) – however, I expect Deep Research would still seem above trend even if it was. I also think it’s helpful to new readers to see some of the charts on linear scales, since in some ways it’s more intuitive.
Thanks for the link, I’ve just given your previous post a read. It is great! Extremely well written! Thanks for sharing!
I have a few thoughts on it I thought I’d just share. Would be interested to read a reply but don’t worry if it would be too time consuming.
I agree that your laser example is a good response to the “replace one neuron at a time” argument, and that at least in the context of that argument, computational complexity does matter. You can’t replace components of a brain with simulated parts if the simulated parts can’t keep up with the rest. If neurons are not individually replaceable, or at least not individually replaceable with something that can match the speed of a real neuron, (and I accept this seems possible) then I agree that the ‘replace one neuron at a time’ thought experiment fails.
Computational complexity still seems pretty irrelevant for the other thought experiments: whether we can simulate a whole brain on a computer, and whether we can simulate a brain with a pencil and paper. Sure, it’s going to take a very long time to get results, but why does that matter? It’s a thought experiment anyway.
I agree with you that the answer to the question “is this system conscious?” should be observer independent. But I didn’t really follow why this belief is incompatible with functionalism?
I like the ‘replace one neuron at a time’ thought-experiment, but accept it has flaws. For me, it’s that we could in principle simulate a brain on a digital computer and have it behave identically, that convinces me of functionalism. I can’t grok how some system could behave identically but its thoughts not ‘exist’.
It increases the AI arms race thus shortening AGI timelines, and, after AGI, increases chances of the singleton being either unaligned or technically aligned to being an AGI dictatorship or other kind of dystopian outcome.
The LW tag is useful here: it says More Dakka is “the technique of throwing more resources at a problem to see if you get better results”.
I like David Manheim’s A Dozen Ways to Get More Dakka; copying it over to reduce the friction of link-clicking:
So if you’re doing something, and it isn’t working well enough, here’s a dozen ways to generate more dakka, and how each could apply if you’re a) exercising, or b) learning new mathematics.
A Dozen Ways
Do it again.
Instead of doing one set of repetitions of the exercise, do two.
If you read the chapter once, read it again.
Use more.
If you were lifting 10 pounds, lift 15.
If you were doing easy problems, do harder ones.
Do more repetitions.
Instead of 10 repetitions, do 15.
If you did 10 problems on the material, do 15.
Increase intensity.
Do your 15 repetitions in 2 minutes instead of 3.
If you were skimming or reading quickly, read more slowly.
Schedule it.
Exercise at a specific time on specific days. Put it on your calendar, and set reminders.
Make sure you have time scheduled for learning the material and doing problems.
Do it regularly.
Make sure you exercise twice a week, and don’t skip.
Make sure you review what you did previously, on a regular basis.
Do it for a longer period.
Keep exercising for another month.
Go through another textbook, or find more problem sets to work through.
Add types.
In addition to push-ups, do bench presses, chest flyers, and use resistance bands.
In addition to the problem sets, do the chapter review exercises, and work through the problems in the chapter on your own.
Expand the repertoire.
Instead of just push–ups, do incline push ups, loaded push-ups, and diamond push-ups.
Find (or invent!) additional problem types; try to prove things with other methods, find different counter-examples or show why a relaxed assumption means the result no longer holds, find pre-written solutions and see if you can guess next steps before reading them.
Add variety.
Do leg exercises instead of just chest exercises. Do cardio, balance, and flexibility training, not just muscle building.
Do adjacent types of mathematics, explore complex analysis, functional analysis, and/or harmonic analysis.
Add feedback.
Get an exercise coach to tell you how to do it better.
Get someone to grade your work and tell you what you’re doing wrong, or how else to learn the material.
Add people.
Have the whole team exercise. Find a group, gym, or exercise class.
Collaborate with others in solving problems. Take a course instead of self-teaching. Get others to learn with you, or teach someone else to solidify your understanding.
This article has a lot of downvoting (net karma of 39 from 28)
This does not seem to be an unusual amount of downvoting to me. The net karma is even higher than the number of votes!
As a more general point, I think people should worry less about downvotes on posts with a high net karma.
Thanks for asking! I added it to the post. The deadline for applications is Monday, 31 March.
Thank you for your comment Marius, this is super useful!
Fair point. I certainly don’t think it is established (or even more than 50% likely) that SBF was purely motivated by narrow personal gain to the exclusion of any real utilitarian convictions at all. But I do think he misrepresented his political convictions.
“how much AGI companies have embedded with the national security state is a crux for the future of the lightcone”
What’s the line of thought here?
Some asked asked what the impact of applying SyDFAIS could be?
I’ve given this ~ 2 hours of thought, aligning with current literature on Bridgespan’s 5 observable characteristics of field-building across 35+ fields.
Below is an impact assessment table, presenting quantified estimates across 5 key outcome areas, along with underlying assumptions and uncertainties.
https://docs.google.com/document/d/1gm0LJ2nDifUfnQn0T7ZqWbo4RNf42MwEjd7Bc8jq0Gg/edit?tab=t.0I may develop this into a separate post...
More dakka is to pour more firepower onto a problem. Two examples:
Example: “bright lights don’t help my seasonal depression”. More dakka: “have you tried even brighter lights?”
Example: we brainstormed ten ideas, none of them seem good. More dakka: “Try listing a 100 ideas”
When people write “more dakka,” do they simply meaning that we need to try harder and/or try more things? I’ve seen this in two or three pieces of writing on the EA Forum, but I’ve never seen a clear explanation. Apparently “dakka” is slang from a sci-fi video game/tabletop RPG? Is this useless in-group terminology, or does this actually have value?
As best I can tell, “more dakka” is a reference to this quote. Can anyone point me to a more clear or authoritative explanation?
We know the solution. Our bullets work. We just need more. We need More (and better) (metaphorical) Dakka – rather than firing the standard number of metaphorical bullets, we need to fire more, absurdly more, whatever it takes until the enemy keels over dead.
Excited to see people capitalizing on opportunities like this!
I’d wonder how much harder it would be to get large commercial product vendors to consider the same thing. (Approaching them is probably harder, and they likely already have food chemists, etc. who would have vested interests and/or would need to be convinced.)