I'm not sure if there are any research showcasing the effects humanity has had in general due to low sun exposure. From all the benefits of Vitamin D and the recent human behavorial shift leading to low sun exposure (car travel, air conditioning, sunscreens even), there are bound to be new biological or psychological changes humanity is experiencing for the first time.
One study found a difference in mortality between the max-sun-exposure and min-sun-exposure cohorts: the second was twofold higher, which is comparable to the effect of cigarette smoking. https://pubmed.ncbi.nlm.nih.gov/24697969/ . I.e. avoiding sun exposure completely is as harmful as smoking cigarettes.
Yes, I think that too. Besides sports, most young people studying today are aiming for jobs that are mainly indoors. It's not a requirement, of course, but because a lot of modern careers consist of working in offices or other enclosed environments.
No movement, No sun, Stale Air (Unless you have good ventilation). Pretty harmful if we think about it.
I've wondered for a while if the apparently higher cognitive performance and resulting societal wealth at higher latitudes might be some kind of second order side effect from long-term selection for lower sun exposure. We already know this vitamin D is almost certainly why Northern peoples evolved lighter skin.
(I realize this is a frought topic, so please hold the race science bullcrap replies or the over-reactions in the other direction. I am not a believer in hard biological determinism or "race science," but I also don't dismiss the existence of variations. As with everything else in population genetics and biology, any variations that do exist probably have more than one cause.)
If there's any truth to this, it might be further compounded as people with darker skin spend more time indoors in the modern world. If you have darker skin you need, as far as I know, more sun to make vitamin D, which normally is not a problem if you're outdoors near the equator. Maybe darker skinned people need to be taking more D supplements.
Doesn’t that make a feedback loop though? Poor health equals higher health care overhead, lower productivity, more family issues, and overall worse outcomes all over the place. That in turn is going to make educational outcomes worse and child rearing worse. Some diseases can even have lasting cognitive side effects.
Tailored clothing is at least 80,000–170,000 years old based on genetic clock research in body lice [1] but archaic humans have probably been wearing hides for at least a million years (there’s currently a big debate about how they managed to migrate to colder climates like Spain 800k-1.2m years ago).
I don’t think clothing is that big a factor because all humans in hot environments adapt and very little survives in the archaeological record. Many populations lived in heavily forested jungles where they was little sun exposure and those in deserts used stuff like Otjize for sun protection. Given all the ethnographic reporting from the age of exploration, tons of that clothing was probably made of feathers, cordage, bark, and other materials we wouldn’t even think of using for clothing.
Still, 170,000 - 1.2M years is a fairly short amount of time if we go back only to the common ancestor who begat progeny that would become Pan and Autralopithecus (around 12 million years ago). It could be that early hide wearers started a trend that, to this day, continues to interfere with natural vitamin D metabolism (while also providing many benefits).
Our ancestors started losing their hair about 2 million years ago and the MC1R gene giving us eumelanin pigmentation was fully fixed in the population around 1.2 million years ago by which point we were mostly hairless. In that range is when our vitamin D metabolism evolved, so clothing would have been present for large fractions of our existence.
Going back to a common ancestor with monkeys is pointless because their vitamin d pathways are significantly different like 7-dehydrocholesterol secretions that metabolize to vitamin D via external UV exposure and are ingested during grooming.
Precisely. People don't realize that it's all numbers. Given average IQ of people involved in a project is 140, an AI with an IQ of 150 can replicate each and every such individuals in the pipeline. People saying AI can't do this or AI can't do that should come to terms with the fact that this IQ gap is monotonously increasing.
1: When was the last time you worked on a project where you thought the average IQ was 140? I don’t even think I have worked on a project where the maximum IQ was 140.
2: Who thinks the IQ of people on the project determines its success? There’s so much more to it than just “high capability team members” (to give IQ a generous interpretation).
3: (math joke) A sequence like (AI IQ - Human IQ) can be negative and monotonicly increasing and still never reach 0.
Pattern matching against millions of IQ test questions from a training set in order to score 150 on an IQ test doesn't give you an intelligence equivalent to 150.
I agree. Inexperienced people (not necessarily "dumb") are likely to accept everything at face value, not apply critical thinking skills, and not even check the AI generated output.
What IQ "means" is separable from what it is. IQ is a measure of performance on IQ tests. That's literally what it is. If a computer system can complete IQ tests, it has an IQ.
The issue is that IQ means less than you want it to.
I don't want IQ to mean anything. pkoird clearly wants it to mean something.
IQ is a terribly flawed measure of human intelligence. But it measures nothing when you apply an LLM that contains multiple IQ tests in its corpus. IQ is deeply flawed, but the point is not to "measure performance on IQ tests". If someone cheats on an IQ test and scores 200, no reasonable person would say they have 200 IQ.
Is that true though? If I define a category or range in formal language, I’m still ambiguous on the exact value. Dealing with randomness is even worse (eg input in random order), and can’t be prevented in real world programs.
Clever. My first impression was that surely this saturates the filter too fast as we're setting more bits at once but looks like the maths checks out. It's one of those non-intuitive things that I am glad I learned today.
It works because the original filter has suboptimal settings. An optimal filter of that size and number of items would set 5 bits per item and have about a quarter of the false positive rate. The 2 bits per item in the blocked filter is still suboptimal, but it's also saving them from saturating a bunch of 32-bit blocks, at the cost of a much higher overall false positive rate.
True, I had the same feeling. The article does go off 256K elements in a bloom filter of 2M. After 1M elements, using 2 bits actually increases false positive rate, but at that point the false positive rate is higher than 50% already.
AI will scrape your blog and your personal philosophy will eventually become a part of collective Human Intelligence. That's a pretty good reason to blog imo.
That reminds me of a gimmick a while ago where GitHub would collect your repositories into an Arctic Code Vault. That was IMO a bit of an incentive for me to upload random bits of git repositories I have on my PC just so that I can say my code will last 1,000 years somewhere in the arctic.
I remember it vaguely but there used to be a badge awarded for being among the first 100 people to solve the problem. I was obsessed with getting that badge to the point that I spent obscene amount of time solving the-then recently released problem even when the following day was my final exams. I did manage to get that badge though. This was circa 2013. Fun times!
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