First — 0.69% of total exports is blood still is surprisingly high! Remember, you can get blood from humans in your own country, and prepare it there. So, why do you need it from the US?
Second — it’s amazing the detail that you can achieve from public data.
Third — I’m left wondering if a true “Deep Research” like tool would be able to provide the same analysis. I find that Deep Research is fine for secondary sources, but not for Deep Analysis of primary source data.
The reason the US exports blood products is because it is one of 5 countries that allow commercial blood product harvesting. Well, at least plasma. I don't remember which organization it is, but there is an international organization that tries to get countries to be "self-sufficient" in blood products so that they are not internationally traded (the organization is something like WHO, UN, or Red Cross). Only those 5 countries that allow some level of commercialization actually meet their goals of being self sufficient (and export as on top of that).
Source: A guest lecture at my university by Al Roth, Nobel prize-winner in economics, who is currently focusing his work on these type of markets. Most of his work is on kidney exchanges right now.
Cognitive dissonance really is required to keep our “warm fuzzy empathic friendly” self image while simultaneously being ruthlessly pragmatic cold blooded killers when it suits us.
Just wait till these robot maximalists figure out that a pile of oxygen, carbon, hydrogen, and nitrogen is much cheaper than robots made out of steel and carbon fiber.
I mean, they haven't glommed onto the daily experience of giving a kid a snickers bar and asking them a question is cheaper than building a nuclear reactor to power GPT4o levels of LLM...
If we could directly convert the food energy of a Snickers bar to electricity we could easily power AI. A Snickers bar has 250 kcal, which is 1000 kJ or about 250 grams of TNT.[https://www.wolframalpha.com/input?i=250+kcal+in+joule] chatgpt-4 uses 3.6 kJ to 36 kJ per query so you could get potentially hundreds of queries on a single Snickers bar.
We only need a way to harness the power of the human body. Maybe we put people in VR for fun while using their body heat to power the AI.
TNT and other explosives have relatively little energy per kg compared to eg petrol or snickers.
That's explosives are chemicals selected / designed to be able to release their chemical energy really quickly and without needing any external oxidizer (because harvesting atmospheric oxygen would be too slow). That focus obviously leads to compromises in other areas, like energy density.
Temporarily, on the margin. A human would need multiple Snickers bars per day to survive, and can't survive on Snickers bars alone for more than couple days or weeks.
Also no human is anywhere close to being as knowledgeable and skilled as LLMs at all the things at the same time, so it hardly even compares.
Only if you also ate some random other stuff you found lying around. Doesn't even have to provide much in the way of energy, just enough 'dirt' to round out your diet with whatever other essentials you need.
Human bodies have evolved to survive for a long time on relatively little, yes. But not to evolve for a very long time on a single source of very 'clean' food like snickers bars. 'Clean' in the sense that chemically snickers has relatively well defined inputs, whereas hungry humans would eat just about anything, including insects and grass and bark or leather.
This isn’t true. There are countless cases of people surviving for months on nearly no food at all.
I’m not talking about what it takes to stay alive for long term periods. I was refuting the silly idea that you would die after a couple of days/weeks of snickers.
How much vitamin C is in a snickers bar? I think you'd get scurvy within a month or two if that's all you had.
How much vitamin A? Night blindness. Vitamin B? Neurological issues, confusion.
That's the thing with mono-diets, your body needs a diverse range of things that it can't synthesise itself.
But to the core point, in cases where the output of an LLM is good enough, many already have much lower energy requirements than humans: o4-mini is currently priced at $1.1 per million tokens of input and $4.4/million tokens of output; if that's all being spent on electricity at $0.1/kWh, that's a max of 11 kWh/million tokens in and 44 kWh/million tokens out — how many calories would a human have to burn to read, write, hear, speak, and internally monologue the equivalent of a million tokens?
They're fully aware of the obvious fact that LLMs are getting better at reasoning than humans at scale in general, and this includes power efficiency too. Meanwhile, what is not getting comparably better is robotics. This leads to obvious conclusion about natural order of things and division of labor: computers are for thinking, humans are for doing manual labor.
> the obvious fact that LLMs are getting better at reasoning than humans
I wanted to say that you were wrong, that LLMs can't reason and so it certainly isn't an obvious truth that they do it better than humans, but when I asked AI if LLMs can reason it told me that they can't which (while still not being reasoned by the LLM) seems to support the spirit of your claim since it gave a correct answer while you (a presumed human that can reason) got it wrong.
We might be elevating the importance of reasoning too much because us humans need to use it to solve many difficult problems. But if intuition was stronger, conscious/explicit/logical reasoning might not be needed. Didn't the famous mathemetician Ramanujan say that God gave him his answers in his dreams? That sounds like really powerful intuition like an LLM. Us humans can already solve a lot of incredibly complex problems intuitively, but they're quite domain-specific, like for spatial navigation and social interaction.
Anthropologist Gregory Bateson predicted we'll know machines are conscious when we ask a question and the computer responds, "That reminds me of a story."
That seems to be the hangup. I have to use a definition that would put it on equal footing to what we do as humans since that's the comparison being made.
Computers and software can be said to "understand", "think", and "reason" in their own way and informally people have always used those words in that context. Recently, software which has been trained on human-reasoned output is producing text that mimics reasoning well enough that it can be confused for the real thing, but nobody has been able to show that any reasoning (as a human reasons) is what's occurring.
If the output it produces is as useful to me as the output produced by a human with the magical and expensive capability to 'reason', why should I care?
There are several that would apply. Let's use this one as an example: Reason is the capacity of consciously applying logic by drawing valid conclusions from new or existing information, with the aim of seeking the truth.
I don't think you need consciousness to reason. I don't see why repeated application of rewrite rules to extrapolate logical conclusions from antecedents shouldn't be considered reasoning. LLMs are perfectly able to match and apply rewrite rules, while using fuzzy concepts rather than being bound to crisp ontologies that make symbolic reasoning impractical to scale up. And for better or worse, LLMs can also apply simplified heuristics and rules of thumb, and end up making the same mistakes that humans make.
If you think "consciously" is a loaded term, wait until you get to "truth"!
Maybe it'd be easier to try another definition:
2
a(1)
: the power of comprehending, inferring, or thinking especially in orderly rational ways : intelligence
The same source defined intelligence as:
a(1)
: the ability to learn or understand or to deal with new or trying situations : reason
also : the skilled use of reason
And here we get the core of the issue. AI doesn't "think". It doesn't comprehend or understand what it does. There is no actual "I" in AI that didn't come from the people whose works were used to train it. At least not yet. I question if LLMs will ever be capable of anything more than producing a convincing affectation of the process used to produce the material it was trained on. I suspect that AGI will have to come from elsewhere. That doesn't mean that what passes for AI these days can't be useful, but I don't think it's capable of reason and as far as I know, nobody has proved otherwise.
Comprehend, from com- ("together" or "with") and prehendere ("to seize" or "grasp"). To take a hold of.
Can a calculator comprehend arithmetic? Can it take a hold of a number (in a register, for example), and a second number, and add them together to get a hold of the result?
What is computation, really? When we design machines to do arithmetic, do the machines actually do arithmetic, or do they just coincidentally come up with states that we humans can interpret as a correspondence with arithmetic?
More importantly, would a rose by any other name smell as sweet?
If you put a problem into text, and give it to an LLM, and an LLM applied a series of higher order pattern matching to it to produce more text, and you read the resulting text and interpret it as reasoning about the solution to a problem, has the LLM reasoned? Does the calculator calculate? Or does it really matter?
To all of you complaining about LLMs hallucinating, do try to give the same prompt to a kid on a sugar rush and let me know if you're getting more reliable responses.
The US also has a lot of people and those donation centers like to be around poor people and junkies which sacrifice their bodies for a couple of bucks. All the money they get are compensations for the time being attached to the machine, because you can’t get paid for anything which comes from your body.
But then the donation center sells your plasma and various other parts of your donation for top dollar to pharma which sells it again.
The machines are not excellent , spills and abrasion products can enter, and you might infect yourself with diseases which you sign a form for. The only safe way to donate blood would be full-blood donations without machines, but they will still separate your plasma and sell it to pharma.
Awful system from my perspective. Separating blood from organ trade would be appropriate. A blood donation foundation or something where value is distributed down to the donor would be an idea.
People with more connections can already get faster access to donor kidneys.
And a poor person with one kidney less but extra health checkups can probably get better health outcomes than a poor person with two kidneys but extra health checkups. (This assumes that the kidney sale comes with some mandatory regular health checkups. Just like kidney donations do.)
In Iran, there is no tracking of donors and most donors don't want to be associated with the donation long-term, as it's connected to their poverty and the shame of their poverty. In the limited surveys that have been done many also noted that they haven't been properly informed about the risks of a donation.
The time is gone anyway, and barring industrial accident you still have your entire body to sell again afterwards. That is not true of kidney donation — you can't donate a second time¹ and if your remaining one fails you are up shit creak because if you were in the position of being willing to sell one back then you are unlikely to be in the position to buy one now.
Donation of blood and other replenishables is a bit different of course, but allowing open sale opens some bad avenues in terms of people effectively being forced to (which could carry risks they wouldn't normally want to take).
> Third — I’m left wondering if a true “Deep Research” like tool would be able to provide the same analysis.
Note that this analysis was performed by Dynonight, a rather bright blogger whose articles appeared several times on the HN front page. The vast majority of humans (I include myself here) probably wouldn't be able to achieve a result of comparable quality, even if it doesn't look that hard in retrospect.
LLM Deep Research can already exceed the performance of not-so-bright humans, but it is a quite different matter to outperform smart people like Dynomight. (I guess "research experts" isn't quite the right term here. The mentioned journalist from The Economist apparently was unable to research the topic to a similar degree, even though research is a main part of his/her job.)
>Third — I’m left wondering if a true “Deep Research” like tool would be able to provide the same analysis. I find that Deep Research is fine for secondary sources, but not for Deep Analysis of primary source data.
In the searches I have done Google's "Deep Research" has been better at providing primary data (or very convincingly fabricating).
OpenAI's version seems to more likely to give the answer that everybody thinks is true. For the blood example I could see it finding many sources that repeat the 2% claim, and accept that because everyone seems to agree, then it must be right. That's a mixed blessing in that maybe most casual users might want the commonly accepted answer, but when I have used the deep research tools, it has almost always because I know the answer everybody gives for a particular question, but I suspect it might not be based in reality. This makes my reason for wanting an automated deep research tool coinciding with the weakest area of the tool itself.
It's also been a bit eye opening how often commonly repeated but poorly founded claims, seem to turn up the same names of individuals, (or organisations, or individuals pretending to be organisations) as you trace them back.
> Remember, you can get blood from humans in your own country, and prepare it there. So, why do you need it from the US?
Random hypothesis:
• equipment needs for uranium enrichment for Manhattan project in 1940s
=> US cornering the market on centrifuges (in both a "we buy them all" sense and a "we won't let companies sell them to other state actors in quantity" sense) for decades
=> US biomedical manufacturing of anything requiring centrifuging as a step, quickly outstripping that of all other countries
=> eventual global logistical dependence on US-based suppliers for such products
In reality simply that the US lets you pay people for blood plasma, an the market does the rest.
There are similar arguments made for kidney donation. Paying people a set amount kidneys is exploiting the poor, but most those who need kidneys are not well off and there is an enormous shortage causing massive shortages, so some argue that we should pay since society would be net better off.
The centrifuges needed for biology (or medicine) are very different beasts from those you need for uranium enrichment.
Miele and Bosch makes great centrifuges for their washing machines. That technology is probably closer to what you need for blood, than the uranium enrichment equipment would be.
Second — it’s amazing the detail that you can achieve from public data.
Third — I’m left wondering if a true “Deep Research” like tool would be able to provide the same analysis. I find that Deep Research is fine for secondary sources, but not for Deep Analysis of primary source data.