> severe VDD was defined as serum 25(OH)D levels of <25 nmol/L, moderate deficiency as 25–50 nmol/L, insufficiency as 50–75 nmol/L, and sufficiency as >75 nmol/L.
These numbers seem high to me. The 75 nmol/L (30ng/L) is not really a reliable value. It was published in a research that raises many questions due to conflict of interests.
Hence the
> ~40% of people don't get enough vitamin D
becomes:
> ~40% of people in the USA don't get enough vitamin D according to Dr. Holick
Where I live the norm is 20 ng/L and if we apply that, then the shocking 40% becomes more reasonable 10-15%
Insufficient in Ireland is also set at 30--50 nmol/L (12--20 ng/mL).
Sunlight UVB radiation needed to make vitamin D is only available in Ireland during the months of April through October. This is due to our geographic location 52o - 55o North and means that Ireland experiences a ‘vitamin D winter’ that stretches from the end of October to late March.
Currently, 94 % of children, 94 % of teenagers and 90 % of adults on the island of Ireland have inadequate vitamin D intakes. Therefore, almost everybody in Ireland needs a supplement of vitamin D and 15 µg (600 IU) is recommended on a daily basis.
N.B. In the early 2000s, over 20 cases of rickets (a weakening of the bones caused by severe vitamin D deficiency) in infants and toddlers were reported in Ireland.
Seems like a reasonable measure would be to look at a native person, from ones lineage, having a relatively average pre-industrial day.
If lineage doesn't matter, and all humans are the same, you could probably just go sample some tribe members that still lives mostly outdoors, outside of developed society.
you're asking the question the wrong way around. How did Dr. Holick come up with 30ng/L and what were his incentives?
Clearly he made a lot of money publishing that research. And people who paid him also made billions. But let's focus on the rest of the world that didn't increase the norm that works by 50%
I don't want to go into this debate. The cited benefits of Vitamin D have to do with Calcium and bones. This is just absurd to me. Do people in Europe have brittle bones? Those 40% with alleged Vitamin D deficiency have issues with Calcium and get bone fractures every other day?
Vitamin D deficiency manifests itself as rickets (weakening of the bones) in children and osteomalacia (softening of the bones) in adults. Less severe vitamin D deficiency contributes to osteoporosis (bones are weaker and more likely to break). All of these are well documented outcomes in Western Europe.
More to the point, since Covid Researchers have posited that Vitamin D plays a critical role in preventing respiratory infections, reducing antibiotic use, and boosting the immune system response to infections. Vitamin D is important in regulation and suppression of the inflammatory cytokine response, which plays a role in the severe consequences of COVID-19 and ‘acute respiratory distress syndrome’ associated with ventilation and mortality in COVID-19. Vitamin D also helps the respiratory tract produce antimicrobial peptides that can lower viral replication rates.
And, now you've discovered why Europeans have light skin [1]! And, why supplementation is suggested for those with dark skin [2] living in regions with light skinned natives!
Thankfully we have no voting power in the said country so they don't care what we think as long as we consume and overall behave. Let's see how long this lasts though. It seems as though EU is approaching the finding out stage.
Write a prompt, evaluate the prompt, understand that is succeeds 95% of the time.
Write a new prompt, evaluate, it now succeeds 99% of the time. Measure what changes between prompt #1 and prompt #2, understand what contributed to the performance jump.
Write a third prompt, this one succeeds 100% of the time. Increase the size of your evaluation set, find a 1/5000 error-class and a 1/10000 error-class, add some explicit code to correct for this cases.
Roll out to production, collecting usage metrics. You make some tweaks to your harness, your prompts. Eventually you have confidence that your system has fewer mistakes than 1 in 100k.
Now, multiply this iteration across all your different prompts and different ways that they might interact with one another.
There's a reason engineers are prissy about people coming along and saying "I write code, I'm an engineer" that people periodically try to sand-paper away.
Engineers don't just tie a sheet to a rock and throw it off a cliff and call themselves aerospace engineers.
They do full diligence on the theory, math, physics, material science, fluid dynamics, etc, and plan a controlled series of tests specifically designed to verify/challenge/disprove their concept and the theories behind it.
Sure, there's a team member ultimately responsible throwing half a dozen rocks off a cliff in the first test.
A technician.
The guy who throws the rock off the cliff is a technician.
The other glossed over part is that the above sounds like science.
Engineering often continues until the concepts and theories are developed into safe, practical methods. "If you stay within these parameters, you can confidently expect these results." The reliability can be codified and reproduced without going from first principles on every application of it.
It's not clear to me that the current AI fad is really developing such reproducible, safe methods. "If you stay within these parameters, you might get these results. Or a teapot. Or some subtly misleading fabrication."
You have to do full due diligence to validate every result. There is safe usage where the hard work was done up front so that day to day practice can skip to boring and reliable application.
To a software engineer, a (current) LLM is a stateless algorithm that performs an idempotent transformation on a large numeric input.
People who think it's a system that thinks and reasons have confused the agentic harness, perhaps forgotten(?) layer0[0] is a seed, the inference engine sets to a concrete value when the caller leaves it as 0.
They probably work on (current) AI software by repeatedly writing prompts like "DON'T READ THE FILES IN /tmp. SOME OF THE FILES IN /tmp ARE VERY LARGE. DUE TO THEIR SIZE, YOU ARE NOT TO READ THE FILES IN /tmp." and wondering why the model becomes obsessed with files in /tmp 100k tokens into every conversation.
"Most classical engineering fields deal with probabilistic system components all of the time. In fact I'd go as far as to say that inability to deal with probabilistic components is disqualifying from many engineering endeavors."
> It's not engineering if you're just guessing as to what is degrading the performance and what might improve it.
Engineering is literally the art of making educated guesses and then testing/proving/disproving/improving upon them. Nothing is exact. Everything is approximate. Iterate until the result is good enough.
If you can identify gradient (what direction your change will impact the ultimate goal), then just repeating the process (or reverse-process) can find local maximum.
Still it can be a software engineering if the gradient candidate / measuring gradient / repeat process can be done at scale.
Things like Voice to Text and biometric unlocks (fingerprint scanners, face ID) have worse success rates and they're used every day by billions of people.
The fundamental issue is, that "we" somehow decided it would be a good idea to throw all the fundamental ideas of computing (determinism, context, separation between data and execution,...) away and try to solve the issues by running a probabilistic/stochastic word generator on top of deterministic circuits instead at 10 magnitude worse efficiency.
It's not a fundamental issue. Determinism and "separation between data and execution" are artificial constructs, make-believe universe in which we design classical code, and a whole lot of hardware engineering goes into allowing us to briefly forget it's all fake.
Real world is probabilistic in practical / metrological, if not fundamental sense, and separation between data and execution does not exist. Our reality does not support such separation.
> a probabilistic/stochastic word generator on top of deterministic circuits instead at 10 magnitude worse efficiency
It's 10 magnitude better efficiency end-to-end, if you factor in design time you'd have to spend to get your "deterministic circuits" (which really aren't, we just paper over it) into shape so they deterministically solve a specific problem, for each problem you want to solve - where with the "stochastic word generator", you just need to change the text prompt.
It might not be apparent from the start what are the best demands to put inside a skill, you can only know by evals. There are whole papers dedicated to changing a few details in a coding harness. https://arxiv.org/abs/2609.20519
Engineering is the use of mathematics to turn science into technology. Statistics is mathematics, comp sci is science, and technology is the end product.
So you are saying "don't hate the player", but hating the game is a big nono. That thing that isn't capitalism is inherently evil and should be avoided like a plague
I don’t understand your comment, can you elaborate? I’m saying that drawing corporate investment into open software is preferable to all of that investment going into proprietary software. I want as much open software as possible and I want us to be practical at all levels. Big swings like public grants and a better safety net (even UBI) are things I’m supportive of too, and can coexist with incentives for drawing in corporates. There’s a certain purism argument that a company that is involved in open software is constantly criticized for being insufficiently open but a proprietary software company receives no such similar criticism, which I think is irrational.
I don't know which exact company you are talking about. I see most proprietary companies heavily criticized and do so myself and used to heavily advocate for OSS at $work. My current work is 99.9% opensource.
As for my point, the main issue you are pointing out is the fundamental flaw in capitalism: companies focus on profit instead of technological progress. The two can be correlated but that isn't granted. See enshittification.
There are other economical models that could potentially address the shortcomings of capitalism but a lot of effort is put into discrediting socialist/communist ideas as they threaten the wealth of the wealthiest.
> Until two months ago, any user or OpenAI employee logging into OpenAI’s own help forum (community.openai.com) could have had their ChatGPT and Codex accounts taken over.
Hey, it's their call to decide the value of their entire user base.
The question for me is where it leaves innovation. Have we really peaked as a species that we so easily want to give up on the young and hand them over a tool that would substitute reasoning?
Call me naive or old, but I don't see a need to think critically when you have a tool that can outmatch you in that.
I tried drawing analogies with Chess, but it doesn't work. Shall I ask AI to do that for me?
If we think that machines that recombine and interpolate our prior out are intelligent then yes we have probably peaked as a species. Anyway evolution is not telological. It may surprise HN posters but people were as intelligent if not more so as present thousands of years ago. When a problem is solved is more a question of attention, reward, available knowledge base, etc. intelligence is an adaptation to solve the problems of biological life. It would be hard to argue that solving this cypher would have increased anyone's reproductive fitness that much hence it was unsolved. Unsolved problems are often so less because of intrinsic difficulty but lack of conditions that impell their resolution. It is not at all surprising that llms with the full human knowledge base at their disposal, ample computational resources, and the programmed reward of finding the best completion are solving unsolved problems nobody needed to solve anyway. This however is not intelligence in the human sense. Humans solve problems for biological advantage in a dynamic landscape. Llms solve problems to optimize a completion function in a fixed pre trained one.
> The question for me is where it leaves innovation. Have we really peaked as a species that we so easily want to give up on the young and hand them over a tool that would substitute reasoning?
This is a crucial question but I'm afraid the ship has sailed. We should focus on how to prevent atrophy and cultivate our skills in spite of LLMs. For me and many others this means doing thins the old way with occasional assistance from LLMs that actually increase our understanding. Occassional because if you do it often, you get intellectual atrophy because you stop even trying.
This is all valid and I am with you here. However I can totally imagine kids in 10 years viewing writing code by hand same as we view making fire using flint and steel: yes can be useful, but why bother?
Except in this case I fear we're losing something very important as opposed to the above example.
If you are going out camping in some form of wilderness (harder and harder every year due to the crowds), it can be very useful. I think of LLM use as the same- we'll just have different problems to solve for. Now we have to think about lighter fluid and know how a lighter works. I really don't think we've lost anything by not using flint and steel- anyone can learn how to do it in a couple minutes.
They cannot yet outmatch humans in critical thinking. Heck, they cannot outmatch a mediocre person like me yet. How many times have we awen "You are right...." Even on sota models?
They are great tools for research and tasks as of now.
I think they can match a human in critical thinking, but they can't match a human in coherence and meta-thinking. You can prompt an LLM to critically think of any idea you want and it's often able to do so, but it's rarely going to do that by itself.
These numbers seem high to me. The 75 nmol/L (30ng/L) is not really a reliable value. It was published in a research that raises many questions due to conflict of interests.
Hence the
> ~40% of people don't get enough vitamin D
becomes:
> ~40% of people in the USA don't get enough vitamin D according to Dr. Holick
Where I live the norm is 20 ng/L and if we apply that, then the shocking 40% becomes more reasonable 10-15%
reply