"The data showed that the age-adjusted incidence rate fell from 55.2 per 100,000 in 2000 to 36.7 in 2022, then rose to 38.3 in 2023."
If you would like to advance a theory that this is because of a specific environmental change, your theory should cope with the fact that the rate was MUCH higher in 2000 and the rise described here is is 2023. Increased screening is said to be a likely culprit in this case for middle-aged adult prevalence but not for older adult prevalence, because screening has increased somewhat in the middle aged groups.
I am personally dealing with colon cancer, and one of the incredibly annoying things about the awful disease is the number of truly clueless people who use it to advance some culinary agenda they believe in without evidence.
I looked through your comment history to ensure you haven't already answered this. But what made you get tested ? Did you have risk factors ? No problem if you'd rather not share.
Related, I was told by a doctor to get screened after turning 50. But a reasonable self-estimate given all my risk factors puts my chances of having colon cancer at 1 in 10000. A colonoscopy has a false positive of ~2%[0] for my demographic. Meaning if I get a positive result, it's actually ~200 times more likely that I don't have cancer. It's hard to justify a screening given those odds and the 99%+ chance I will waste my time treating and worrying about a disease I don't have. My guess is an insurance company wouldn't cover a colonoscopy for those reasons.
I just had my first colonoscopy at 45 - they lowered the guideline recently, as the article mentioned.
The link you give is for colon cancer blood tests. Colonoscopies themself are basically definitive, because if they see something suspicious they will snip it and send it to the lab for biopsy. I had one such "suspicious polyp" and it turned out it wasn't a polyp at all, just normal intestinal tissue they mistook. There's your false positive. But the risks and long-term consequences are basically nil, the intestine heals itself in a week or two.
It's a very unpleasant procedure (the prep, not the procedure itself), but it's also very low risk and effective at catching colon cancer cases early when they can still be treated.
> If you would like to advance a theory that this is because of a specific environmental change
It probably is, but it could be anything. For all we know, (joke,) it could be a pesticide with traces present in salads and fresh fruit, or exposure to a cleaning chemical in public transportation.
But the bigger issue is that the people pushing these theories are pushing them on moral reasons; IE, making an unfair claim that colon cancer is on the rise because people have immoral lifestyles. IE, from eating poorly or the multitude of other holier-than-thou lifestyle claims at the tip of their tongue.
Personally, my money is that we find out that regularly holding in farts increases the probability of colon cancer, and that we need a public health campaign to fart in public.
So the processed meat -> colorectal cancer link is actually a textbook example for explaining what statistical & scientific concepts mean.
Processed meat is a known Group 1 carcinogen, in the same category as asbestos, tobacco smoke, and plutonium. Carcinogens are grouped by the strength of scientific evidence on them, not by how hazardous they are. In this case, there are abundant studies with solid methodology that show a link between consuming nitrites in processed meat and a higher risk of cancer, and we also understand how the process works at a molecular level.
This shows how well we understand the link, not how strong the link is. And it turns out that processed meat is a very minor carcinogen. When you average the studies together, the hazard ratio for someone eating 50g of processed meat per day, over an 85 year lifetime, over somebody who eats no processed meat is about 1.18. That means that folks in the former group are about 18% more likely to get colon cancer than folks in the latter group. By contrast, the hazard ratio for cigarette smoking is about 20x (smokers are 2000% more likely to get lung cancer than non-smokers), for asbestos exposure it's about 35-45x (industrial asbestos workers without PPA develop mesothelioma at a rate 3500-4500% greater than the general public), and plutonium exposure is about 7-50x for a single unprotected exposure.
There's a further piece to the statistical puzzle, and that's base rates. Colorectal cancer is relatively rare, with a lifetime incidence (again assuming an 85y lifespan) of about 7%. Combined with the 18% hazard ratio, that means a diet full of processed meats increases your lifetime risk of colon cancer by about 1%. There are far worse activities you could be doing.
A related concept is the Prop65 warning labels in California. If you've ever been to the restrooms in the SFO airport, you might notice that there's a warning label of "This restroom contains chemicals known to the State of California to cause cancer." These are pretty ubiquitous, you'll see them everywhere else in California too, like on new cars. Are you going to get cancer just because you transferred through SFO or LAX? No. But the list of chemicals that have scientifically demonstrated carcinogenicity is long, and the good people of California don't really make a distinction between minor risks and major risks.
Whether the known carcinogenicity of processed meats is behind the uptake in colon cancer rates is a separate scientific question. You would need data on processed meat consumption at a population level, over time, to see if that epidemiologically explains the increase we've been seeing. I don't know if this data exists and kinda suspect it would go the other way, but that's what the scientific method is for.
One major element in this is the rise of earnings from pass-through income. Self-employed or nearly self-employed individuals who would have been counted as employees of their small businesses 30+ years ago increasingly take "profits" from their business rather than "wages," even though they are the same thing. The "profits" get tax advantages. This makes labor share decline despite dentists, consultants, etc. still doing the same amount of work and taking home the same pretax income. See: https://www.ericzwick.com/labshare/labshare.pdf
By this paper's own conclusion, this phenomenon explains 31.9% of the decrease in recent decades. That's significant, but also means that most of the decrease comes from somewhere else.
Migration, outsourcing/deindustrialisation, automation, rising inequality (after an insanely cash printing bout during covid went mostly to the top) would be my guess.
At the center of their story is a quiet revolution in the American economy: the rise of a particular kind of private business. A few decades ago, these businesses collectively made far less money than Corporate America. But by 2011, they were generating more income than all traditional U.S. corporations combined — and accounting for most of the rise in the share of income flowing to the top "one percent."
Over the previous few decades, this sort of private business had — quite privately — taken over the American business world. In 1980, pass-through businesses generated about one-fifth of all U.S. business income. By 2011, they generated more than half. Move over, Corporate America. Hello, Pass-Through America!
> “Pass-through” businesses like partnerships and S-corporations now generate over half of US business income and account for much of the post-1980 rise in the top-1% income share.
Any LLCs and PLLCs (physicians, attorneys, lawyers, accountants, architects, etc.). An owner of a LLC cannot be an employee of it and therefore is pass-through.
Amazingly, when this (IMHO quite good) data leaked, Moderna stock took a huge drop: https://finance.yahoo.com/markets/stocks/article/moderna-sto...
(Seems like people were expecting absolutely incredible, "cure for cancer" results and had already bid up the price a lot in advance.)
Not a huge surprise given the absolute face ripping jump MRNA had when the vaccine was first announced. The ~$20B company jumped 174% overnight, and then climbed another 70% over the last two months, now only dropping 18% on this news.
To illustrate how much they've gone up, this 18% drop is just slightly less than their entire market cap in June (four months ago)
When it clicked that you meant MRNA the ticker symbol, it also just clicked for me that the name Moderna is a play on mRNA. Not sure why I never noticed that before.
Like the FedEx logotype arrow, now I will never unsee it.
I'm way out of my depth on this topic, but my understanding is that studies have shown that several currently approved mRNA vaccines cause a similar reduction in these cancers. Moderna's goal with this trial was to show their tailored vaccine outperformed a COVID vaccine (for example), and my assumption from the stock dip is that smarter people than I were not convinced.
> Moderna's goal with this trial was to show their tailored vaccine outperformed a COVID vaccine (for example), and my assumption from the stock dip is that smarter people than I were not convinced.
The trial result is excellent - anyone ‘not convinced’ was not living in the realm of typical results.
Please note this has about nothing whatsoever to do with COVID. It’s probably best not to comment on technical topics if you have no relevant experience.
This has everything to do with mRNA vaccines effects on cancer reoccurrence. The COVID vaccine just happens to be the most common and therefore most studied.
Does anyone know what is happening to the company eMudhra? Are they being sued into oblivion? Taken over by Indian government? Or just doing business still?
They are an oligarch business. What would happen if X had this fuckup in the Us is the easiest way to answer all your questions l. Nothing will happen.
I'm not at all anti-AI, but I'm still holding my breath to see real scientific contributions coming from modern (LLM/CoT/agent) AI. Much of the premise behind "AI will make superabundance a reality" hinges on getting AI-driven science that affects everyday lives Anthropic's quasi-CRISPR-like discovery did not seem super compelling, and that is still the best I have seen. If anyone has more heartening stories that could convince me to be an optimist, please do share ;)
What I think the parent post is missing is that breakthroughs in science don't immediately translate into breakthroughs in engineering and even less so into economically viable products.
The distinction for many people is that math and cs feel like very natural domains for LLMs (and importantly, domains that enable quick iteration and verification). Much less applicable with eg biology and other fields that require lots of physical experimentation.
(in)Conveniently those are also the fields where most ordinary people would experience the most effects from accelerated progress. Dario famously promises potential cures for cancer and dementia.
I think there's a pretty clear distinction between math and science. The former builds theoretical models of what certain axioms and assumptions imply. The latter builds actual models of what we see and measure in the real world.
Advances in math will probably result in advances in science, which in turn will result in advances in engineering (which is probably where the average person sees an actual benefit in their day to day life). But it's not automatic and a lot of the hand wringing by mathematicians about the AI math results include "is this (AI) method of finding proofs actually going to result in as many of those downstream advances as the old fashioned way?"
(I include theoretical CS as a subfield of math - and believe the S in it is a misnomer).
I have a feeling that many more fields are utilizing AI and having some success with it and we just don't know about it in our STEM bubble.
On the other hand, you could downplay the math findings a bit, since it didn't further our understanding of mathematics just yet, only provided proves to things we didn't have proves for.
AI has an incredibly long history of contributing to science and engineering. Some highlights:
Gerard t' Hoofd (under Martinus Veldman) proved in 1971 that Yang-Mills gauge theories are renormalizable, using a rule-based AI (LISP-styled but manually written in assembly) called "Schoonschip" (I'm guessing called that because there were several failed attempts that went before and failed). This program was an AI in the sense of a search algorithm searching symbolic proofs. It got the 1999 Nobel prize in Physics.
This was hugely important because first, it showed that it was possible to make the Standard Model of physics and it also helped beyond that by showing for a lot of (at that point considered) impossible theories exactly how to make them work (meaning not just a proof that it could be done, but a long list of "if you have problem X, do Y" recipes). One of these became first the "electroweak unification", then the standard model.
Hao Wang proved that the logic of "Principia Mathematica" was actually correct using another symbolic proof generator. His efforts were also the start of many other such programs that contributed lots of stuff to mathematics that nobody sane was ever going to do, such as finding all the higher-order versions of the quadratic formula (there's a lot of them).
At Stanford university, tens of thousands of molecules were found in 1965 by having an AI, this one was what's called an "expert system", evaluate mass spectroscopy data and combine it with chemistry knowledge in the form of rules about what was possible or not possible and if only one option remained, spit it out. It almost doubled the sum total of our chemistry knowledge if counted by known molecular structures. It was later adapted to make mass spectroscopy useful in finding the composition of samples.
Then there's Alphafold, first a ConvNet (Resnet+Convnet to be exact), then switched to the transformer architecture, which gave use the folding of just about every protein we have ever found, and even more proteins that we've never even found. Nobel prize in Chemistry 2024.
If you are limiting yourself to modern whatever, you are not going to find that a lot of science that affects everyday lives. Between the first results and practical applications, it can take many years. There is a reason Nobel prize winners tend to be old.
Less modern AI (aka. machine learning) is used all the time in science. I don't know of any commercial breakthrough yet, but there are some promising developments, like in antibiotics. If it materializes, that would be a very big deal.
I think maths is really the only solid case so far. I do wonder whether the big early contribution to experimental science will be in speeding up the scientists conducting it, at least until some non-negligible boundary in simulation fidelity is crossed.
There’s been a tendency since well before LLMs for AI demos to focus on “here’s a new problem we made up that it solves that you could imagine will soon transfer to an existing real problem” as opposed to “AI solves X”. This has been an ongoing challenge, it does cool stuff and looks so promising but has been very hard to harness for useful work. It’s still going to take time before the hype dies down and we see what’s left.
I don’t think it’s going away, LLMs and other ML stuff will no doubt remain part of people’s workflow, but I also see no evidence for superabundance or anything close to it.
Saw a post recently about how AI agents were used to check if papers had flaws in their conclusions and it found 15% did, that kind of auditing is already a massive massive advancement for science
As a fellow cancer-haver, I would give a piece of proactive advice for those (in the US) who do NOT have cancer or even suspect they have it:
Find a decent primary care doc who is not impossible to schedule with. Someday, if you do have a problem, the primary care doc will be able to send you off for scans, etc. much more easily when you are an existing patient. Getting appointments as an existing patient is much easier.
Just like many of us in the US grew up with shop class (where you learn to build and repair things) and home ec (where you learn to save money by doing things yourself), we should have classes in middle school on how to work within the medical system.
It took me decades (and a ton of advice from my wife) to understand how medical systems work and to get the results I want. Having a good relationship with your PCP is invaluable.
It also helps that your history with the doctor will help you build trust. If you have the same doctor for years and you only went twice for symptoms (that was treated by specialists), then your doctor might redirect you to a specialist in no time as soon as you have any new symptoms.
I'm ready to blame the current admin, federal funding cuts, and cuts to immigration, but we all do need to check that the year for this change is clearly 2024...
(But I am also ready to be even more depressed by 2025 stats!)
This battle was lost 20 years ago, and to reverse it you would need to go back 40 years to prevent US industry from outsourcing to China after it joined the WEF.
You can't divorce engineering from manufacturing, because designing better stuff heavily favors those who also make the stuff. The US was convinced otherwise by economists who don't believe in nation-states, because shareholders correctly saw that they could make massive profits by paying Chinese wages rather than American wages. But now China builds more ships in a year than the US does in a decade, and all of a sudden, the chickens have come home to roost. It will take generations for the US (and indeed the West in general) to regain what was given away, if it's even possible.
> The US was convinced otherwise by economists who don't believe in nation-states
You mean economists ultimately employed by the corpo ownership class, who were using those "beliefs" as cover to put money into their own pockets for shipping entire production lines overseas. Of course the corpo ownership class hasn't sat still - now that the jig is up, they've moved on to the next scam of destroying what remains of our distributed economy so they can continue centralizing. They've even come up with revanchist political movement based around rallying cries that would have helped the common person iff done decades ago, to make the average joe think they're finally being listened to...
You'll need to be a bit more specific in your claims here, because I'm not following. What is being centralized? Because the last 40 years has been about decentralizing supply chains and manufacturing. What political movement are you referring to, and how are large corporations and the wealthy benefiting?
I’d wager it didn’t happen due to the advice of economists who don’t believe in nation states. What happened is the natural conclusion of optimizing for maximum profit and giving capital (read i.e. corporations) the means to do so.
Any attempt at course correction is now labeled with “government overreach, socialism, communism”, etc. in an absurd way.
It's both. Governments correctly realized that you don't outsource technologies that are critical to your defense toolchain, which is why Boeing still makes planes in Everett and not in China. The oversight was not realizing the extent to which all technologies feed into one another. Eventually, you're trying to get electromagnetic launchers working on your aircraft carriers, and you're discovering that you don't have that capability, because administrations 30 years ago let electronics manufacturing go to China. So not only do you not have the capability of doing the thing that you wanted to do, but your adversary has reached a level of electronics manufacturing that your country never achieved.
It's treason if you or I leak secrets to China, and I'd argue that it would also be treason if Lockheed or Boeing wanted to make jets vital to US military interests in China. But if you sell public assets that are subsequently bought by the Chinese, or you move manufacturing that feeds the logistical supply chain, and subsequently erode local capability, that's apparently fine.
The market will always seek to maximize profits, but it's on the government to actually bat for its own sovereign interests. It's that second part that has been lacking, hence why I said in my previous post that this stuff was given away. It didn't need to be stolen.
> The market will always seek to maximize profits, but it's on the government to actually bat for its own sovereign interests.
True that! But the US government is defanged (where it matters), lobbied to death and captured.
Also you never know what could one day prove to be critical to sovereign interests. It’s not one industry. It’s all of them together at the same time, from building the screws to hold your phone together to the advanced chips that AI runs on.
> More than 7,800 research grants terminated or frozen. Some 25,000 scientists and personnel gone from agencies that oversee research. Proposed budget cuts of 35% — amounting to US$32 billion.
> These are just a few of the ways in which Donald Trump has downsized and disrupted US science since returning to the White House last January. As his administration seeks to reshape US research and development, it has substantially scaled back and restricted what science the country pursues and the workforce that runs the federal scientific enterprise.
What number am I supposed to be looking at in that cbp.gov link?
I saw "Total CPB Enforcemnt Actions" yearly numbers for inadmissibles, expulsions and apprehensions (as per the footnotes). Are those the numbers your are referring to?
I don't get it. Weren't those the waves of people after the pandemic, the numbers showing how many were turned around?
There's a legitimate border between Mexico and the US.
People are expected to cross it; I've done it myself. 11M crossing that border sounds like a number that could be correct of the amount of unique people that cross it.
There's a legitimate war between Ukraine and Russia.
People are expected to kill; I've done it myself. 1M killings in that war sounds like a number that could be correct of the amount of unique people that killed in it.
>People are expected to cross it
People are expected to cross it legally. Congrats, you played yourself.
Ok, but how do the economics of this work? Based on its settlement, Anthropic paid an average of $3000 per work they scanned based on their settlement (https://tech-insider.org/au/anthropic-copyright-settlement-2...). They and OpenAI pay billions per year for a mix of experts and normal people to label or create data. Why would they continue doing this if the value of this is immediately copied by open models? If your goal is to end the economics of generating and buying data for AI (and I recognize for some people this is really the goal) then sure, but if you want AI for various subfields of interest to continue improving then it's not workable.
Back when people made arguments for software privacy, the argument was usually "big business will still pay and consumers wouldn't have paid anyways so it's ok for us to pirate" - I actually think that was fine for business software but terrible for indie games, whose market was 0% businesses.
But in the AI case, it's not like they get to keep some of the value of their investment - it all gets cloned into models that businesses and consumers alike are happy to use. If someone knows how labs could continue to fund data creation and acquisition in this model, please do share!
They can’t they’re literally fucked, and it’s not society’s problem! The whole world doesn't have to bend over to make sure a couple of lunatics who believe they are building a doomsday weapon also have a viable business model
Somehow people who think open models will lead to infinite abundance and people who think open models will kill AI development are both liking this post.
> You're basically arguing that a criminal syndicate must be allowed to continue and we're required to make their business model make sense?
This is how Uber worked. They didn't just break the law in different countries, in several they actively misled government/law enforcement investigations. Google "Greyball".
Oh I'm aware that they're ~all assholes and many have gotten away with worse. It just seems like a poor argument that we're required to make it happen for them.
Surely if you hoover up every book in existence to feed into an ai model you must be extracting more than 1.5B in value. If not then it’s not a viable business.
I uninstalled basically all of these EXCEPT youtube, and that's what I struggle with sometimes now. I find so much great long- and medium-form content on Youtube that I want to keep it around. But I have to admit that I can sometimes fall down a time-wasting rabbit hole with shorts.
The Youtube app now has a "shorts feed limit" under "time management" that will limit your access to the auto-scroll shorts feed to a certain amount per day. Worth checking out!
By putting AI into every product I think Google has made a tactical error on YouTube, since the “summarize it this video” feature is helping me spend far less time watching rage bait political content.
I try to pressure people into just turning off the absolute majority of the social media / algo type recommendation stuff on youtube. I still "use" youtube, but my experience is night and day compared to the typical usage, I have my sidebar with a handful of creators i care about, tiny blue indicator next to their name if they have a new video i haven't seen, just like the normal UI. I think this portion is vital, it removes the "clickbait image" meta on youtube, I have to make the first move and say "I wonder what {user} posted".
So i pretty much see, search bar and that text sidebar on my main screen for youtube. Its absurd seeing the standard youtube ui, after using it like this for a couple years now. This also just really really tightens who i follow. If i find myself clicking through to their profile and seeing what they posted and deciding not to watch, i consider that a waste of my time and after a handful of times i might just unfollow entirely.
"The data showed that the age-adjusted incidence rate fell from 55.2 per 100,000 in 2000 to 36.7 in 2022, then rose to 38.3 in 2023."
If you would like to advance a theory that this is because of a specific environmental change, your theory should cope with the fact that the rate was MUCH higher in 2000 and the rise described here is is 2023. Increased screening is said to be a likely culprit in this case for middle-aged adult prevalence but not for older adult prevalence, because screening has increased somewhat in the middle aged groups.
I am personally dealing with colon cancer, and one of the incredibly annoying things about the awful disease is the number of truly clueless people who use it to advance some culinary agenda they believe in without evidence.
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