The 15mg/d they used in that study is just the standard dietary intake (top end, europeans). Looked a number of other studies that also used just regular intake levels as "supplementation". Weird how they all stay small when the no observable adverse effects level is much higher.
>(3) Results: Compared with a placebo, spermidine supplementation significantly increased spermine levels in the plasma, but it did not affect spermidine or putrescine levels. No effect on salivary polyamine concentrations was observed.
Which might be fine if the metabolite is actually the responsible molecule.
Given the concentration, you'd have to drink half a litre of human seminal plasma to match one 15mg supplement pill.
I have no idea what the concentration of seminal plasma is in semen, but even if the latter was pure plasma that's still 135 sessions to equal one pill.
One realization I had is that tech advantage might in fact become a disadvantage. Consider companies that have invested heavily in building a technological edge. Google Translate, for instance, faces challenges as a simple prompt can overshadow its billion-dollar product. Similarly, Grammarly's competitive edge may now rely more on its momentum and user interface than on its underlying tech. As ChatGPT introduces new capabilities, countless products see their technological edge vanish. To illustrate, the introduction of the image input feature means that, with a single prompt, it could serve as a top-tier school homework assistant, a photo-based calorie counter, and a plant identifier all at once.
This dynamic raised into question the viability of ML research as a core business strategy. Take Midjourney, for example. They've made significant strides and achieved dominance with their advanced text-to-image generation technology. But if a product like DALL-E 3, or its successors, could render their entire offering redundant in a few short years, than it's a tricky path for a company to take.
To me, this suggests that the actual "new strategy in the age of AI" is that tech companies need to transition from relying on their tech edge as their competitive advantages, to relying more on more stable moats. For example, the network effects rooted in two-sided marketplaces. It also hints that tech giants like Google, who above all relied on their tech advantage, could face existential challenges in the coming decade. A sort of a win-or-die situation. While companies like Amazon might be in a more stable ground for now.
Midjourney basically used RLHF on their model, so they have a bit of a data moat in terms of human aesthetic preference, but DALL-E 3 isn't bad in terms of aesthetics and its prompt adherence is vastly superior so that preference moat might not save them. They'll need to improve prompt adherence quite a bit to stay relevant.
Data is the new oil in the age of AI. The companies that do well will have products that siphon context enriched user behavior, build a strong brand with user loyalty, and effectively capitalize on the collected data to automate some expensive task. These data collection apps will be designed to break down and gamify tasks in such a way as to maximize the training value of the resulting data stream.
For example, imagine an IDE with an integrated stack overflow type service, where people could do collaborative coding or request help and get answers inside the application. That would give edit-by-edit updates, console output, problems with solutions and user solution preference. The company that owned that data would have a huge leg up on the competition in terms of creating AI software generation tools.
Perhaps a naive question, but why is using plastic for energy good?
When we produce plastic we essentially convert oil into a highly stable form instead of burning it into the air. Essentially, we sequester the CO2 that would've been burnt if that oil was used as fuel. That's a huge benefit of using plastics that we are eliminating.
Natural gas can be a byproduct of oil extraction, but it is also available by itself ("dry gas"). IIRC, most natural gas production in the US is of this kind.
Fracked gas in the US is unusually high in ethane, the substance that is the primary feedstock for ethylene (and then polyethylene) production.
In a world without fossil fuel production, reduced carbon compounds will become more valuable. The cost of making plastic may rise, but plastic itself will become more valuable as a commodity for later use (either as a fuel or a feedstock).
PET is not polyethylene. Synthesis of PET involves a more complex feedstock (in particular, para-xylene to make terephthalic acid.) The other component, ethylene glycol, is made from ethylene.
Ethylene from fruit would not be competitive with other non-fossil sources. However, para-xylene can be made from biomass.
And burying that plastic returns some of the carbon to the ground from whence it came. Bury it deep enough and in a few million years it may be cooked, recycled, back into liquid hydrocarbons.
To be fair, COVID's death rate has such a strong association with (very) old age, that not accounting for it is quite questionable. In the article, Nate mentioned himself that Mormon population is 100x higher in Utah and that's a significant effect. The COVID death rate of over 85 years old is more than 100x higher than the very young.
I'm not questioning the results, just that accounting for age when analyzing COVID is definitely a reasonable question to ask for any conclusion.
Initial constraints like ICU bed shortages and gear scarcity definitely had a basis. But those measure lasted long after the bottlenecks got resolved and the risk assessment became clearer. For example, public schools stayed remote while virtually every private school switched to in-person (even California's governor opted for private in-person schooling for their kids).
The public's frustration is that these prolonged, seemingly arbitrary measures outlasted their initial justification.
ICU capacity was a bottleneck that never got resolved. In the US there was never a nationwide effort to mobilize ICU resources to target hot spots other than an initial aborted attempt to gather respirators for the surge in NYC and send a military floating hospital.
Regional programs were put into place to shift patients during a local surge and to mobilize hallways and other non-traditional capacity. In California once capacity dropped below 10% health orders went into effect.
At the beginning of 2023 and well after widespread vaccination the California statewide capacity was at 24% availability with 7% of beds being taken by Covid patients.
The hospital ship was never intended to take covid patients. The idea was the ship would take non-covid cases leaving ICU capacity in hospitals. It turns out that military hospital ships aren’t great for the general population given bulkheads and the general layout of ships.
In Chicago we also spent millions of dollars building extra temporary capacity. It only got something like 38 patients and was quietly dismantled after one month.
Deaths peaked in 2021 but hospitalizations peaked in 2022. Hospitals were at higher capacity in 2022 but treatment protocols had improved reducing mortality rates. Deaths caught the headlines so people missed the surge.
I wonder if suddenly going from masks and sanitizing constantly to immediately stopping (at least in my country) may have contributed to the sudden jump. Also we were encouraged not to visit the hospital unless it was necessary so many opted not to for almost 3 years.
And most hotels have centralized departments for dealing with it, contacts with extermination agencies, and a single large building to treat, and a very very strong incentive to get it done immediately, lest they lose all business and be forced to shut down.
I obviously don't know the specifics but I'd bet Hilton is a million times more effective at pest management than some 60 year old dude who put up his second home for extra income. To whom does the cost of extermination act as a large deterrent?
FYI, Hilton does not own or operate 99% of hotels with their brand name on it. Quality of management will vary greatly, but I agree that the probability of hotel management fixing the issue quicker is higher than an Airbnb operator.
It’s part of the problem, sure, but only a contributing factor. The story mentions them being found in cinemas and trains, which is uncommon, but they have been in hotels as well.
What's the difference between 0x2e and .?
You can easily transform between representations of data, be that text or binary in any encoding you'd like.
The model input token vector (or LUT index) is still the same. I don't see a difference there.
Dude, you are spewing out random things as if they are fact. Yet you lack an understanding of what IQ is.
IQ is an attempt to measure a general intelligence factor (g-factor). What happened is that researchers noticed that people who are good at some tests tend to also be good at other tests, even if it's from very different domain. E.g. say you are good with math, you also tend to be good in you language skills. This led to the assumption that there is a general factor out there that is shared across all skills (the g-factor). So determining how good you are at math is a combination of your math specific skills + the g-factor. Same with other domains.
How do you extract the g-factor? You measure a large set of people across a cognitive challenging set of tests, and do a factor analysis (statistical technique) to extract a linear g-factor. Each test can have a "g-loading" which essentially calculates what portion of it is due to the general g-factor. For example, one of the tests with the highest g-load is simply hearing a sequence of numbers and repeating them in reverse. This test has nothing to do with "reasoning skills. Yet for some reason you claim that it's designed to measure reasoning skills but not designed to measure "a bunch of other things".
You also claim that IQ varies significantly day to day, but that has not been shown in studies. In fact, IQ measurements tend to be remarkably stable across the person's entire adult life.
Than you spewed up a bunch of unsubstantiated claims about the difference of IQ between a leader and his team.
> Dude, you are spewing out random things as if they are fact. Yet you lack an understanding of what IQ is.
In my previous career, I did quite a bit of research on IQ. I’m pretty sure I have a decent understanding of what it is.
If you take out your straw-mans and overstatements of what I said, then I think you will be able to find research that supports everything I said above about IQ approximately to the degree of confidence that I stated it.
> Let’s make it easy - please cite the research that shows that an IQ gap of 20+ leads to worse leadership results.
Iirc, Greatness: Who Makes History and Why cites some research on this very topic.
There is more to be found — I’m sure you can find it if you try yourself or ask a librarian at a good academic library.
I will also add that you have conveniently ignored the fact that I prefaced that specific section with “imho”. It’s my opinion, and I stated all of those comments as such because I don’t think that there is any unassailable research in this area. There probably won’t be due to the difficulty of structuring a good and replicable study regarding IQ and IQ deltas specifically.
While the overall research is not air tight, there is research that I have done (unfortunately proprietary) that indicates that the “20 IQ point difference” concept is directionally correct (“directionally” because we had to use IQ proxies). Implementing this in organizational restructuring led to consistent measurable improvements at the extremes (which was our focus).
Given your challenging tone and style of engagement, I’m guessing that you’re hellbent on flaming. I’m not interested. As such, I will leave you to your library and librarian to find research that supports the ideas I have stated (assuming you bother to look).
“Leadership and IQ delta” a super interesting topic, but the current trends in psych research and psych funding unfortunately don’t really focus on these areas despite demand from outside of academia (it’s very political in an uninteresting way).
The reality is that it’s very difficult to come by any research that shows that higher IQ leads to worse outcome (which your delta hypothesis claims).
We also know that iq correlated over 0.95 between same person taking the test on a different day, so any claim around daily fluctuation is exaggerated except for outlier cases. Your claims paint a different picture.
