I am actually hoping someone there studies such interventions the way they did with CMU's intelligent tutor — which if I recall correctly did not have net strong evidence in its favors as far as educational outcomes per the reports in WWC — given the fall in grade level scores in math and reading since 2015/16 across multiple grades in middle school. It is vital to know if any of these things help kids succeed.
I have a noob question. How can developed economies where populations levels have plateaued continue to be expected to post positive GDPs (and therefore add net new goods and services) yoy?
Homes as assets should pass on, higher cost services of today would be replaced by lower cost which only temporarily would increase units sold(but should eventually plateau because #units/person is not going to change). No component of the GDP will move.
If the fertility rate of developed economies is less than 2.1 then there should be wealth and asset accumulation among the younger people over time. The demand for newer goods and services from the people who get richer is inelastic: most goods and service's prices dont matter to the rich they buy them any ways, and it continues to keep becoming more inelastic.
So within like a several years the demand should just collapse as wealth accumulates a lot and people work less and become more price insensitive. Immigration is set to remain low to developed nations for the next 3-5 years.
This seems to be quite evident in Japan and EU already(though in the EU if you adjust the productivity for work hours the GDP becomes same as America's).
So why do people assume developed countries would even buy this much more new stuff. 1.5 trillion$ worth of new things over the next 5 years?
GDP does not require that the goods or services were sold for money. GDP measures the market value adjusted to constant quality of all final goods and services produced. GDP can grow even with fewer workers, fewer hours, fewer buyers, and fewer units sold.
So the way I understood it, productivity, efficiency and quality gains can increase GDP year over year.
Say we are a country of 1 person. If that person can make a car in 2025, but in 2026 manages to make both a car and a house, the GDP has more than doubled. Doesn't matter that nobody paid the money for them.
Another weird thing is, say that 1 person country makes a car in 2025, and in 2026 makes a similarly priced car, if the car is higher quality, it counts as a higher GDP, because they'll measure its value as greater than last year's model, even if it sells for the same price, because the old model would now be worth less.
I have a theory (actually I wanted at some point to write more seriously about it) about how GDP also expands by consuming life itself. If you're burnt out, or don't have time to see friends and are depressed have to pay for therapy, GDP grows. If you don't have time to care for your children so you have to keep them busy with million classes, or paid for caretaking, GDP expands. If you don't have time or confidence to meet people IRL and have to pay for Tinder, GDP expands. If you don't have time to cook (even if you enjoy it) so UberEats all the time, GDP expands. When you replace public services by extractivist and more inefficient private ones (see healthcare, education) GDP often grows. The list goes on and on. The more every aspect of human existence is replace by a transaction in the market place, the more GDP grows. We replace a variety of motivations to do and to be based of human relationships and affection, by cold self-interested exchanges between strangers.
GDP is a fucked up way to look at life. It's go to way to look at whether a country is doing good, but it's consuming our environment and our own sanity in so many ways.
That's one of the reasons why I think that actually limiting the working hours (bringing it down to 30, and eventually to 20 hours a week) should be one of the main agenda points for this coming century. It's important for our environment, but also for our own sanity.
One could argue that given a sufficiently large GDP, one can make the individual choice to earn less and have more time. But that's sadly not how things work, since having more workforce available also devalues work relative to subsistence goods (e.g., you can't afford a roof without a full time job). Also, individualism is such a powerful ideology in a market driven economy. Maximizing individualism itself can help you get ahead in the marketplace, and spreads through society via marketing, private media. At some point, we even stop seeing how to behave differently than to maximize our own profit. We need democratic instruments outside of the marketplace to steer our society in a way that improves our lives, regardless of what that does to GDP.
But this only addresses the supply side. The demand side has to be buying those two cars. The 1 person country car that one or two car would need to be bought by someone else there is no GDP consumption recorded
> How can developed economies where populations levels have plateaued continue to be expected to post positive GDPs (and therefore add net new goods and services) yoy?
Think about the unsatisfied needs and desires most people have. In extremely low income areas, it may be a roof over your head or knowing where your next meal comes from. Moving up a tier, it might be the ability to send your children to education or better clothing. In wealthier areas it might be things like a better car or higher quality food even though you're not in danger of going hungry. For the extremely wealthy it might be more leisure time, art, and new experiences.
When GDP increases, broadly, those are the areas you see expand. Looking at life today in a baseline American household, the things which are mass produced are far more available and affordable than they were a century ago - in the 1930s households spent about 10-12% of their income on clothing.
Sadly, the rate of improvement for non-mass-produced items like college tuition, medical care, and especially housing has ballooned compared to median income, so life doesn't feel inexpensive, certainly, but GDP has a lot of room to grow in a lot of areas.
Why not? It has been changing forever. It was on a pretty consistent upward trend in the US since there was a US, roughly doubling since 1790, but it has started to decrease in the last few years.
Total GDP can keep rising so long as technologist can improve efficiency through robotics, inventions and scientific breakthroughs.
GDP just describes peoples amount of activity. People will always build bigger buildings or monuments (see egypt pyramids, dubai skyscrapers, cambodia angkor wat). These are actaully not inelastic as megaprojects will quickly hit real limits regardless of the amount of capital. (I can always add 10 more floors to the tallest skyscraper, or 10 feet to the longest wall, or 10 facets to the most ornate church)
There has never once in history been a point where people decieded that they where going to stop innovating or producing permanently. This is equivalent with death.
So the people with the most money at some point will decide to build things which they spend all their money on which increases GDP.
Also the actual "number" of gdp if heavily controlled by USA inflation rates. So we should always look at gdp in regards to inflation adjusted dollars to get a clearer picture.
You would just think there has got to be end to it all... technology needing to increase so much, indefinitely, the imagination falters tbh. Its like we have to become space gods by year 2500 or we are going to go bankrupt as species anyway.
Even if the populations and quantities of stuff sold by weight peak, people can still by fancier stuff - Ferraris rather than Fiestas etc. GDP just measures the amount spent basically.
Your entire premise is simply incorrect, through and through. Discard it entirely and begin again.
You have a hundred people, they have a GDP of N. Tomorrow, their productivity doubles because of a technological innovation. Your GDP is 2N.
Prices matter extensively to the rich and poor. The cost of a given compute capacity has gone from "literally the entire United States can't afford it" to "my lightbulb has this much compute because it's cheaper than choosing a dumber processor".
What happens tomorrow if eg ChatGPT 5.1 performance becomes doable for $500 of tech? $50? Swap this for grain harvesting, waste bin collection, etc if you don't like the LLM case.
No, it wouldn't as the whole reason people were giving Openai that 500 dollars is because they thought they could make more than 500 dollars from it.
So now that value is just shifted into the companies that were going to purchase from openai.
It would just hurt the investors who have exposure to openai/anthropic/google/microsoft.
Much of the value of this AI boom is not from the direct model companies but its from companies which use their technology.
Although the government could be stupid and bail out these companies which WOULD hurt all us citizens and the inflation caused by money printing due to that could cause a recession.
Here's what I think would happen if anyone, by tomorrow, could download GPT 5.1 for free and run it performantly on something like a $500 laptop:
* It would stop datacenter- and other related infrastructure construction, making huge investments effectively worthless for companies like Oracle and Amazon, and of course hurt the construction sector.
* It would hurt the companies you mention, plus a many more including NVidia, likely in ways that would lead to large-scale layoffs.
* It would seriously hurt corporate and VC investors and likely make them much less interested in large investments for quite some time, thus affecting other sectors as well.
* It would seriously hurt index funds and pension funds.
A number of years down the line, if LLMs are indeed capable of significantly boosting productivity, I'm sure we'd see a recovery, but when large bubbles suddenly burst there's usually some pretty serious fallout.
I would offer a stronger more pointed observation, ofen the problem in building a good classifier is having good negative examples. More generally how a classifier identify good negatives is a function of:
1. Data collection technique.
2. Data annotation(labelling).
3. Classfier can learn on your "good" negatives — quantitaively depending on the machine residuals/margin/contrastive/triplet losses — i.e. learn the difference between a negative and positive for a classifier at train time and the optimization minima is higher than at test time.
4. Calibration/Reranking and other Post Processing.
My guess is that they hit a sweet spot with the first 3 techniques.
I think the biggest problem with such classifiers is to actually know what is good data and what is bad data. To take a sample of the data and to recognize whether or not this dataset is a general enough representation of both true and false examples (for a binary classifier) to be able to use it to train a model. Because it isn't rare at all to have data sets that are biased 100 to 1 or more for one of the classes, which contain hints about what class the object is in that isn't in the object itself and so on. You can train until the cows come home on such data but it will never lead to satisfactory results.
So the bias is an issue can be handled in a variety of ways, one which I know to work is to use weights on your rarer class when training. You could also use larger margins to make sure you definitely don't mis-classify the rare class at the cost of mislableling your dominant class — presuming you are ok with it. An example is when doctors order breast biopsies, it happens a lot more than the cancer itself and based on a noisy technique of physical exam.
Has someone done a survey to ask devs on how much they are getting done vs what their managers expect with AI? I've had conversations with multiple devs in big orgs telling me that Managers and dev's expectations are seriously out of sync. Basically its
Manager: Now you "have" AI, release 10 features instead of 1 in the next month.
Devs: Spending 50% more working hours to make AI code "work" and deliver 10.
>.. that LLMs can only solve problems they have seen before!
This is a reductive argument. The set of problems they are solving are proposals that can be _verified_ quickly and bad solutions can be easily pruned. Software development by a human — and even more so teams — are not those kind of problems because the context cannot efficiently hold (1) Design bias of individuals (2) Slower evolution of "correct" solution and visibility over time. (3) Difficulty in "testing" proposals: You can't build 5 different types of infrastructure proposals by an LLM — which themselves are dozens of small sub proposals — _quickly_
Just as a note pressure cookers like the Instapot are rated at 1000wh but they don't use that all the time IIRC — only initially when building the pressure. In simple terms it's like using 1kw for 10 - 15 mins and not an hour. So on average very efficient.
Has someone measured the time for max usage and average usage? Could be a good alternative with a 1kwh lfp battery with a lot of juice left over after pressure cooking(no pun intended)
Fascinating. I do wonder if people with this condition are self selective in some way on how they do things. I also wonder if these conditions describe the level of success they have in a specific field vs a control group.
e.g. as described in the article the example of Phds/Researchers to lean more heavily towards abstractions and rules.
Given the apple v epic ruling about in payment commision outside the app store, I don't understand this. I assume Google would get the same ruling if they tried what apple did, so why bother with walling off if you can't get paid?
At least with 3p app stores they could have Gpay if the app developer wanted to, but now they will be pissed and can't build a 3p app anyway since users can't install it via 3p app stores.
I am actually hoping someone there studies such interventions the way they did with CMU's intelligent tutor — which if I recall correctly did not have net strong evidence in its favors as far as educational outcomes per the reports in WWC — given the fall in grade level scores in math and reading since 2015/16 across multiple grades in middle school. It is vital to know if any of these things help kids succeed.