basically every growth process in the body can be induced by chemicals. and so now people are starting to take some of these chemicals. we will see how it turns out
We were in a lockdown, and Congress voted for multiple trillion dollar stimulus' financed by debt. Refusing to "print money" in those circumstances is just asking for a worse Great Depression.
A crisis prevents people from earning money. No money means nobody buys anything. Nobody buys anything means no company can now sell stuff, so no revenue. Companies start closing down, so there are even more people who cannot earn money.
The government can print money and inject into the system. Some people have money so they continue to buy stuff but maybe at a slower pace or less amount. Things also can get expensive but it is not a total collapse.
one of the big problems of the great depression was banks went bankrupt left right and centre, and took everyone's life savings with them. Also as a lot of banks generally hold mortgages in their portfolio, so when a bank collapses it means that mortgages all get fucky too.
So the mass printing of money meant that banks didn't collapse.
It also meant that a fucktonne of cash went into the hands of the uber rich.
This is one of the reasons safety nets on savings exist in both the USA and in Europe (and probably other places as well about which I'm less informed). Even so, the tacit understanding is that this is more about preventing bank runs than about the practical effects on the currencies involved because it could very well be that that insurance will pay out in money that is worthless.
Why did the fed raise interest rates? To soak up some of that cash. It was too slow, but this is exactly the sound money policy that everyone expects. You loosen cash (what you mistakenly call printing money), when you need investment, and tighten cash when inflation and risk taking is out of control.
a sound response to some of the worst fed decision making in US history. they essentially ruined the housing market, priced out a generation of younger buyers, which is now crushing fertility rates, savings, and more
Investment real estate ruined the housing market. All of a sudden housing prices are expected to grow year over year as an investment. As more and more growth expectations were applied to housing, public policy (including zoning) changed to protect those expectations. Is it any surprise that there came a point at which it became too expensive?
Once problem we need to solve is how to unwind housing prices without financially ruining honeowners whose house is their primary/only wealth. Of course this problem is even more severe in areas of the country that are becoming uninhabitable due to changes in climate as it drives down demand.
covid money printing was some of the worst fed decision making in US history. they essentially ruined the housing market, priced out a generation of younger buyers, which is now crushing fertility rates, savings, and more
actually, llmslave, it was a very good decision. It's better to have mild inflation than widespread unemployment. But also, the fed's actions contributed comparatively little to the inflation we experienced. Globally there was a huge drop in supply, which caused prices to jump everywhere, not just in the US.
The government acted as if the pandemic was happening in 1990, when everyone either worked in person all the time, or nothing worked.
Instead, the golden geese of the American economy (the actual golden geese), simply stayed home and worked from their laptop.
This created a situation where people were getting their regular paycheck, plus getting a multitude of stimulus on top of that. There were many making $100k+ salary, not paying rent (rent moratorium), not paying student loans (student loan moratorium), and not going out to do anything, resulting in having huge pools of cash laying around. If you had a mortgage, you got to refi at 3% and dramatically cut your mortgage bill. I won't even get into PPP loans either, everyone knows the story there.
I could write pages and pages about this, but the short of it is, we thought we need a wheelbarrow of money, but technology meant we only needed a jug of money. But we still got the full wheelbarrow.
Its the 'kept printing' that is the problem with the story.
There was a surge and a pull back.
Post-COVID Tightening: After this historic surge, the Federal Reserve began "quantitative tightening" in 2022 to combat inflation, slowing M2 growth to near zero and eventually reversing it.
This was arguably largely offset by the actions of the treasury's increased short duration issuance (>1 Trillion in t-bills) combined with draw-downs of the reverse repo facility[1] instead of from banks. It's difficult to tell exactly how much money winds it's way into the economy without using proxies - for example credit spreads[2] or NFCI[3] which indicate loose conditions, which don't show much evidence of post 2022 QT's impact.
Or in other words the data seems to show the loosening effects were more powerful than the tightening ones. Now that the RRP has been drawn down balance sheet growth will likely occur.
>slowing M2 growth to near zero and eventually reversing it.
The M2 money supply went from 15.4b at the start of 2020 to a peak of 21.7b, before slightly reversing to 20.7b. Then they just continued printing. Now it currently stands at a record high of 22.2b. The dollar is more diluted than ever.
its a tight rope. shrinking the money supply also has downsides.
Summary of the Policy Reversal
Period Policy Action Balance Sheet Impact
June 2022 – Nov 2025 QT (Tightening) Shrank from ~$9T to ~$6.5T
Dec 1, 2025 QT Ends Runoff stops; maturing assets reinvested
Dec 12, 2025 – 2026 Reserve Management Expansion begins via T-bill
purchases
By December 1, 2025, the Fed officially halted QT after reducing its balance sheet by approximately $2.4 trillion. The following factors forced the reversal to expansion:
1. Liquidity Squeeze and Repo Market Stress
As the Fed drained cash from the system, bank reserves fell toward "critical thresholds". This caused stress in the overnight repo market, where banks lend to each other.
Spiking Rates: Key short-term lending rates, such as the Secured Overnight Financing Rate (SOFR), spiked above the Fed’s target range, indicating cash was becoming scarce.
So basically the amount of time it takes for them to scrape existing US models and then train on that data. China doesnt have any intellectual property, they are just stealing
China produced foundational technologies (paper, compass, printing, gunpowder etc) long before the US existed, the US later built on global inventions too. Same here, LLM progress is cumulative and international, today's leaders won't be tomorrow's by default.
All frontier US models are closed weight. It's great what Chinese are doing because open weights help everyone. Also there is a lot of research thanks to these open weights, look how much research is being done using Qwen models in US (Microsoft etc) and in the rest of the world.
Multi-head Latent Attention (MLA) + DeepSeekMoE? plus an auxiliary loss free load balancing strategy and multi token prediction objective to train/infer huge MoE models efficiently.
Have you seen Manifold Constrained Hyper Connections (mHC) paper from a few days ago from Deepseek? Projects residual connection space onto a constrained manifold to keep identity mapping properties while enabling richer internal connectivity, so basically it eliminates a huge problem.
They also released A LOT of training tricks and innovation around optimizing inference and training.
As to other industries:
"China leads research in 90% of crucial technologies — a dramatic shift this century" [1]
And here's[2] "China Is Rapidly Becoming a Leading Innovator in Advanced Industries", a big report on where they lead and how.
But companies like OpenAI collected a lot of data about the artificial intelligence through platforms such as OpenAI GYM, and people voluntarily contributed and published their code/models there because they believed that this was not a commercial organization and would act for the benefit of all mankind.
This is a complete myth. Human populations are not homogenous, gene pools that relied on agriculture for the last 10k years are completely different than hunter gatherer populations. You have been lied to
Which myth? I have genuine trouble understanding what you disagree with.
Industrially processed food is a very recent invention. I'm not talking about modern fad like the Nova classification here. I don't care about bread as long as it's made with water, yeast and flour. I just don't want my food to contain any recent additives.
My take is basically that if it was fine a thousand years ago, it's probably ok-ish minus everything we know now to be poisonous. The blind spot is obviously plant selection and modern varieties being different but well, that's ok, nothing is perfect.
It all depends on how you prompt. and the prompt system you’ve setup.. when done well, you just “steer” the code /system. Quite amazing to see it come together. But there are multiple layers to this.
Yes, I personally think so. In the hands of an experienced user you can crank out work that would take days or weeks even, and get to the meat of the problem you care about much quicker. Just churning out bespoke boilerplate code is a massive time saver, as is using LLMs to narrow in on docs, features etc. Even high level mathematicians are beginning to incorporate LLM use (early days though).
I cant think of an example where an LLM will get in the way of 90% of the stuff people do. The 10% will always be bespoke and need a human to drive forward as they are the ones that create demand for the code / work etc.
The problem is many users are not experienced. And the more they rely on AI to do their work, the less likely they are to ever become experienced.
An inexperienced junior engineer delegating all their work to an LLM is an absolute recipe for disaster, both for the coworkers and product. Code reviews take at least 3x as long. They cannot justify their decisions because the decisions aren't theirs. I've seen it first hand.
I agree totally; most people are no experienced, and there is a weird situation where the productivity gains are bifurcated. I have also seen a lot of developers unable to steer the LLM as they can’t pick up on issues they would otherwise have learned through experience. Interesting to see what will happen but probably gonna be a shit show for younger devs.
It seems you've registered this account a couple of months ago only to basically repeat this opinion over and over (sprinkled with some anti-science opinions on top).
great engineering effort was spent to make software at FAANG built on clear service oriented modular architectures, and thus easy to develop for. Add to that good organization of process where engineers spend most of their time doing actual dev work.
Enterprise software is different beast - large fragile [quasi]monoliths, good luck for [current] AI to make a meaningful fixes and/or feature development in it. And even if AI manages to speed up actual development multiple times, the impact would be still small as actual development takes relatively small share of overall work in enterprise software. Of course it will come here too, just somewhat later than at places like FAANG.
No it doesn’t. I’m not trying to make a point about vaccines, just that the study is a population study and so shows benefits on average to a population.
If the vaccine killed 1/100 people (again I don’t believe this but it’s the internet) but made the other 99 immune to dying over the 4 years, it would look really good on average even if it was directly responsible for the deaths of 1%.
This comment helps me understand how folks see "your taxes will go up $10k but you won't pay $20k in health insurance premiums" as a hit to the pocketbook.
Well, if say the vaccine gave 1/100 fatal lung cancer then a population study would show a decrease in covid deaths and an increase in lung cancer deaths though.
It's only the case if the vaccine gave everybody slightly higher chances of dying from everything that it could hide in the weeds.
So in this specific example we can see from Table 2 that deaths/1 million are just lower for everything in the vaccinated so it's not the case that it lowered one kind of death drastically at the expense of another.
Don't those 99 enjoy being alive despite all of the things that would have killed some of them had they not taken the vaccine? If "some" is at least 1%, that sounds like an individual benefit to me.
If you take the vaccine, you have a lower chance of dying over those 4 years. You also have an infinitely higher chance (specifically 1% vs 0%) of dying from the vaccine, but that doesn't change the previous sentence.
For vaccines like the measles vaccine where it can entirely stop the spread in a vaccinated population this can be true until enough people think this way that measles starts spreading in your vicinity.
But with Covid-19 vaccination wasn't able to eliminate its spread so it mostly is about protecting yourself rather than protecting others.
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