You assume that the people who are at the top of the organizations generating said wealth will have any incentive to do that. Look around the world at the petro states for examples of a highly capital intensive industry generating money that subsidizes the rest of the economy.
If you think that people won't have work and therefore no money to buy anything, there will be no wealth- not for the people and not for the riches. The value of Google or Tesla go to zero without masses of people paying for their products.
1. AI seems different here, American AI companies doing better seems to result in the rest of the American economy doing better as intelligence is generally productivity increasing. Plus it's not bound by physical scarcity as oil. It feels more like cloud computing or electricity
2. Even if we were to assume an analogy to a petro state, it seems like we as a society can decide if we go the route of Norway or Venezuela
Are you aware of any reputable study that supports this? Everything I've seen, coding included, has productivity at a net neutral at best, with large cost increases due to LLMs.
This is probably the best one for coding? The two main findings are that developers didn't want to do tasks without AI (implication being that they would find it too tedious) and for the tasks that were measured, there was a speedup (and more of a speedup if you had more experience with AI tools)
Unfortunately "productivity" is very hard to measure directly. I prefer looking at how much money companies are paying Applied AI companies (a lot) because in aggregate, that meant these companies justified ROI vs. OpenAI/Anthropic directly, and sufficiently enough that large enterprises are willing to go through the time and money to spend on a vendor. It's not foolproof but it dampens the effect of companies tokenmaxxing their Codex/Claude Code to look productive.
The problem is, it’s not like being a pm or manager, the people you work with generally aren’t pathological liars with severe amnesia. The anxiety you feel is because there is a system that is very difficult to control reliably injecting entropy into a system which your paycheck depends on your ability to make it stable and ideally provably correct, that should make you feel anxious.
But the people who want to do local inference are putting some amount of value on privacy that’s not captured by the raw monetary value so just comparing the price is somewhat beside the point, it’s also true that, if you have eg a Mac and you use that as your main computing device then you would have spent money on it anyway, so you can’t even really compare its value to spend on something that’s not general purpose.
That's a lot of assumptions. I think there are also people buying new hardware specifically for this purpose, and their motivation to do it is thinking it will be cheaper in the long run. Privacy is not necessarily the motivation.
My overall opinion is that the smart thing is not to upgrade to the maximum memory for AI purposes. It's worth quantifying how much extra we pay for privacy.
It’s shocking how close this feels to claude, obviously it's much slower, but I don’t know that it’s significantly dumber. Interestingly the imatrix quantization seems to be better than whatever quant the zdr inference backends on open router are using. It was self aware enough yesterday to realize that it’s own server process was itself without me telling it, which is not something I’ve ever observed a local model doing before.
In my (obviously anecdotal) testing, DeepseekV4 Pro was better than Sonnet at coding. However, it is much slower, but also many times cheaper, especially with the promotion right now.
You pay per api call but you will be challenged to burn trough 20$ per month. 24/7 usage for single agent will probably cost you around 100$ per month. It is very efficient especially with modern harnesses.
I racked up $30 in 3 days, but I did A LOT of refactoring. Got my projects really buttoned up and now I’m sipping tokens with codex again. Have been more like $1-2/day with deepseek since that initial swarm. With max effort.
It’s especially great that you don’t have to worry about hitting your limit and being stalled.
Sure, ETA for a nuclear power plant is ~15-20 years from now, wind is ~5-10, solar is 2-6, natural gas is 2-4 years. Data centers take 18 - 24 months. Even if build out for power infrastructure needed had started when the demand became apparent (which, it’s not clear that it has done). You should still expect electricity costs to inflate due to the ~100GW of additional demand that has been announced, because there is no way to build the power infrastructure in less time than it takes to build the additional data centers. It’s also not clear that there would be enough elasticity in the supply chain for building any of these generation methods that you even could strike ground on increasing us electricity production by the ~10% needed over the given time frame. The reality is, there is no way to build all the additional data centers without significant inflationary pressure, that will be borne by everyone except the well connected hyperscalers with excellent lobbyists unless average people actually realize that fact and force their dealing with the relevant municipalities and grid operators to be transparent.
Fine! So let's get started then! I don't care about data centers. I don't care about AI. Maybe it's here to stay, maybe it's a passing trend. I care about humans, and human prosperity.
Human prosperity - ours and our grandchildren's - is to a large degree determined by how much power we produce. So let's get started producing more.
The best time to have built a power plant was 20 years ago. The second best time is today.
The last time I asked the same question here, user dwattttt finally pointed out[1][2] to me that there is a significant difference: wfmo can actually acquire semaphores in addition to waiting for them, which poll can't do in a non-racy way and efficient way. It can also do rendezvous synchronization (i.e. signal-and-wait).
Because we have offshored most of our heavy industry. For national security reasons we now have to re-industrialize. Plus a lot of the infrastructure for transportation and heating is gradually shifting off of fossil fuels. So electricity usage is going to go steadily upward for the next couple decades. This would be necessary even without AI data centers.
I think we reached peak "electricity" for the consumer decades ago. You know...when our TVs were a giant electron gun pointed as a phosphor screen whilst the room was lit with a filament of 3000 degree tungsten.
...and Americans were getting like 200HP out of a whole ass 7.whatever L v8 ahaha.
Sure, but, given that, does it not seem like the conclusion is: if you have something that could in principle be reverse engineered by a competitor with more compute, they can and will steal it, because the only constraint is roi.
Because those are very capital intensive and don’t skew towards germanys existing competitive advantage in diesel engines and high precision heavy engineering. Same reason most places don’t try to compete, it’s cost prohibitive to do so.
