The main argument builds on the assumption that the economy is a zero sum game when it clearly is not. Just because we invest these ressources in AI does not mean we could mobilize the same capital for other pursuits.
Precisely AI is being built out today because the value returned is expected to be massive. I would argue this value will be far bigger than railroads ever could be.
Overspending will happen, for sure, in certain geographies or for specialty hardware, maybe even capacity will outpace demand for a while, but I don’t think the author makes a good case that we are there yet.
> "... builds on the assumption that the economy is a zero sum game when it clearly is not"
Be cautious making assessments as to compounding effects; while it remains the critical attribute, the compounding nature of a system is not always obvious. For example, the author is correct that financing for AI CapEx is starving other fields of investment at least in the short term.
In addition, the massive investment may be overbuilt, but then likely will end up being useful long-term. This is just as the initial buildout of the internet to power pets.com was a bust at the time, but then led to Amazon, YouTube, Zoom, etc and in fact led to us being able to weather Covid better than you'd have expected.
The modern internet came from folks getting connected over-exuberantly based on near-term returns (with a lot of investors losing their shirts) but then humans figured out what the actual best use of the technology.
> Just because we invest these ressources in AI does not mean we could mobilize the same capital for other pursuits.
No offense but you sound naive here. This is exactly how dry powder manifests in PE/VC and is even predictable under cash rich corporate regines via M&A.
Trends like this are ripe for acceleration under favorable environmental conditions like high interest rates. Not to mention, a lot of it develops out of peer pressure.
Sometimes when your job is to deploy capital, you just deploy it. Of course you try to put it in the best possible places. But when those are few, well yeah... This happens.
I am rereading a novel from French author René Barjavel: “the ice people” on this exact theme. Scientists in the South Pole discover an ancient civilization 900k years old. Its also fun because he anticipates the near future quite accurately from 1968 when he wrote it. Well worth a read.
https://en.m.wikipedia.org/wiki/The_Ice_People_(Barjavel_nov...
I use macfan control to force a lower fan rate which throttles the cpu. Battery is significantly better (feels like 2x at least) for mundane tasks. I can still watch videos, browse and do light work without feeling any slowdown.
Great point. It seems to me the mechanics of competition are at play to some extent in open source: ideas compete against each other, the better ones prevail, and contribute to a better whole.
Abstractions have other purpose than deduplication. They make it easier to reason about your code as well. It might be the smartest thing sometimes to abstract away the first occurrence in a method imho.
Actually if it’s simply a put the profits on the hedge stand independently of what they actually produce. They could lift the hedge at any moment or take the opposite bet to offset it regardless of their actual production. It seems to me it would be more advantageous to lift part of the hedge at a profit and then produce less since the price is way under the cost of production.
Unless them producing more drives the payout on the puts up more than what they pay for production (minus world prices).
Oh, and of course, this is all politics. They are not just maximizing profits, but they also have to worry about the optics of firing redundant workers, if they stop production.
I second this. I freelance as a part time CTO and this has been my favorite appproach to hiring devs. A paid project goes a long way to establishing a good work relationship and gives both sides most of what they need to decide if it’s a good fit longer term. I also always offer my clients to start with a small contained project to see if we’re a fit. This ends up saving a lot of time: the risk is low for the employer, and the developer gets paid their market rate and has a chance to show that they are worth it. It’s then really easy to decide if we should continue working together or not.
Precisely AI is being built out today because the value returned is expected to be massive. I would argue this value will be far bigger than railroads ever could be.
Overspending will happen, for sure, in certain geographies or for specialty hardware, maybe even capacity will outpace demand for a while, but I don’t think the author makes a good case that we are there yet.