The average person's inattention to nuance could be labeled as "populist brainrot" in this case, and the cases of poor zoning could be used as examples of the issues with datacenters that the average person does not evaluate with the proper attention to nuance.
So are we now at the point in the hype lifecycle for AI, where the crypto bros have learned they can vibecode fake projects to scam people out of money?
We've already had consolidation of education for a while now. Even before all the edutech courses, there were Youtubers educating better than many university professors. 10-15 years ago students were already skipping lectures and just showing up for tests.
The main thing keeping me from making the multi-material jump is the waste. I have a couple Vorons and would love to be able to print with different materials at the same time, but the waste with the current solutions is so egregious.
Prusa is generally like Apple in that regard, in that they wait for the new technology to be tried and true before committing their design(s) to it. CoreXY is the most prominent example.
Prusa was actually the "non-technical" printer company for quite a while though. They would sell to schools and libraries, and still do, and offer(ed) assembled kits.
I don't own a Prusa, I've assembled Vorons and have a highly-modified Ender 3 S1, but if I was in the market to get a user-friendly printer, or recommend one, I'd get a Prusa.
My conspiracy theory is the whole AI datacenter water consumption outrage is a psyop by state actors to worsen public sentiment around AI, so China and others can catch up. Obviously we should lessen the environmental impact of our technology, while considering it's relative impact vs benefit, especially compared to other technology, in this case in particular to other datacenter usage.
But it's comical to see the average person commenting online, outraged at new datacenters and their water usage (separating this from legitimate zoning issues), when all their posts are in fact being transmitted, stored, and served by relatively similar datacenters.
Is the average person allergic to asking follow-up questions?
I'll never understand the people who stand in line for an hour for "Free donut day" or something similar. You really value a $1.50 donut equal to an hour of your time?
Cancelled my Prime subscription last month after the past year of worsening experiences with Amazon:
Received several orders that were returned items, with broken open packaging and sometimes the item was something else entirely, purely put there for weight by whoever returned it.
When I went to return some things at a major Amazon distribution center, the return area was closed for the week for some sort of construction or renovation, with no indication of that anywhere on the site. The only messaging was a piece of paper in the window once you got there.
At another separate major distribution center, the return area was a small room with pieces of paper taped to a door with an arrow pointing to the Amazon lockers where the returns are accepted.
Orders are now often so delayed that it makes the Prime subscription pointless. Have had multiple orders over the past year that didn't ship for 3 or 4 days.
Amazon listings are almost half Sponsored listings now, and there are unrelated ads on the side of listings.
Half of the listings are some random made-up brand name, like XIJGNU, which is just a Chinese seller selling low-quality products, and when the reviews get bad enough, they re-list the product under another made-up brand name.
Fake reviews were already rampant before LLMs, but now reviews are effectively useless because they are so easy to fake.
I choose to use frameworks in the same sense I choose to use crypto libraries. Smarter people have thought long and hard about the problems involved, and came up with the best ways to solve them.
Why have the agents redo all of that if it's not absolutely necessary? Which it probably isn't for ~98% of cases.
Also, the models are trained on code which predominantly uses frameworks, so it'll probably trend toward the average anyway and produce a variant of what already exists in frameworks.
In the cases where it might make sense, maybe the benefit then is the ability to take and use piecemeal parts of a framework or library and tailor it to your specific case, without importing the entire framework/library.
It seems to be an ever-present trait of modern business. There is no rigor, probably partly because most business professionals have never learned how to properly approach and analyze data.
Can't tell you how many times I've seen product managers making decisions based on a few hundred analytics events, trying to glean insight where there is none.