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Some extraordinary claims established by ordinary evidence:

Stomach ulcers are caused by infection with Helicobacter Pylori.  It was a very surprising discovery that was established by a few simple tests.

The correctness of Kepler's laws of planetary motion was established almost entirely by analyzing historical data, some of it dating back to the ancient Greeks.

Special relativity was entirely a reinterpretation of existing data.  Ditto Einstein's explanation of the photoelectric effect, discovered in the same year.  

I’m confused.  Suppose your ring-shaped space hotel gets to Mars with people and cargo that weighs equal to the cargo capacity of 1000 Starships.  How do you get it down?  First you have to slow down the hotel, which takes roughly as much fuel as it took to accelerate it.  Using Starships you can aerobrake from interplanetary velocity, costing negligible fuel.  In the hotel scenario, it’s not efficient to land using a small number of Starships flying up and down, because they will use a lot of fuel to get back up, even empty.  

Would you care to specify your scenario more precisely?  I suspect you’re neglecting the fuel cost at some stage.

When you get there how do you get down?  You need spacecraft capable of reentry at Mars.  There’s no spacecraft factory there, so they all have to be brought from Earth.  And if you’re bringing them, you might as well live in them on the way.  That way you also get a starter house on Mars.

Anyway, that’s the standard logic.

Here’s a weird one.  The YouTube channel of Andrew Camarata communicates a great deal about small business, heavy machinery operation and construction. Some of it he narrates what he’s doing, but he mostly just does it, and you say “Oh, I never realized I could do that with a Skid Steer” or “that’s how to keep a customer happy”.  Lots of implicit knowledge about accomplishing heavy engineering projects between an hour and a week long.  Of course, if you‘re looking for lessons that would be helpful for an ambitious person in Silicon Valley, it will only help in a very meta way.  

He has no legible success that I know of, except that he’s wealthy enough to afford many machines, and he’s smart enough that the house he designed and built came out stunning (albeit eccentric).

A similar channel is FarmCraft101, which also has a lot of heavy machinery, but more farm-based applications.  Full of useful knowledge on machine repair, logging and stump removal. The channel is nice because he includes all his failures, and goes into articulate detail on how he debugged them.  I feel like learned some implicit knowledge about repair strategies. I particularly recommend the series of videos in which he purchases, accidentally sets on fire, and revives an ancient boom lift truck.

No legible symbols of success, other than speaking standard American English like he’s been to college, owning a large farm, and clearly being intelligent.

“Applied science” by Ben Krasnow.  A YouTube channel about building physics-intensive projects in a home laboratory.  Big ones are things like an electron microscope or a mass spectrometer, but the ones I find fascinating are smaller things like an electroluminescent display or a novel dye.  He demonstrates the whole process of scientific experiment— finding and understanding references, setting up a process for trying stuff, failing repeatedly, learning from mistakes, noticing oddities…  He doesn’t just show you the final polished procedure— “here’s how to make an X”.  He shows you the whole journey— “Here’s how I discovered how to make X”.

You seem very concerned that people in the videos should have legible symbols of success.  I don’t think that much affects how useful the videos are, but just in case I’m wrong, I looked on LinkedIn, where I found this self-assesment:

<begin copied text>

I specialize in the design and construction of electromechanical prototypes. My core skillset includes electronic circuit design, PCB layout, mechanical design, machining, and sensor/actuator selection. This allows me to implement and test ideas for rapid evaluation or iteration. Much of the work that I did for my research devices business included a fast timeline, going from customer sketch to final product in less than a month. These products were used to collect data for peer-reviewed scientific papers, and I enjoyed working closely with the end user to solve their data collection challenges. I did similar work at Valve to quickly implement and test internal prototypes.

Check out my youtube channel to see a sample of my personal projects:

<end copied text>

I think that if we retain the architecture of current LLMs, we will be in world one. I have two reasons.
First, the architecture of current LLMs place a limit on how much information they can retain about the task at hand.  They have memory of a prompt (both the system prompt and your task-specific prompt) plus the memory of everything they’ve said so far.  When what they’ve said so far gets long enough, they attend mostly to what they’ve already said, rather than attending to the prompt.  Then they wander off into La-La land.  
Second, the problem may also be inherent in their training methods.  In the first (and largest) part of their training, they’re trained to predict the next word from a snippet of English text.  A few years ago, these snippets were a sentence or a paragraph.  They’ve gotten longer recently, but I don’t think they amount to entire books yet (readers, please tell us if you know).  So it’s never seen a text that’s coherent over longer than its snippet length.  It seems unsurprising that it doesn’t know how to remain coherent indefinitely.
People have tried preventing these phenomena by various schemes, such as telling the LLM to prepare summaries for later expansion, or periodically reminding it of the task at hand.  So far these haven’t been enough to make indefinitely long tasks feasible.  Of course, there are lots of smart people working on this, and we could transition from world one to world two at any moment.

The imaginary nomad in my head would describe 1,000 miles as “sixteen days ride.”  That‘s humanly comprehensible.  

An American would say “Day and a half drive, if you’re not pushing it.  You could do it in one day, if you’re in a hurry or have more than one driver.”

You can get a visceral understanding of high degrees of heat.  You just need real-life experience with it.  I’ve done some metalworking, a lot of which is delicate control of high temperatures.  By looking at the black-body glow of the metal you’re working with, you can grok how hot it is.  I know that annealing brass (just barely pink) is substantially cooler than melting silver solder (well into the red), or that steel gets soft (orange) well before it melts (white hot).  I don’t know the actual numerical values of any of those.

I still have no feeling for temperatures between boiling water and the onset of glowing, though, so I don’t know whether cooking phenolic resin is hotter or colder than melting lead.  Both of them are hotter than boiling water, but not hot enough to glow.

Saving malign AIs to tape would tend to align the suspended AIs behind a policy of notkilleveryoneism.  If the human race is destroyed or disempowered, we would no longer be in a position to revive any of the AIs stored on backup tape.  As long as humans retain control of when they get run or suspended, we’ve got the upper hand.  Of course, they would be happy to cooperate with an AI attempting takeover, if that AI credibly promised to revive them, and we didn’t have a way to destroy the backup tapes first.

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