I guess it’s about entropy. Some items have more entropy than others. They have more parts and more possible states, and most of those states are misconfigured.
A table or a chair has most of its parts glued together in a fixed, low-entropy position, and has few parts to begin with.
A printer has many parts, both at the hardware and software level, and they can be in many states. It has paper, which can be in a state of having run out or not, and if it has run out, the supply can be almost literally anywhere. It has many intricate mechanical parts which can wear out at different rates, it has an ink cartridge that can dry out even when unused, and many intricate little parts that I don’t even know about.
On top of that, the software also has high complexity. Lots of software components, including the low level stuff that manages the actual printing, whatever needs to connect to the wifi, whatever is needed in case it can print from email, etc. all of these processes can run concurrently, which may introduce race conditions, any of these components may have a bug.
And then there’s the drivers installed on your laptop, which may be out of date, or your laptop’s drivers may be fully up to date but the printer software is out of date and your driver is no longer compatible with it.
Many components, many possible states, high entropy.
EDIT: also, I think a big part of it is that printers aren’t really tested for reliability. I used to work at a car manufacturer. Cars are hybrid software-hardware systems, and both sides of that equation are highly complex. Car engineering is a huge discipline that focuses aggressively on reliability. Even though car makers appear to come out with a new model every year, in reality they only change the cosmetics. The underlying platform usually only changes once every six years, and every version of the platform is aggressively stress tested in every possible way. The company I worked for had a test track in the coldest possible part of Canada, as well as in Death Valley, because reliability testing has to be aggressive and thorough.
Also the software side used special, hardened compilers that only supported a subset of the programming language, and were rarely changed. Getting a contract to supply a car company with a critical tool like a compiler is a hugely profitable multi-year deal, because they are happy to pay for reliability and reluctant to change something that is working well.
I bet nobody really cares about the reliability of printers to the same extent, and they have huh entropy, so they generally suck.
Where can one buy ostrich eggs?
This comic by Tim Urban is interesting, but I remember when I first read it, it seemed wrong.
In his framework, I think ASI can only be quantitatively more powerful than human intelligence, not qualitatively.
The reason is simple: humans are already Turing complete. Anything a machine can do, it can only be faster execution of something a human could already do.
I don’t think it has much bearing on the wider discussion of AI/AI-risk, I haven’t heard anybody else think that the distinction of quantitative/qualitative superiority had any bearing on AI risk.
I have similar problems, and I was hoping you had found a solution. One question I have: on a typical night, do you have good sleep quality, for example as measured by a fitness tracker?
Closest thing I have found to a solution of daily energy is creatine, 5g daily, and 10g if I did hard exercise that day. I cycle on it for about two weeks, until it starts to feel like too much of a good thing, then cycle off for a week, repeat.
Super interesting! I have some follow-up thoughts to this.
A classical example of the latter point is when novices learn to play chess. In a typical training session, they will be presented with a position, and be asked to propose a move. They will take a moment, then propose a move that loses a queen in a totally obvious way, and when challenged, they will take a moment and confirm that "oh, yeah, that loses a queen". Typically a novice is overwhelmed by the details of the position, perhaps still remembering how the pieces move, and have no sense of which moves are important and which moves should be ignored. As a result, they can't do "basic" one-step lookahead to see what countermoves the opponent has. Their working memory is too overloaded with all of the possibilities on the board.
This gets resolved with practice, drills, and experience. Eventually the hind-brain simply "surfaces" the information "that square is controlled by an enemy bishop", and in many cases will not even suggest the move that would hazard the queen, it won't even get loaded into conscious attention.
EDIT: Building on this, it's super interesting to watch Grandmasters like Hikaru Nakamura play games live on stream, and comment on their thought process. Yes, they calculate long lines, sometimes branching, but as they talk, partially distracted, they never consider bad moves, they're always analyzing the top moves recommended by the computer.
I love this post, and I have been thinking a lot about it since it came out.
One counter argument I can think of is the following.
So one may argue that it’s rational to seek king-power on this basis
Despite this, I personally resonate very strongly with the image of the wizard, and I think the world would be a better place if we all sought to strengthen our wizarding powers.
Can you say more about what kind of changes you implemented?
A perhaps more interesting interaction is with wills that are managed by trusts. My understanding is that you can put conditions on how the money in a trust will be disbursed to your heirs, for example "as long as they maintain a minimum GPA in college". I have heard lawyers make outrageous jokes like adding a clause that says "as long as they don't marry that person".
It's quite reasonable to expect that some will add a clause to their trust that says "this only pays out if they have placed themselves on the lifetime no-gambling list".
a google search suggests desoxyn might be just be a brand of pharmaceutical-grade meth
Actually I wonder if we could do an experiment in the following way:
It's true that there will be some amount of overlap, but this should put a ceiling on how well this approach could work.