I've been thinking about this in the back of my mind for a while now. I think it lines up with points Cory Doctorow has made in talks about enshittification. 

I'd like to see recommendation algorithms which are user-editable and preferably platform-agnostic, to allow low switching costs. A situation where people can build their own social media platform and install a recommendation algorithm which works for them, pulling in posts from other users across platforms who they follow. I've heard that the fediverse is trying to do something like this, but I've not been able to get engaged with it yet. 

It's cool to see efforts like Tournesol, though it's a shame they don't have a mobile extension yet.

This is fascinating, and is further evidence to me that LLMs contain models of reality.
I get frustrated with people who say LLMs "just" predict the next token, or they are simply copying and pasting bits of text from their training data. This argument skips over the fact that in order to accurately predict the next token, it's necessary to compress the data in the training set down to something which looks a lot like a mostly accurate model of the world. In other words, if you have a large set of data entangled with reality, then the simplest model which predicts that data looks like reality.

This model of reality can be used to infer things which aren't explicitly in the training data - like distances between places which aren't mentioned together in the training data.

I'm not sure if this is the right place to post, but where can I find details on the Petrov day event/website feature?

I don't want to sign up to participate if (for example) I am not going to be available during the time of the event, but I get selected to play a role.

Maybe the lack of information is intentional?

(apologies in advance for the wall of text, don't feel you need to respond, I wrote it out and then almost didn't post).

To clarify, I wouldn't expect stagnant or decreasing salaries to be the norm. I just wanted to say that there are circumstances where I expect this to be the case. Specifically, if I am an employee who is living paycheck to paycheck (which many do), then I can't afford any time unemployed.

As a result, if my employer is able to squeeze me in this situation, I might agree to a lower wage out of necessity.

The problem with your proposed system is that it essentially encourages employees to selectively squeeze themselves- if they're in a situation where they can't afford to lose their job, then this will lower what they ask at a negotiation, and what they receive, even if the employer is offering the same rmax to all employees. This has little to do with their relative skills as an employee and everything to do with their financial situation and responsibilities outside work.

Here's an example. I'm not sure why I wrote it, but here it is:

Brenda and Karl work at a gas station supermarket. They both work the same job, on the checkout area, with some shelf stocking as needed.

Brenda is a single mom with a 2 year old child who she is paying for childcare, and the rest of her earnings go on rent, food and fuel for her beat up car (it's a miracle it's still running). She works at the gas station 4 days a week, 9-7.

Karl takes on shifts 2 nights a week, it helps pay him through college and he enjoys the extra money. His parents give him enough that he could probably survive without the job entirely, and certainly a period of unemployment would not be a big problem for him.

Brenda and Karl both get paid $15/hr for their work, but they know that the new "payPlav system (TM)" is being introduced by management, and they have a pay negotiation coming up.

Management asks them to read the rules of the new system carefully submit their r-min. They say that if rmax < rmin, then the employee will stay on their existing salary.

Brenda sets her rmin at $15.50. She could do with a significant pay bump, but she doesn't want to lose out on the pay increase entirely, since she's only holding it together at $15.

Karl sets a bolder rmin of $16.50. He works hard at the job and thinks he deserves more, but it's not a big deal if he misses out and stays at $15

Management sets rmax at $17

Brenda gets $16.25

Karl gets $16.75

I don't think this is fair. It's a clear case where the system creates a situation where employees who care less and need the money less will be rewarded more.

Here's another scenario - same as the above, but management says that rmax<rmin will mean termination of the contract.

Brenda sets rmin at $13.50. She simply can't lose this job, it would ruin her.

Karl sets his rmin to $16

Management sets rmax at $15.50

It's more extreme, to be sure, and maybe a little unrealistic.

Many workers employed on zero-hours contracts end up in this situation - since the employer is able to lower wages with impunity and they don't have many other options, they get squeezed for profit. Sometimes unscrupulous employers do this selectively, based on which employees can least afford to stop working. This results in the most impoverished employees losing out.

I feel that human intelligence is not the gold standard of general intelligence; rather, I've begun thinking of it as the *minimum viable general intelligence*.
In evolutionary timescales, virtually no time has elapsed since hominids began trading, utilizing complex symbolic thinking, making art, hunting large animals etc, and here we are, a blip later in high technology. The moment we reached minimum viable general intelligence, we started accelerating to dominate our environment on a global scale, despite increases in intelligence that are actually relatively megre within that time: evolution acts over much longer timescales and can't keep pace with our environment, which we're modifying at an ever-increasing rate.
Moravec's paradox suggests we are in fact highly adapted to the task of interacting with the physical world-as basically all animals are-and we have some half-baked logical thinking systems tacked on to this base.

The employee is incentivised to put the r-min rate as close as they can to their prediction of the employer's r-max, and how far they creep into the margin for error on that prediction is going to be dependent on how much they want/need the job. I don't think the r-min rate for new hires will change in a predictable way over time, since it's going to be dependent on both the employee's prediction of their worth to the employer, and how much they need the job. 

For salary negotiation where the employee already has a contract, I would expect employees to set r-min at their current salary or a little above. 
This prediction is fully dependent on the consequences of r-max< r-min though. If  r-max< r-min results in immediate termination of the contract, then you might see wages stagnate or even decrease, depending on employer's understanding of the employee's situation. In general, I dislike this situation, since it incentivises employers to exploit workers who can't afford a break in employment, squeezing them onto worse pay when they think they can get away with it. It encourages mind games as well - if the employer says "I'm thinking about setting r-max a little below your current salary" then they may convince the employee to lower r-min, and then even if the employer sets a reasonable r-max a little above the employee's salary, the employee may lose out.

Rolled pants leg up to the ankle on the right hand side, but not the left - this is a fairly clear sign that someone is a cyclist, and has probably recently arrived.

They do it to avoid getting bike oil from the chain on the cuff of the pants, and to avoid the pants getting caught in the gear. Bicycles pretty much always have the crank gear on the right hand side.

It doesn't seem particularly likely to me: I don't notice a strong correlation between intelligence and empathy in my daily life, perhaps there are a few more intelligent people who are unusually kind, but that may just be the people I like to hang out with, or a result of more privilege/less abuse growing up leading to better education and also higher levels of empathy. Certainly less smart people may be kind or cruel and I don't see a pattern in it. 

Regardless, I would expect genetically engineered humans to still have the same circuits which handle empathy and caring, and I'd expect them to be a lot safer than an AGI, perhaps even a bit safer than a regular human, since they're less likely to cause damage due to misconceptions or human error since they're able to make more accurate models of the world.

If you're worried about more intelligent people considering themselves a new species, and then not caring about humans, there's some evidence against this in that more intelligent people are more likely to choose vegetarianism, which would indicate that they're more empathetic toward other species.

If I did not see a section in your bio about being an engineer who has worked in multiple relevant areas, I would dismiss this post as a fantasy from someone who does not appreciate how hard building stuff is; a "big picture guy" who does not realise that imagining the robot is dramatically easier than designing and building one which works. 

Given that you know you are not the first person to imagine this kind of machine, or even the first with a rough plan to build one, why do you think that your plan has a greater chance of success than other individuals or groups which have tried before you? Is there something specific that you bring to the table that means you will avoid the challenges or be more suited to tackle them?

I think you might do better starting out with creating a machine which can assemble a copy of itself, from pre-built off-the-shelf parts. A robot arm and camera attachment, which is capable of recognising the pre-made parts of itself and fitting them together autonomously would be very challenging to make and would be a good proof of concept for the larger project. 

If you have this system working, then your next step would be creating the same machine but including a 3d print bed (which it is also capable of assembling) or small scale milling machine to build a few of the parts, and continue by adding more and more manufacturing capabilities, so you have to supply fewer parts with each iteration of the design. I remember assembling my 3d printer a few years ago, and there were quite a lot of steps which would be major practical challenges to a robot a similar size to the printer, even in just assembling the pre-made parts.