Thank you for the suggestions.

Regarding NextDNS, can it be setup in a way that is difficult to disable? Or could I just disable the user application on my phone and use my unfiltered mobile internet? Same for accountability softwares, are there any that go below the user application level to stop me from simply disabling them?

Google parental controls seem cumbersome, as apparently I can only block domains in Chrome and will thus also need to block other browsers. But I will play around with it and see if I can make it work for me.

Could you give a description of how you block social media? All methods I found so far can be undone within seconds.

Remove app, block website like it's an ad, parental controls, unfollow everything, log out, forget credentials, delete account.

You don't need to make the website unreachable, only to delay the impulse for long enough.

For me apps like Opal work really well.

For mathematics, there are the Princeton Companion to Mathematics and the Princeton Companion to Applied Mathematics.

Yes, they were wrong. Many young kids who are bad at mental calculations are later competent at higher mathematics and able to use it. I don't understand what patterns and tricks you're referring to, but if they are important for problems outside of mental calculations, then you can also learn about them by solving these problems directly.

Home gyms are great. I also recommend adjustable dumbbells, they are very versatile.

Interesting, this sounds like my normal state. I cope by only eating tasty calorie-dense meals and snacks, never skipping meals or snacks, and weight lifting to increase my appetite. Otherwise I become significantly underweight.

Seeing this type of argument always bothers me. It's basically saying that, because people in the past were often overly critical of new technologies or trends, we can dismiss criticisms of new technologies or trends in general. Makes no sense.

I think it's less dismissing criticisms and more "just because it's new doesn't mean it's bad."

Other examples: cars vs horses, household appliances will make people lazy vs household robots will make peopl lazy, or SNL has really gone downhill (people have been saying that for decades, and it is indeed subjective but the generation who says it now thought it was peak in their youth, when the old people of their time were saying it sucked).

There may be some merit of truth and some valid criticisms in all of it. As other commenters have pointed out, books were a one-sided conversation, so Socrates was right in that sense, but sometimes it's necessary to have this one-sided conversation in order to have a fruitful multi-party conversation. And I think it's important for that to be understood -- some things are good for some things in some roles.

It's becoming very difficult to function in modern society without a smartphone. Smartphones have given us luxuries we couldn't even fathom in the 90s. Today I sent a spontaneous birthday gift to a friend in another state using Doordash. Twenty years ago that may not have even been possible.

I think it's important to understand the role of smartphones in our society and lives. It shouldn't replace real-life social interaction. It shouldn't be where we spend half our days looking at. We shouldn't believe the news that comes from our social feeds at face value (that transcends smartphones but you get my drift). But using it as a tool to get stuff done, that's invaluable.

The distribution of the data is also the main problem with MBTI, AFAIK. Intra-/extraversion for example have a unimodal distribution with most people being somewhere in the middle. And exactly that middle is where MBTI makes the cut on their classification.

This is a great point. We have a generally tendency to typify in binary[black and white] terms. It overrides our ability to express nuance and un this case pushed out a larger category (if we even wanted to still categorize) of ambiverts.

MBTI speaks more on our drive for categorization than it does on the people being categorized.

It may seem this way from an outsiders perspective, but I think the intersection between people who work on the development of state-of-the-art LLMs and people who get replaced is practically zero. Nobody is making themselves redundant, just some people make others redundant (assuming LLMs are even good enough for that, not that I know if they are) for their own gain.

Somewhat true, but again from an outsiders perspective that just shows your industry is divided and therefore will be conquered. I.e. if AI gets good enough to do software and math I don't even see AI engineers for example as anything special.

many tech people are making themselves redundant, so far mostly not because LLMs are putting them out of jobs, but because everyone decided to jump on the same bandwagon. When yet another AI YC startup surveys their peers about the most pressing AI-related problem to solve, it screams "we have no idea what to do, just want to ride this hype wave somehow"

I don't understand why you would draw this conclusion. The deep search you describe is an algorithm that humans can understand perfectly fine. Humans just can't solve it in their heads and need to let a computer handle the number crunching. Just like a scientist may understand the differential equations to describe a system perfectly fine, but require a computer to approximate the solution for an initial value problem.

“Knowing” that some line works to some ridiculous depth is different than understanding how and why.

And at some level the answer is simply “because every possible refutation fails” and there is no simpler pattern to match against nor intuition to be had. That is the how and why of it.

The scientist can understand “how” the model works, how many layers there are, that each neuron has a weight, that some are connected… Parent comment and yours show that “understanding” is a fuzzy concept.