The amount of money you save (and invest) isn’t accurately depicted with this though. Living expenses don’t necessarily grow with take home, if you keep lifestyle creep to a minimum.

So what this means is that if you make $100k and save $10k/year, if you start making $200k you can save the same $10k/year, plus the entire additional $100k after taxes (let’s just say that’s $50k+). So you doubled your salary but your savings went up 6x+.

Not sure why you’re saying Python forces everything to be object oriented…?

Wouldn’t 25 year olds still be in school for their doctorates though?

Yes, I think that’s the point — they skew the numbers upwards.

“Chain migration” is how many people — myself included — get jobs.

I went to a very good school, and while I like to think the quality of education is what makes a school “good,” let’s be honest — the value is largely in your connections. Friend lands a good job, recommends you when there’s an opening, and bam, you’re already at the top of the pile of the CVs (better yet, they’re the hiring manager).

Friends from school — peers and mentors alike — are a great place to start, if you can. Ask to grab a coffee and chat about their career, and be clear that you’re in the market. Most people are happy to chat (at the very least, it’s flattering).

It’s the way the world works…

My hunch is that this is not restricted to TikTok…

I particularly like the truck/engine correction.

play(1)? I’m getting cat $FILE > /dev/snd vibes…

awk(1)ward

FTFY

One thing to keep in mind — the US is huge, both geographically and culturally. Flying from Los Angeles to Boston is further than London to Baghdad.

And likewise, the cultural “distance” between, say, New England or the Pacific Northwest and the deep south is extreme.

Of course there are things that affect (nearly) all Americans, but some context is important.

But this applies to the UK, Ireland, France, Belgium, Italy, Spain, Portugal, and…well…much of the world, if these data are to be trusted.

But “included” doesn’t mean free. You still paid for it.

Baking is chemistry, cooking is jazz.

I’m curious how the battery percentage went up

Physicists hate this one weird trick…

Exactly. And it includeded a 500GB m2 (SATA, not NVME, but still), with a spare m2 slot available. As opposed to an SD slot + USB port…

Dual gigabit NICs and importantly can be configured to boot after power loss (which the pi of course also does).

And Intel QuickSync may not be perfect but it is well supported with mainline kernels.

Only drawback is that it draws a few extra watts compared to the Pi.

Is that true though? As in, is it really that dangerous? It seems that you’ll dissipate power equal to the inefficiency times the nominal charging power, so something like 5V x 2A x inefficiency (inefficiency being 1-efficiency), which will probably be of order a watt.

I can use my car battery to charge itself without any issues — I just plug the red terminal to itself, and same with the black, which is to say, a battery is always connected in a way that “charges itself.”

I think the key is that the battery probably isn’t really playing a big role in OOP’s setup — electricity doesn’t “go through the battery,” it just goes from the charging input to the power output circuits, with the additional power (due to inefficiency) being provided by the battery.

I’m not sure though — the power output and the charging input are both regulated and (almost certainly) current limited. So I think (not positive…) that you’re basically dissipating your power in the inefficiency the charging and output circuits, with this power coming from the battery.

The inefficiency should (I think…) just be the round-trip inefficiency of the charging/discharging of your power bank — this should be way, way less than the short-circuit power dissipation.

The simplest toy model is to take a battery and try to charge itself. So you put jumpers on the + terminal and you connect those to the + terminal, and same for - (charging is + to +, NOT + to -). But this is silly because you’ve just attached a loop of wire to your terminals, which is equivalent to doing nothing. With charging circuits in between things get much more complicated, but I’m not sure if it goes full catastrophic short…

I switched my home server from ARM SBCs to a $140 N100 (16GB) and honestly it’s a real improvement.

I love the original concept of the SBCs — affordable and efficient, with hardware acceleration for compute-heavy tasks. But the reality for me lately has just been more trouble than it’s worth, and running a mainline kernel on x64 is such a better experience. (I’m mostly griping at the Orange Pi I had — RPi tend to have better SW support.)

For those wondering about the energy, not just the power:

When fully charged, the upper reservoir can store enough energy to power the plant at full capacity for 10.8 hours, equivalent to nearly 40 GWh.

For 75kg (roughly average South Korean male weight) and 7" step height (standard in the US I think, not sure about Korea), this is about 0.13kJ/step.

By coincidence, the human metabolic efficiency is (roughly) the same as the conversion between kJ and food (kilo)calories, meaning this would be (very roughly) 0.1 calories/step.

Not much, given a single French fry is maybe 5-10 calories. But it’s better than nothing!

good enough simulations that you can’t tell the difference.

This requires us having actual conversations with those dead people to compare against, which we obviously can’t do.

There is simply not enough information to train a model on of a dead person to create a comprehensive model of how they would respond in arbitrary conversations. You may be able to train with some depth in their field of expertise, but the whole point is to talk about things which they have no experience with, or at least, things which weren’t known then.

So sure, maybe we get a model that makes you think you’re talking to them, but that’s no different than just having a dream or an acid trip where you’re chatting with Einstein.