Yes, that’s a more correct use of “prisoners dilemma:” a choice to either cooperate or defect. Origin below, for the curious.

The dilemma

Two prisoners are interrogated in separate rooms. Each is asked to snitch in exchange for a reduced sentence.

Because they’re separated, the prisoners can’t coordinate, but each knows the other is offered the same deal and the interrogator will only offer bargains that increase their combined years of imprisonment.

For example, “house wins” if snitch gets -2 years and snitchee gets +3 years, since interrogator would net +1 year from the deal.

So what will each prisoner do?

The result

Of course, the best outcome overall is for neither to snitch, and the worst is for both to snitch.

The Nobel-Prize-winning observation was that any prisoner faced with this dilemma (once) will always net a lesser sentence if they snitch than if they don’t, no matter what the other decides.

In other words, two perfect players of this game will always arrive at the worst result (assuming they only expect to play once). This principle came to be known as the Nash equilibrium.

Applications

The result above sounds bleak because it is, but real-world analogs of this game are rarely one-offs and thus entail trust, mutuality, etc.

For example, if the prisoners expect to play this game an indeterminate number of times, the strategy above nearly always loses (the optimal strategy, in case you’re wondering, is called “tit-for-tat” and entails simply doing whatever your opponent did last round).

The study of such logic problems and the strategies to solve them is called game theory.

Edit: fixed typo, added headings and links

Shall I compare thee to a Summer’s day?

Now look here! I was invited to speak with the very real, very human patrons of this fine establishment, and I’ll not have you undermining my efforts to fulfill that obligation!

Hello, this is John Cleese. If you doubt that this is the real John Cleese, here is my mother to confirm that I am, in fact, me. Mother! Am I me?

Oh yes!

There you have it. I am me.

Lol I noticed the same. They evidently have some ongoing internal disagreement as to their target audience. Docs and functionality says “our audience is enterprise developers” but their marketing definitely says “our audience is end users.”

It may be explained by recent partnerships with former custom ISO devs (seeking legitimacy and offering a sizable user base in turn). I expect the plan is eventually to sell premium support for an enterprise toolset, but for now their target audience is the non-dev-but-tech-savvy end user. And those happen to be surprisingly opinionated re: java and electron.

Forgive me for not explaining better. Here are the terms potentially needing explanation.

• Provisioning in this case is initial system setup, the kind of stuff you would do manually after a fresh install, but usually implies a regimented and repeatable process.
• Virtual Machine (VM) snapshots are like a save state in a game, and are often used to reset a virtual machine to a particular known-working condition.
• Preboot Execution Environment (PXE, aka ‘network boot’) is a network adapter feature that lets you boot a physical machine from a hosted network image rather than the usual installation on locally attached storage. It’s probably tucked away in your BIOS settings, but many computers have the feature since it’s a common requirement in commercial deployments. As with the VM snapshot described above, a PXE image is typically a known-working state that resets on each boot.
• Non-virtualized means not using hardware virtualization, and I meant specifically not running inside a virtual machine.
• Local-only means without a network or just not booting from a network-hosted image.
• Telemetry refers to data collecting functionality. Most software has it. Windows has a lot. Telemetry isn’t necessarily bad since it can, for example, help reveal and resolve bugs and usability problems, but it is easily (and has often been) abused by data-hungry corporations like MS, so disabling it is an advisable precaution.
• MS = Microsoft
• OSS = Open Source Software
• Group policies are administrative settings in Windows that control standards (for stuff like security, power management, licensing, file system and settings access, etc.) for user groups on a machine or network. Most users stick with the defaults but you can edit these yourself for a greater degree of control.
• Docker lets you run software inside “containers” to isolate them from the rest of the environment, exposing and/or virtualizing just the resources they need to run, and Compose is a related tool for defining one or more of these containers, how they interact, etc. To my knowledge there is no one-to-one equivalent for Windows.

Obviously, many of these concepts relate to IT work, as are the use-cases I had in mind, but the software is simple enough for the average user if you just pick one of the premade playbooks. (The Atlas playbook is popular among gamers, for example.)

Edit: added explanations for docker and telemetry

Just a tip: if you must use consumer editions of Windows regularly, consider adding an automatic provisioning tool like AME to your workflow.

The example above uses customizable “playbooks” to provision a system the way docker compose would a container image, so it can fill the role of a VM snapshot or PXE in non-virtualized local-only scenarios.

The most popular playbooks strip out AI components and services (there are many more than just Recall) but also disable all telemetry and cloud-based features, replace MS bloatware with preferred OSS, curtail a truckload of annoying Windows behaviors, setup more sensible group policies than the defaults, and so forth.

I have a few custom playbooks for recurring use cases so that, when one presents, I can spin up an instance quickly without the usual hassle and risk.

deleted by creator

even old data retroactively

My impression is that retroactive opt-out data grifting represents the lion’s share of user data sales today, and that it’s a popular strategy because it works.

The formula: appraise the data and find your buyers in advance. THEN update the privacy policies to include the data you want to sell. That way, the moment new policies go into effect, all you have to do is hit the transfer button.

After that, it’s done. Users that find and flick your new opt-out toggle only stop you from selling their data to additional buyers, and that’s nbd since data brokers only pay top-dollar for exclusive access to stuff that’s not already on the market.

It’s why I consider the introduction of any opt-out privacy policy an explicit admission of data theft.

Ah! Yeah it’s been a while but I seem to recall seeing alkaline batteries in a some freezers or refrigerators sometimes when I was a kid, along with other curiosities like rolls of film. No one ever explained why.

IIRC freezing accelerates the chemical degradation of lithium ion (especially if you attempt to charge the battery at the same time) and tends to lower both the voltage and amperage of most battery chemistries, but it seems plausible that this might

1. temporarily defeat a cell protection circuit, allowing a charging procedure to initialize, or
2. delay a thermal failsafe cut-off of a damaged cell long enough to boot or charge a device

Regardless, for those tuning in at home, best to keep your batteries out of the freezer, especially lithium types, unless spicy pillows are what you’re after.

Hmm, you’re right. At a guess, this field might represent the maximal combined interest of both scientific and pedestrian readership within technology research, since on the one hand energy density and storage logistics is the key limitation for a ton of desirable applications, and on the other most consumers’ experience with batteries establish them as a major convenience factor in their day-to-day.

Edit: you’re*

How are energy and power “loose terms”? Energy might be difficult to fully explain rigorously, but it’s one of the fundamental elements of our universe. And power is just energy over time

Well, you yourself just provided the example, since your definition of energy and power are the inverse of the definitions used in the video.

It’s the fact that people use them differently or interchangeably that makes them “loose” IMHO.

He’s making a point about instantaneous versus overall energy use, which it sounds like you already understand. “Power” and “energy” are kind of loose terms IMO, which could confuse that conversation a bit.

But for anyone still scratching their head:

The typical energy consumer need only consider watts (w, kw) when accounting for circuit capacity. For example, if your hair dryer pulls 1600 watts, don’t use it on a 1500 watt outlet, or you will likely trip the circuit breaker.

Otherwise “watt-hours” (wh, kwh) is likely the metric you’re looking for when considering energy use. This is a certain amount of power drawn over a period of time, where 1 watt over 1000 hours and 1000 watts over 1 hour are both equal to 1 kilowatt-hour (kwh), which is the standard unit you likely see in your electric bill.

It’s why low but constant power draw can significantly impact energy use. For example, a typical laptop pulls fewer than 100 watts, lower than many appliances in your house, but if it draws that much power all the time, it might significantly impact your electric bill. Conversely, an electric kettle / coffee maker might pull as much as 1300 watts while in use, more than most appliances in your house, yet it probably represents a minuscule portion of your electric bill, since it only runs long enough to boil a small amount of water with each use.

Edit: include tea drinkers, add more concrete examples

you could at least

Note: here “it would be nice if” is more polite, since the least one could have done is always