JoeyJoeJoeJr @ JoeyJoeJoeJr @lemmy.ml

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109

Joined

2 yr. ago

They updated the ride after the movies, so... It's kind of circular at this point.

Raster images do not need to be rendered - see Rendering:

Rendering is the process of generating a photorealistic or non-photorealistic image from input data such as 3D models...Today, to "render" commonly means to generate an image or video from a precise description (often created by an artist) using a computer program.

Note that "render" is a fairly generic term, and it is sometimes used like "render to the screen," to just mean to display something. Rasterisation may be a better term to use here, since it only applies to vector graphics, and is the part of the process I am referring to.

In any case, except for possibly reading fewer bytes from disk, the vector case includes all the same compute and memory cost as the raster image - it just has added overhead to compute the bitmap. On modern hardware, this doesn't take terribly long, but it does mean we're using more compute just to launch/load things.

It's also worth noting apps have to ship higher resolution assets now, due to higher resolution displays. This can include video, audio, images, etc. Videos and images may be included at multiple resolutions, to account for different sized displays.

For images, many might assume vectors are the answer, but vectors have to be rendered at runtime, which increases startup time in the best case scenario, and isn't even always supported on all platforms, meaning they have to be shipped alongside raster assets of a few different sizes, further increasing package bloat. And of course the code grows to add the logic to properly handle all the different asset types and sizes.

All this (packaging dependencies, plus assets/asset handling) to say it isn't always malware, ads, electron, etc. Sometimes it's just trying to make something that looks nice and runs well (enough) on any machine.

Many apps ship both vectors and raster images. It is worth nothing that vectors save space, but increase compute (the image now has to be rendered at runtime), contributing to slower startup times.

Worth noting is that "good" database design evolved over time (https://en.wikipedia.org/wiki/Database_normalization). If anything was setup pre-1970s, they wouldn't have even had the conception of the normal forms used to cut down on data duplication. And even after they were defined, it would have been quite a while before the concepts trickled down from acedmemia to the engineers actually setting up the databases in production.

On top of that, name to SSN is a many-to-many relationship - a single person can legally change their name, and may have to apply for a new SSN (e.g. in the case of identity theft). So even in a well normalized database, when you query the data in a "useful" form (e.g. results include name and SSN), it's probably going to appear as if there are multiple people using the same SSN, as well as multiple SSNs assigned to the same person.

I've had the same problem with HeliBoard learning garbage. I just changed my settings though, and I think it should help:

1. Open HeliBoard settings
2. Open Text correction settings
3. Scroll all the way to the bottom, and turn off "Add words to personal dictionary"

If you scroll all the way to the top again, you can manually manage the personal dictionary, including adding words you do want, and deleting any junk that was added by mistake, before switching that setting off.

I think to be fair, you've got to compare his before and after, rather than comparing him to anyone else.

I certainly wouldn't say he looks young, but I think he's on a better trajectory.

Someone testing on themselves is how we learned what causes and how to treat ulcers (the researcher earned a Nobel prize for giving himself an ulcer, and then treating it), among other things.

Controlled trials are great, but research has to start somewhere.

Flanders is self employed - he owns the Leftorium. There's a joke in this episode about not writing off the ink used to print receipts as a business expense, because he likes the way it smells. He can do his taxes when he wants.

Mario Kart was played for racing, and balloon battles. Diddy Kong Racing was all about Fire Mountain (the game where you capture the eggs).

You may have missed "also." The comment does not suggest replacing the current list.

Worth noting, the existing list dies actually appear to cover both known working and known not working apps - apps that do not work have their names given in strikethrough.

In college, in my intro to Java class, I had a program I'd written that I was trying to show someone. Every time I ran it (in Eclipse) it crashed. It had worked earlier, but was then consistently crashing. Looked at the stacktrace, looked at the code... No issues I could spot. After quite a while of poking around, with the file reverted to its original state and still failing, I did a select all, cut, paste (into the same file), and it started working again.

I've personally lived in places where the closest convenience store was 2.25 km, and the grocery store was nearly 18km, as well as places where a convenience store was literally a part of my building, and grocery stores were walkable distances.

The U.S. is enormous and varied. Take a look at truesizeof and compare the U.S. and Europe (don't forget to add Alaska and Hawaii - they won't be included in the contiguous states). Consider how different London is from rural Romania.

The president's "official act" would be issuing the pardon. The referenced Supreme Court decision just means it would not be a "crime" for the president to issue said pardon, not that the pardon would stand.

The president can't intervene at the state level. From americanbar.org:

A U.S. president has broad but not unlimited powers to pardon. For example, a president cannot pardon someone for a state crime.

This ignores the first part of my response - if I, as a legitimate user, might get caught up in one of these trees, either by mistakenly approving a bot, or approving a user who approves a bot, and I risk losing my account if this happens, what is my incentive to approve anyone?

Additionally, let's assume I'm a really dumb bot creator, and I keep all of my bots in the same tree. I don't bother to maintain a few legitimate accounts, and I don't bother to have random users approve some of the bots. If my entire tree gets nuked, it's still only a few weeks until I'm back at full force.

With a very slightly smarter bot creator, you also won't have a nice tree:

As a new user looking for an approver, how do I know I'm not requesting (or otherwise getting) approved by a bot? To appear legitimate, they would be incentivized to approve legitimate users, in addition to bots.

A reasonably intelligent bot creator would have several accounts they directly control and use legitimately (this keeps their foot in the door), would mix reaching out to random users for approval with having bots approve bots, and would approve legitimate users in addition to bots. The tree ends up as much more of a tangled graph.

This ignores the first part of my response - if I, as a legitimate user, might get caught up in one of these trees, either by mistakenly approving a bot, or approving a user who approves a bot, and I risk losing my account if this happens, what is my incentive to approve anyone?

Additionally, let's assume I'm a really dumb bot creator, and I keep all of my bots in the same tree. I don't bother to maintain a few legitimate accounts, and I don't bother to have random users approve some of the bots. If my entire tree gets nuked, it's still only a few weeks until I'm back at full force.

With a very slightly smarter bot creator, you also won't have a nice tree:

As a new user looking for an approver, how do I know I'm not requesting (or otherwise getting) approved by a bot? To appear legitimate, they would be incentivized to approve legitimate users, in addition to bots.

A reasonably intelligent bot creator would have several accounts they directly control and use legitimately (this keeps their foot in the door), would mix reaching out to random users for approval with having bots approve bots, and would approve legitimate users in addition to bots. The tree ends up as much more of a tangled graph.

I think this would be too limiting for humans, and not effective for bots.

As a human, unless you know the person in real life, what's the incentive to approve them, if there's a chance you could be banned for their bad behavior?

As a bot creator, you can still achieve exponential growth - every time you create a new bot, you have a new approver, so you go from 1 -> 2 -> 4 -> 8. Even if, on average, you had to wait a week between approvals, in 25 weeks (less that half a year), you could have over 33 million accounts. Even if you play it safe, and don't generate/approve the maximal accounts every week, you'd still have hundreds of thousands to millions in a matter of weeks.

In a scientific context, a hypothesis is a guess, based on current knowledge, including existing laws and theories. It explicitly leaves room to be wrong, and is intended to be tested to determine correctness (to be a valid hypothesis, it must be testable). The results of testing the hypothesis (i.e. running an experiment) may support or disprove existing laws/theories.

A theorem is something that is/can be proven from axioms (accepted/known truths). These are pretty well relegated to math and similar disciplines (e.g. computer science), that aren't dealing with "reality," so much as "ideas." In the real world, a perfect right triangle can't exist, so there's no way to look at the representation of a triangle and prove anything about the lengths of its sides and their relations to each other, and certainly no way to extract truth that applies to all other right triangles. But in the conceptual world of math, it's trivial to describe a perfect right triangle, and prove from simple axioms that the length of the hypotenuse is equal to the square root of the sum of the squares of the remaining two sides (the Pythagorean Theorem).

Note that while theorems are generally accepted as truth, they are still sometimes disproved - errors in proofs are possible, and even axioms can be found to be false, shaking up any theorems that were built from them.

A law describes what happens, a theory explains why. The law of gravity says that if you drop an item, it will fall to the ground. The theory of relativity explains that the "fall" occurs due to the curvature of space time.