The others have made great points about how any amount adds up. Especially with compounding.

But the most important reason me just be making it a habit. If you are saving $50/month you have a place to put your savings and an investment strategy for that money. The next time you get a pay raise or get rid of some recurring spend it will be natural to start saving $60/month, then $100 and more and more. It is much easier to improve an existing habit than starting a new one. So as soon as you have the chance start that got habit.

GMail could actually use more competitors. However I definitely won’t be trusting Musk with my email.

“Residential IPs” are quite valuable for web scraping. Many scraping prevention tools and services use the source IP as the primary metric. If you come from a public cloud provider like AWS, GCP or DigitalOcean you get blocked 99% of the time. If you come from a US residential ISP then you get much more relaxed screening.

As with most of these things it is pricing based on value.

• Contractor is often fixing or building and cares a lot about the price.
• Most other purchases are during renovations so a luxury expense and relatively speaking the faucet will be a small part of that, so it is easy to milk these people for money.

I wouldn’t call a nail hard to use because I don’t have a hammer. Yes, you need the right hardware, but there is no difference in the difficulty. But I understand what you are trying to say, just wanted to clarify that it wasn’t hard, just not widespread yet.

which is hard to decode using hardware acceleration

This is a little misleading. There is nothing fundamental about AV1 that makes it hard to decode, support is just not widespread yet (mostly because it is a relatively new codec).

Just to be clear it is probably a good thing that YouTube re-encodes all videos. Videos are a highly complex format and decoders are prone to security vulnerabilities. By transcoding everything (in a controlled sandbox) YouTube takes most of this risk on and makes it highly unlikely that the resulting video that they serve to the general public is able to exploit any bugs in decoders.

Plus YouTube serves videos in a variety of formats and resolutions (and now different bitrates within a resolution). So even if they did try to preserve the original encoding where possible you wouldn’t get it most of the time because there is a better match for your device.

From my experience it doesn’t matter if there is an “Enhanced Bitrate” option or not. My assumption is that around the time that they added this option they dropped the regular 1080p bitrate for all videos. However they likely didn’t eagerly re-encode old videos. So old videos still look OK for “1080p” but newer videos look trash whether or not the “1080p Enhanced Bitrate” option is available.

It may be worth right-clicking the video and choosing “Stats for Nerds” this will show you the video codec being used. For me 1080p is typically VP9 while 4k is usually AV1. Since AV1 is a newer codec it is quite likely that you don’t have hardware decoding support.

I’m pretty sure that YouTube has been compressing videos harder in general. This loosely correlates with their release of the “1080p Enhanced Bitrate” option. But even 4k videos seem to have gotten worse to my eyes.

Watching a higher resolution is definitely a valid strategy. Optimal video compression is very complicated and while compressing at the native resolution is more efficient you can only go so far with less bits. Since the higher resolution versions have higher bitrates they just fundamentally have more data available and will give an overall better picture. If you are worried about possible fuzziness you can try using 4k rather than 1440p as it is a clean doubling of 1080p so you won’t lose any crisp edges.

The use case will change everything. OP is likely using much more memory than you are (especially disk cache usage) so the kernel decided to swap out some data. Maybe you aren’t using as much so it has no need.

To put it another way you want to be using all of your RAM and swap. It becomes a problem if you are frequently reading from Swap. (Writing isn’t usually as much of an issue as they may be proactive writes in case more memory needs to be filled up).

Basically a perfect OS would use RAM + Swap such that the least disk reads need to be issued. This can mean swapping out some idle anonymous memory so that the space can be used as disk cache for some hotter data.

In this screenshot the OS decided that it was better to swap out 3GiB of something to use that space for the disk cache (“Cached” ). It is likely right about this decision (but is not always).

3 GiB does seem a bit high. But if you have lots of processes running that are using memory but are mostly idle it could definitely happen. For example in my case I often have lots of Language Servers running in my IDE, but many of them are for projects that I am not actively looking at so they are just waiting for something to happen. These often take lots of memory and it may make sense to swap these out until they are used again.

It honestly sounds more like someone convincing you that crypto is great than someone convincing you that Greenpeace is great.

We did it not because it was easy, but because we thought it would be easy.

I switched to Immich recently and am very happy.

1. Immich’s face detection is much better, very rarely fails. Especially for non-white faces. But even for white faces PhotoPrisim regularly needed me reviewing the unmatched faces. I also needed to really turn up the “what is a face” threshold because otherwise it would miss a ton of clear faces. (Then it only missed some, but also has tons of false positives). On the other hand Immich just works.
2. Immich’s UI is much nicer overall. Lots of small affordances. For example the menu item to “view in timeline” is worth switching alone. Also good riddance to PhotoPrism’s persistent and buggy selection. Someone must have worked really hard on implementing this but it was really just a bad idea.
3. Immich has an app with uploading, and it allows you to view local and uploaded photos in one interface which is a huge UX win. I couldn’t find a good Android app for uploading to photoprism. You could set up import delays and stuff but you would still regularly get partially uploaded files imported and have to clean it up manually.
4. Immich’s search by content is much better. For example searching for “cat with red and yellow ball” was useless on PhotoPrism, but I found tons of the results I was looking for on Immich.

The bad:

1. There is currently a terrible jank in the Immich app which makes videos unusable and everything painful. Apparently this is due to some Album sync process running in the main thread. They are working on it. I can’t fathom how a few hundred albums causes this much lag but 🤷 There is also even worse lag on the location view page, but at least that is just one page.
2. The Immich app has a lot less features than the website. But the website works very well on mobile so even just using the website (and the app for uploading) is better than PhotoPrism here. The fundamentals are good but it just needs more work.
3. I liked PhotoPrism’s advanced filters. They were very limited but at least they were there.
4. Not being able to sort search results by date is a huge usability issue. I often know roughly when the photo I want to find was taken and being able to order by date would be hugely helpful.
5. You have to eagerly transcode all videos. There is no way to clean up old transcodes and re-transcode on the fly. To be fair the PhotoPrism story also wasn’t great because you had to wait for the full video to be transcoded before starting, leading to a huge delay for videos more than a few seconds, but at least I could save a few hundred gigs of disk space.

Honestly a lot of stuff in PhotoPrism feels like one developer has a weird workflow and they optimized it for that. Most of them are counter to what I actually want to do (like automatic title and description generation, or the review stuff, or auto quality rating). Immich is very clearly inspired by Google Photos and takes a lot of things directly from it, but that matches my use case way better. (I was pretty happy with Google Photos until they started refusing to give access to the originals.)

Most Intel GPUs are great at transcoding. Reliable, widely supported and quite a bit of transcoding power for very little electrical power.

I think the main thing I would check is what formats are supported. If the other GPU can support newer formats like AV1 it may be worth it (if you want to store your videos in these more efficient formats or you have clients who can consume these formats and will appreciate the reduced bandwidth).

But overall I would say if you aren’t having any problems no need to bother. The onboard graphics are simple and efficient.

I don’t want the end executable to have to bundle these files and re-parse them each time it gets run.

No matter how you persist data you will need to re-parse it. The question is really just if the new format is more efficient to read than the old format. Some formats such as FlatBuffers and Cap'n Proto are designed to have very efficient loading processes.

(Well technically you could persist the process image to disk, but this tends to be much larger than serialized data would be and has issues such as defeating ASLR. This is very rarely done.)

Lots of people are talking about Pickle. But it isn’t particularly fast. That being side with Python you can’t expect much to start with.

Must be because Factorio released 2.0 and the Space Age DLC recently.

I paid for GPM for quite a while. I then started working at Google and beta tested YouTube Music from very early on and gave lots of feedback about how it sucked. When they shut down GPM I cancelled my YouTube Premium membership and installed an ad blocker. Not just YTM but so many things about YouTube were getting worse and worse and I couldn’t find it in myself to keep paying for a service that kept removing features.

Yes, but in my experience it is pretty trash. Unlike Google Play Music which matched the music to known tracks and shuffled it in with recommended playlists and other features on YouTube Music the uploaded songs are basically completely isolated. At that point why use a streaming service?