Glaciers actually do retreat and advance seasonally or on even longer cycles. Some have terminuses that move back and forth literal miles. One of the key indicators of climate change is the fact that globally, glaciers are retreating more than they’re advancing on average.
Flat cables can be conformant and they still have twisted pairs. Cables just have to meet the physical properties set by the standard.
Dogs and wolves are the same species (Canis Lupus), not just members of the same genus. Genus Allium is much bigger than genus Canis (over 800 species) and its members are much less closely related to each other. The common food species are at least evolutionary cousins though, unlike other parts of the category. The onions and chives all share subgenus Cepa, while garlic and leeks are off in subgenus Allium.
You can find plenty of people complaining online about the startup time of the windows and gnome (snap) calculators. The problem in those cases isn’t solved by compiled languages, but it illustrates that it’s important to consider performance even for things like calculator apps.
You can sometimes deal with performance issues by caching, if you want to trade one hard problem for another (cache invalidation). There’s plenty of cases where that’s not a solution though. I recently had a 1ns time budget on a change. That kind of optimization is fun/impossible to do in Python and straightforward to accomplish Rust or C/C++ once you’ve set up your measurements.
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There’s multiple things you’re mixing up here. There’s the “up” in the global coordinate reference frame. This could be based on the local system, though that makes entering and exiting the system a tiny bit more difficult. More likely it’d be based on galactic coordinates.
There’s also the ship reference frame in the comic. This probably won’t be oriented towards the global coordinate system. It’ll be oriented towards whatever the engines, sensors, and gravity need. Because the ships will all be in orbit, their orientations will probably be changing constantly relative to other ships and the global reference frame. There’s no reason to orient in a single direction and lots of reasons not to (it wastes energy, points your sensors away from the things you want to see, etc).
The ecliptic North Pole (Earth’s plane of orbit) is a bit over 27 degrees off the plane of galactic rotation. Which one is “up” and why would a spacecraft that’s done any number of inclination changes to get there care about it?
WSL is just a well integrated VM running Linux. It’s mainly intended for CLI tools, but there’s nothing preventing you from e.g. running an X server and having programs appear in the Windows “window manager”.
The super key is largely inaccessible though. It’s tied very deeply into Windows, which is still the one talking to the keyboard.
It’s a little weird and very European, so OpenSUSE.
I haven’t explained what the differences are because almost everything is different. It’s like comparing a Model T to a Bugatti. They’re simply not built the same way, even if they both use internal combustion engines and gearboxes.
Let me give you an overview of how the research pipeline occurs though. First is the fundamental research, which outside of semiconductors is usually funded by public sources. This encompasses things like methods of crack formation in glasses, better solid state models, improved error correction algorithms and so on. The next layer up is applied research, where the fundamental research is applied to improve or optimize existing solutions / create new partial solutions to unsolved problems. Funding here is a mix of private and public depending on the specific area. Semiconductor companies do lots of their own original research here as well, as you can see from these Micron and TSMC memory research pages. It’s very common for researchers who are publicly funded here to take that research and use it to go start a private company, usually with funding from their institution. This is where many important semiconductor companies have their roots, including TSMC via ITRI. These companies in turn invest in product / highly applied research aimed at productizing the research for the mass market. Sometimes this is easy, sometimes it’s extremely difficult. Most of the challenges of EUV lithography occurred here, because going from low yield academic research to high yield commercial feasibility was extremely difficult. Direct investment here is almost always private, though there can be significant public investments through companies. If this is published (it often isn’t), it’s commonly done as patents. Every company you’ve heard of has thousands of these patents, and some of the larger ones have tens or hundreds of thousands. All of that is the result of internal research. Lastly, they’ll take all of that, build standards (e.g. DDR5, h.265, 5G), and develop commercial implementations that actually do those things. That’s what OEMs buy (or try to develop on their own in the case of Apple modems) to integrate into their products.
You have no idea how modern technology is produced. Any particular product is usually the result of dozens to thousands of iterations, some funded with public money and many not. Let’s take an example from your chart: DRAM. I actually don’t know when DARPA “developed” DRAM (since DARPA usually funds private companies to do development for them), but it must have been before 1970 when Intel designed the 1103 chip that got them started. Do you think that pre-1970s design is remotely similar to the DRAM operating on your device today? I’ll give you a hint: it’s not.
And no, modern device development does not consist of gluing a bunch of APIs together. Apple maintains its own compilers, languages, toolchains, runtimes, hardware, operating systems, debugging tools, and so on. Some of that code had distant origins in open source (e.g. webkit), but that’s vastly different than publicly funded and those components are usually very different today.
They’re failing to produce competitive modems because modern wireless is one of closest things humans have to straight up black magic. It’s extremely difficult to get right, especially as frequencies go up, SNR goes down, and we try to push things ever faster despite having effectively reached the Shannon limit ages ago.
Cost of living isn’t the same everywhere and perspective is relative.
Rent in my area averages around 3k USD/mo for fairly plain arrangements. Between that and “unavoidable” costs like utilities, you’d get 3-4 months max on that amount, even living frugally. It really isn’t that much for a lot of people, even if that amount might be to you.
Larian has an actual QA team. It’s just a big, complicated game.
You can, today, download an app and go ride in a self-driving car around multiple US cities. All of those cars use LIDARs. Sensor disagreement is not a major issue because sensor fusion is a very well-understood topic.
The thing is, steam’s market dominance is one of user choice rather than anticompetitive strategies or lack of alternatives. Steam doesn’t do exclusives, they don’t charge you for external sales, they don’t even prevent you from selling steam keys outside the platform, or users from launching non steam games in the client. The only real restriction is that access to steam services requires a license in the active steam account. Even valve-produced devices like the steam deck can install from other stores.
Sure, dominance is bad in an abstract theoretical way and it’d be nice if Gog, itch.io, etc were more competitive, but Steam is dominant because consumers actively choose it.