There are electron apps for demo.
But basically, using the right compression, you can reduce disk requirements. Mine is like 4TB, so it is useful. Oh, it is lossless, so you can get back your ARW back. It also treated like a regular JPEG image, because compressed matrix data is in the tail of the file, and builtin JPEG is shown first.
By the way (hello, adobe).
DNG compression compresses worse than 7zip, haha.
Too much for an open standard, too hard to add LZ4 as an option in the times of having 24 core setups :D
"Sony’s software for processing ARW RAW files is called Imaging Edge. Like most first-party software from camera manufacturers, it’s terrible and unintuitive to use — and should be saved for situations like a high-resolution multishot mode where it’s the only method to use a camera’s proprietary feature."
I think the primarily reason is that they have great hardware developers and terrible software developers. So, having ARWs it is maximum they could provide to photographer, so they could take the files and run away from sony as soon as possible (i.e. do the rest in the better software).
Pentax could save DNGs, there are zero reasons for other companies not to do the same.
It is always written into a memory buffer first, which could be like 256 megabytes... it tooks time to fill it up, once it is filled, memory card speed becomes a bottleneck. So, actually, writing only jpegs would trigger the slowdown later, so you could take more frames before the buffer fills up
They do way less then that. They just form a final list of locks and download that at the build time. Of course you have to also "recursively" go though all your dep tree and add submodules for each of subdependencies (recommend to add them in the main repo). Then you will have do waste infinite amount of time setting include dirs or something. If you have two libs that require a specific version of a shared lib, no dep manager would help you. Using submodules is questionable practice though. Useful for simple stuff, like 10 deps in total in the final project.
Most popular dependency management systems literally linking to a git sha commit (tag), see locks file that npm/rebar/other tool gives you. Just in a recursive way.
Natural language is pretty good for describing the technical requirements for the complex system, though. I.e. not the current code implementation, but why the current code implementation is selected vs other possible implementations. Not what code do, but what it is expected to do. Basically, most of the missing parts, that live in Jira-s, instead of your repo. It is also good, at allowing better refactoring capabilities, when all your system is described by outside rules, which could be enforced on the whole codebase. We just use programming languages, because it is easier to use in automated/computer context (and was the only way to use, to be honest, before all the LLM stuff). Though, while it gives us non-ambiguity on the local scale, it stops working on the global scale, the first moment person went and copy-pasted part of the code. Are you sure that part follows all the high-level restrictions we should to follow and is correct program? It is program that would run, when compile, but definition of run is pretty loose. In C++ program that corrupts all the memory is also runnable.
Apple has its own trackers and ad services. But it treats itself specially. While other apps need to ask. Maybe I don't want some apps from apple to have the same permissions, as other apps from apple. It is basically bundling. I agreed for one app from apple to share data, not for all apps from apple. Oh, and don't let me start about wording they use on these pop-ups... Like when I download some app from the internet, which is signed, notarized and so on, it still asks: oh, you downloaded this app from the internet (surprise!)... Instead of: "ok, you downloaded from internet, it has sign, notarification, developer is already delivering software for 10 years and have 20 million users, so looks safe to run...". Basically, fear inducing messages instead of actually useful from security sense.
Would not fly.
Developers would not go into the store. Because everyone knows, that 30% tax would be next (basically it is the current situation on the Mac, apple could pull the switch on gatekeeper any time). And, because a lot of modern apps are just electron wrappers, people would just move to the web versions for everything. Which means killing their own platform.
Similar why gatekeeper exists on Mac.
This would mean that old software would stop to work, though. Which is a bit anti-microsoft politics. Without running all the old unsigned software Win is not Win anymore.
By hand or regl library (almost by hand). I tried THREE, but it feels it gives me more pain than benefits (and you still end up tweaking their shaders sometimes). AI is pretty good at small tasks like tweaking shaders. I needed to draw a spectroscope, like a line connecting all pixels on the image one by one on the colorspace projection. Ended up 100 times more efficient in webgl comparing to browser API. But it is pretty low level. On another hand once you dig deeper into shaders, they are actually more powerful. Let's just say, API is just painful too :). Also, there is some fun with how transparency works and order of elements displayed (because of parallel processing). Oh, ideally I want web canvas API, but which allows to pass a buffer of lines to draw instead of one ;)
older docs are forever there. what it needs is more training data with new APIs.
Actually, because older docs are there, you can ask to update some old code to newer versions automatically.
Point is that it needs enough examples with a newer version.
Also, reasoning models are pretty good at spotting which version they are using.
(tested not with tailwind, but some other JS libs).
they pretty much know it.
Also, many speedrunners just run, while research is done and "published" by people before, pretty much using all the hacking technics.
A lot of stuff is simple, like cleaning brushes around the house, replacing wooden fences with metal/stone. More harder - changing ventilation for the attics. Except it is still not popular, so nobody would do it, if not mandated.
Laws are nice, when they work, clear and applicable.
It is probably would be as useful, as GDPR. Like of course, it sounds nice on the paper, but in reality it will get drown in a lot of legalize. Like with tracking consent in forms nowadays. Do you know which companies you gave consent and when? - me neither.
The issue with such laws, is that they are extremely wide and hard to regulate/enforce/check. But making regulation would make a few political points. While probably not so useful in real life.
We already do a lot falling under these baskets for years, big tech uses AI for algorithms left and right. "Ooopsie, we removed your youtube channel / application, because our AI system said so. You can talk to another AI system next." - we already have these, but I don't hear any reasonable feedback from EU for this.
Basically, big companies with strong legal departments would find the way around the rules. Small startups would be forced to move.
AI used for social scoring (e.g., building risk profiles based on a person’s behavior) - Oh, so insurance, and credit score is banned now? And background checks.
AI that manipulates a person’s decisions subliminally or deceptively. - Oh, so no more ads?
AI that exploits vulnerabilities like age, disability, or socioeconomic status. - Oh, are we banning facebook now?
AI that attempts to predict people committing crimes based on their appearance. - pretty sure that exists somewhere too.
AI that uses biometrics to infer a person’s characteristics, like their sexual orientation. - oh, my, tiktok does not even needs biometrics, just a couple of swipes. Google actually too, just where you visit.
AI that collects “real time” biometric data in public places for the purposes of law enforcement. - but cameras everywhere are ok.
AI that tries to infer people’s emotions at work or school. - like every social network, right? or a company with toxic marketing, but without ai (hello, apple with green bubbles)
AI that creates — or expands — facial recognition databases by scraping images online or from security cameras. - oh, this also probably exists. So companies could track clients.
of course. Each user input would be compared with other user input and existing data in the model before. Only legit and cross-referenced data could be used. Other data could still be used but marked as "possible controversial data". Good model should know that controversial data exists too and should distinguish it from the proper scientific data on each topic.
Bad reddit comment though, try pair programming with it.
Reasoning usually comments on your request, extends it, figures out which solution is the best and usable, backtracks if finds issues implementing it, proposes a new solution and verifies that it kinda makes sense.
The result after that could actually look different though for usual questions (i.e. summarised in a way chatgpt answers on questions would look like).
But it is usually very coherent with the code part, so if for example it has to choose from two libraries - it will use the one from the reasoning part, of course.