Setup AdGuard-Home for both blocking ads and internal/split DNS, plus Caddy or another reverse proxy and buy (or recycle/reuse) a domain name so you can get SSL certificates through LetsEncrypt.
You don't need to have any real/public DNS records on that domain, just own the domain so LetsEncrypt can verify and give you SSL certificate(s).
You setup local DNS rewrites in AdGuard - and point all the services/subdomains to your home servers IP, Caddy (or similar) on that server points it to the correct port/container.
With TailScale or similar - you can also configure that all TailScale clients use your AdGuard as DNS - so this can work even outside your home.
I also get “there were crawl errors”, which upon investigation are for pages that never existed (and I’ve owned the domain for 20 years, so its not a previous owner/operator thing)
Countries in Europe realized that if USA sanctions International Criminal Court judge - that judge suddenly loses access to their email/calendar/docs/etc because Microsoft/Google/etc have to comply.
Just like with plain git - in GitLab you can merge a branch that has multiple separate commits in it. And you can also merge (e.g. topical/feature) branches into one branch - and then merge that "combined" branch into main/master.
Though most teams/project prefer you don't stretch that route to the extreme - simply because it's PITA to maintain/sync several branches for a long period of time, resolving merge conflicts between branches that have been separate for a long time isn't fun, and people don't like to review huge diffs.
I guess what I'm saying is: for very large complex features, I don't want one big commit. I want to review a series of commits and then I want to have that series of commits persist in the history.
This is how Gerrit operates "natively" - the commit message and everything is part of the artifact under review exactly like the diff.
If the model is to squash an MR into a single commit before merging it, I'd then want to be able to have MRs that depend on each other.
You can "chain" them and there's some native support for this in Gitlab, but I can't say I've ever tried using it. If I really need a feature branch, I just create a separate branch and target my MR's to that until the whole thing is ready to land in main. Again, it seems less natural to me than how Gerrit does it.
Where did "AI for inference" and "semantic tagging" come from in this discussion? Typically for code repositories - AIs/LLMs are doing reviews/tests/etc, not sure what/where semantic tagging fits? Even do be done manually by humans.
And besides that - have you tried/tested "the amount of inference required for semantic grouping is small enough to run locally."?
While you can definitely run local inference on GPUs [even ~6 years old GPUs and it would not be slow]. Using normal CPUs it's pretty annoyingly slow (and takes up 100% of all CPU cores). Supposedly unified memory (Strix Halo and such) make it faster than ordinary CPU - but it's still (much) slower than GPU.
I don't have Strix Halo or that type of unified memory Mac to test that specifically, so that part is an inference I got from an LLM, and what the Internet/benchmarks are saying.
The way Gerrit handles this is to make a series of PR-like things that are each dependent on the previous one. The concept of "PR that depends on another PR" is a really useful one, and I wish forges supported it better.
Here in NL - Casio FX-82NL is allowed during test/exams for middle/high school, and actually for Radio Amateur/HAM licence exam - they even hand you one of their FX-82NLs.
Other more advanced (graphing, with memory/Python/etc) are also allowed in some places, but they need to be set to exam mode that disables memory/python/etc.
The tring that Ukraine and Arab Spring have in common - is that same folks that managed to bring Milošević down in Serbia (known as Resistance/Otpor), later went on to talk/teach protestors in Ukraine, Egypt ...etc.
Check out #Post Milošević; and #Legacy; sections on https://en.wikipedia.org/wiki/Otpor (couldn't figure out how to get deeplinks on mobile).
TL;DR: Besides Ukraine and Egypt, they went to a few more places, in some it worked, in others it didn't. And there were revelations of foreign (e.g. USAID) funding.
Of course you can fake a small/large crowd in a protest.
From the top of my head I can think of news reporting both "few (tens of) thousands" vs "hundreds of thousands" (different news reporting different numbers/estimates/etc) in 2025 protests in Serbia/Belgrade, as well as those comparisons of Obama vs Trump inauguration news/photos.
Meanwhile to you as an individual there on the spot - both crowds of say 50K-100K and 1M+ look basically the same = "huge amounts of people in every direction that you look".
Counting large crowds is hard, but the tools continue to improve: we have increasingly advanced drone photography and access to better AI tools to generate more reliable estimates.
If crowd sizes become a significant point of contention it'll become increasingly commonplace for multiple parties to take lots of aerial video and photos that serve as independent verification. You could probably get a pretty accurate estimate of how many people show up to an event by sending drones to take photos every 15 minutes.
In any case, I think the problem you highlight is more focused towards the upper-end, while I was thinking about the lower end of the spectrum. Where some people might be very vocal online, but they're unable to gather more than a dozen or two people for any given protest. If a protest is gathering an unknown number of people that ranges between 100k and 1 million that sounds like a really good problem to have.
Your criticism of inconsistent people estimates are valid, I'm not sure if newspapers have published the set of tools and criteria that they use when generating these estimates, so that's an area where it would be great to see increased transparency.
While 100K itself is indeed impressive - the order of magnitude difference between 100K and 1M makes a lot of room for interpretations, rationalizations, spins ...etc.
The "publishing the set of tools and criteria used to generate estimates" is happening, and so far it seems that usually doesn't matter.
It doesn't matter because of course those sources/news that report wildly wrong (be it larger or smaller numbers) are usually (not always, but very commonly) controlled by the governments.
So despite students that organized the biggest protests in Belgrade giving their estimates (based on combo of RSVP and how many people accommodated people from other cities). And those being close to independant research (using drone footage, VR/AR crowd simulations, AI) with loads of posts/videos providing detailed explanations ...
Most "ordinary people" saw (and keep seeing) just the "official version".
