Ok, yes, I support actions like these, and they are good for community defense against small civilian fascist groups. There are not the numbers to counter organizations like FBI, DHS, or national guard though. Things are a bit different when the fascist group you’re trying to counter is the federal or state government with the will to kill and immunity from their actions.
The left is such a small population in the US, it’s irrelevant. If we are to believe Trump’s rhetoric, any group that becomes too much of a nuisance will be deemed “the enemy within,” and be shot.
IMO, the U.S. will become similar to Russia. It’s not some sudden societal collapse scenario; just an oligarchy with high levels of corruption and incompetence. Most people will conform or keep their heads down to avoid the consequences of stepping out of line. If you’re in a possibly targeted group, you may want a valid passport though. And it’s always been a good idea to keep at least a months worth of non-perishable food on hand in case of supply chain disruptions. Possibly stuff like emergency propane heaters and a propane tank could be useful too (they’ve been useful for me in the past already without an authoritarian government or social unrest). Knowing your neighbors and helping eachother out in little ways is probably the most powerful thing though.
Source? First I’ve heard of anything like this. I’d imagine a lot of things would have to be settled in court given the US’s strange laws giving states so much leeway in how they conduct federal elections.
Factories I’ve worked at had vending machines filled with microwavable food (burritos, burgers, sandwiches, etc). All of it was pretty disgusting.
Thought this was a Republican ad for a second. Similar language and appeal to fear and ignorance.
Code should be self-documenting. That way it is never outdated. Here’s an example of this similar to what you can expect to see in practice:
def nabla_descent(X, y, theta, alpha, delta, nabla):
m = len(y)
for _ in range(delta):
h = X.dot(theta)
nabla = (1/m) * X.T.dot(h - y)
theta = theta - alpha * nabla
return theta
I (probably unreasonably) despise using web front-ends for desktop applications.
GTK is OK. QT is very feature rich, but that adds complexity. Both can be cross-compiled to most systems and shipped with all the required libraries pretty easily.
I haven’t used it in a long while, but I remember liking Java Swing for some reason. Java should be “write once, run anywhere.” But, cross-compiling isn’t usually too hard, so not sure how much that matters. There’s more modern frameworks for JVM-based languages now, but I haven’t tried them.
I’ve noticed Gradio is popular in the ML community (web-tech based, and mostly used for quick demos/prototypes).
Edit: For web applications, I prefer Angular’s more traditional architecture over React’s hook architecture.
Haven’t tried Gemini; may work. But, in my experience with other LLMs, even if text doesn’t exceed the token limit, LLMs start making more mistakes and sometimes behave strangely more often as the size of context grows.
This is more complicated than some corporate infrastructures I’ve worked on, lol.
I usually just use VS Code to do full-text searches, and write down notes in a note taking app. That, and browse the documentation.
Nah, LLMs have severe context window limitations. It starts to get wackier after ~1000 LOC.
Python is quite slow, so will use more CPU cycles than many other languages. If you’re doing data-heavy stuff, it’ll probably also use more RAM than, say C, where you can control types and memory layout of structs.
That being said, for services, I typically use FastAPI, because it’s just so quick to develop stuff in Python. I don’t do heavy stuff in Python; that’s done by packages that wrap binaries complied from C, C++, Fortran, or CUDA. If I need tight-loops, I either entirely switch to a different language (Rust, lately), or I write a library and interact with it with ctypes.
C# is actually pretty nice. Ecosystem, not so much, but D doesn’t really have one anyways :)
Yeah, the image bytes are random because they’re already compressed (unless they’re bitmaps, which is not likely).
This is good, IMO. People don’t have to smoke as much, so less damage is done to their lungs. Vapes, edibles, and concentrates that are not combusted are probably even less damaging.
Both times I’ve received ChipDrops, the loads were an entire dump truck; ~20 cubic yards. I just used a wheelbarrow, a many-tined pitchfork, and a garden rake to make multiple large mulched beds, and a small pile in my back yard. I now have multiple large mulched beds, use it to cover food scraps in my compost bin, and use some in my vegetable beds/paths. It’s about a full day’s work to handle it all. I think ChipDrop also allows people to notify other users you’re giving some away if you can’t use it all, or you could try something like Craigslist.
If you’re talking about naive bayes filtering, it most definitely is an ML model. Modern spam filters use more complex ML models (or at least I know Yahoo Mail used to ~15 years ago, because I saw a lecture where John Langford talked a little bit about it). Statistical ML is an “AI” field. Stuff like anomaly detection are also usually ML models.
OSMC’s Vero V looks interesting. Pi 4 with OSMC or Librelec could work. I’m probably going to do something like this pretty soon. I just set up an *arr stack last week, and just using my smart TV with the jellyfin app installed ATM.
My PC running the Jellyfin server can’t transcode some videos though; probably going to put an Arc a310 in it.
I haven’t checked it out in years. From my understanding, IPFS aims to be a distributed filesystem that kinda works like Bittorent. If you access a file, you then seed it. Last time I checked it out, the project was jumping on the crypto bandwagon… Just checked out their website now, and don’t know WTF it is.