Kata1yst

No, I'm not conflating "a" with "b". I'm using stability exactly as it's used in physics.
https://phys.libretexts.org/Bookshelves/College_Physics/College_Physics_1e_(OpenStax)/09%3A_Statics_and_Torque/9.03%3A_Stability

My point is, it's a completely valid use of the word. And yes, so is reliable, though I think "reliable" fails to capture the essence of the system changing but maintaining it's state, hence why we don't study "reliable systems" in physics.

I recommend picking something else to be pedantic about.

Amazingly, for someone so eager to give a lesson in linguistics, you managed to ignore literal definitions of the words in question and entirely skip relevant information in my (quite short) reply.

Both are widely used in that context. Language is like that.

Further, the textbook definition of Stability-

the quality, state, or degree of being stable: such as

a: the strength to stand or endure : firmness

b: the property of a body that causes it when disturbed from a condition of equilibrium or steady motion to develop forces or moments that restore the original condition

c: resistance to chemical change or to physical disintegration

Pay particular attention to "b".

The state of my system is "running". Something changes. If the system doesn't continue to be state "running", the system is unstable BY TEXTBOOK DEFINITION.

Both are widely used in that context. Language is like that.

What the hell did you want them to do? Are you just looking for reasons to be outraged?

That's boiler plate EULA language for PR/forums, which is what it actually was for in full context. Believe me, I've read a ton of them for my job. Is it right? No. Is it enforceable? Largely no, it won't completely hold water if challenged in court. Is it effective at helping the legal department craft C&Ds, and terminate accounts when necessary? Absolutely. Purely a risk mitigation / CYA measure.

And someone took issue with it. Vultr didn't think it was an issue, but listened and took decisive, effective action anyway well before they would have been forced to. Then they made a full blog post to be transparent and owned it rather than hid from it. All in all, a pretty mature, proactive, community focused response.

Honestly I'm impressed by it, I find the negativity baffling.

I think the confusion comes from the meaning of stable. In software there are two relevant meanings:

1. Unchanging, or changing the least possible amount.

2. Not crashing / requiring intervention to keep running.

Debian, for example, focuses on #1, with the assumption that #2 will follow. And it generally does, until you have to update and the changes are truly massive and the upgrade is brittle, or you have to run software with newer requirements and your hacks to get it working are brittle.

Arch, for example, instead focuses on the second definition, by attempting to ensure that every change, while frequent, is small, with a handful of notable exceptions.

Honestly, both strategies work well. I've had debian systems running for 15 years and Arch systems running for 12+ years (and that limitation is really only due to the system I run Arch on, rather than their update strategy.

It really depends on the user's needs and maintenance frequency.

Yo this has been debunked multiple times. Those ToC were for their ~~website hosting services~~ forums and PR (sorry, I didn't read it properly the first time through), and they've already responded by removing the confusing language.

Yes, sorry. That is what I thought, I just phrased it very poorly.

My cat has been training for the next war her entire life.

Doesn't Kickstarter not pull funds until the project's success?

Yeah, most of the Mars missions planned are around 900 days round trip, around 500 of which will be on Mars waiting for the next transfer window. All of them include the astronauts being well shielded from radiation.

My favorite city builder in decades. A few notes.

Pros:

• Easy mode is relaxing and quite easy.
• Medium mode is a fun challenge at first, eventually becoming fairly chill as you advance in skill and confidence.
• Hard mode is always fairly hard, especially on harder maps.
• There are many resources to manage, but none that feel burdensome.
• The game is extremely thematic, it feels alive with charm.
• Graphics are excellent, though sometimes graphical glitches can still be encountered.
• The water. It's so hard to explain to someone who hasn't encountered this system before, but water is life in this game, and it's both beautiful graphically, and extremely well simulated by physics. Learning to control the water, and see the shortest paths to end water scarcity with beaver engineering is an amazingly fun and unique aspect of the game.
• Mods are well supported and the community is vibrant.

Cons:

• Not a ton of content. They've been very good about adding new mechanics (badwater, extract, etc) but there's still just 2 races of beaver and a dozen or so maps.
• No directed experience. In similar games I've enjoyed a campaign, challenge maps/scenarios, weekly challenges, a deeper progression system, just... Something to optionally set your goals. There's nothing of the sort in the vanilla game. It's fully open ended and there's only one unlock outside of your progress though the resource tree in a map.

All in all, I highly recommend it, especially at the modest asking price. If you love city builders, charming and beautiful art, thematic settings, dynamic challenge, and solution engineering, this is a fantastic game for you.

Other games I've enjoyed that scratch similar itches:

• KSP
• Cities: Skylines (but Timberborn has been far more compelling)
• Factorio
• Mindustry
• Planet Zoo (Timberborn has less of a directed experience, but is otherwise completely superior)
• Gnomoria
• Banished
• Tropico series (though I view this as more casual)

Get it and have fun is my recommendation.

Author doesn't seem to understand that executives everywhere are full of bullshit and marketing and journalism everywhere is perversely incentivized to inflate claims.

But that doesn't mean the technology behind that executive, marketing, and journalism isn't game changing.

Full disclosure, I'm both well informed and undoubtedly biased as someone in the industry, but I'll share my perspective. Also, I'll use AI here the way the author does, to represent the cutting edge of Machine Learning, Generative Self-Reenforcement Learning Algorithms, and Large Language Models. Yes, AI is a marketing catch-all. But most people better understand what "AI" means, so I'll use it.

AI is capable of revolutionizing important niches in nearly every industry. This isn't really in question. There have been dozens of scientific papers and case studies proving this in healthcare, fraud prevention, physics, mathematics, and many many more.

The problem right now is one of transparency, maturity, and economics.

The biggest companies are either notoriously tight-lipped about anything they think might give them a market advantage, or notoriously slow to adopt new technologies. We know AI has been deeply integrated in the Google Search stack and in other core lines of business, for example. But with pressure to resell this AI investment to their customers via the Gemini offering, we're very unlikely to see them publicly examine ROI anytime soon. The same story is playing out at nearly every company with the technical chops and cash to invest.

As far as maturity, AI is growing by astronomical leaps each year, as mathematicians and computer scientists discover better ways to do even the simplest steps in an AI. Hell, the groundbreaking papers that are literally the cornerstone of every single commercial AI right now are "Attention is All You Need" (2017) and
"Retrieval-Augmented Generation for Knowledge -Intensive NLP Tasks" (2020). Moving from a scientific paper to production generally takes more than a decade in most industries. The fact that we're publishing new techniques today and pushing to prod a scant few months later should give you an idea of the breakneck speed the industry is going at right now.

And finally, economically, building, training, and running a new AI oriented towards either specific or general tasks is horrendously expensive. One of the biggest breakthroughs we've had with AI is realizing the accuracy plateau we hit in the early 2000s was largely limited by data scale and quality. Fixing these issues at a scale large enough to make a useful model uses insane amounts of hardware and energy, and if you find a better way to do things next week, you have to start all over. Further, you need specialized programmers, mathematicians, and operations folks to build and run the code.
Long story short, start-ups are struggling to come to market with AI outside of basic applications, and of course cut-throat silicon valley does it's thing and most of these companies are either priced out, acquired, or otherwise forced out of business before bringing something to the general market.

Call the tech industry out for the slime is generally is, but the AI technology itself is extremely promising.