We have thumb drives that can store petabytes of data?
Or did you mean the "big data" crowd which thought 500GB was noteworthy? I don't think anyone took those serious, neither in 2010s nor now. That was always "small" data
Most companies using term "big data" had datasets in TB region. One company I had a gig at had full Hadoop cluster setup and their whole dataset was 40GB. Their marketing had all the big data adjacent keywords over the brochures for clients.
Doesn't Jira only have one primitive: the ticket.
Everything else just augments it.
You could say that these augmentations are separate primitives, but then the same would apply to all tools in the other cited examples like Photoshop too
There is a very valid reason why the Creator of erlang back in the day said something along the line of "you need to iteratively remake your software, improving it each time"
As your knowledge about a topic grows, your initial mistaken implementation may become more and more obvious, and it may even mean a full rewrite.
But yes, a person which instantly says "rewrite" before they understood the software is likely very inexperienced and has only worked with greenfield projects with few contributers (likely only themselves) before.
It shows that previously he likely worked only at companies which catered to him, honestly.
That was pretty widespread during 2005-2015, but it's been dropping extremely quickly now.
Developers are generally seen as replaceable cogs. Middle management loves to talk about "scaling" - by which they don't mean scaling how devs understand it, but instead multiplying headcount - because surely throwing x-n devs at the same software will multiply the velocity by the same factor amiright?
The biggest value you can get is by having a very small team of extremely capable people (with extremely high bus factor) being fully in control of everything they do.
Realistically speaking, that'd be impossible to "scale" in the perspective of an MBA however, hence the industry at wide doesn't to that.
You may notice that some employers do, however.
You're just unlikely to get a job there, because their team is already established.
That's a catch 22, I mean they literally are using the contractor... So yeah, they're effectively doing it.
The point was that they shouldn't use contractors and keep their citizens data private. Whenever they don't do that... that's an issue. Hence the critique.
That was the norm for some time, it's just being eroded over the years and is basically entirely gone at this point
Yes, animals have feelings and are intelligent (to varying degrees, but generally a lot more then most think). Modern meat factories are absolute shit shows and it's outlandishly bad our societies treat the animals like that.
However, it doesn't have to be that way. And killing an animal for food which lived a nice life is perfectly fine. We're all part of the physical reality in which the survival of the fittest reigns supreme. Even if you want to put your head into the sand and deny this, animals eating each other is perfectly normal. And yes, humans are animals too.
I’m not a vegetarian and have no plans on becoming one but.. just because eating meat is normal doesn’t mean it needs to stay that way.
There’s an endless list of atrocities committed by our ancestors or our peers in the animal kingdom that we no longer tolerate. There’s no reason why eating another animal can’t someday become as abhorrent as cannibalism or slavery or whatever.
If eating plant-based didn't make me sick (and I could tolerate gluten and cereals and carb-heavy foods), I'd do it. Now, one might go on a tirade that I'm doing it wrong, but from my research, it's pretty clear the body and the brain evolved for a high-fatty diet; or at least that's how I feel the best.
So here's the conundrum: should I be sick and avoid the food that makes me feel really good, because of ethical concerns? Self-preservation, I believe, should be the top-most concern.
Whenever I hear vegans preaching, I think of the quote "for every complex problem there is an answer that is clear, simple, and wrong" — if veganism works for you, I'm glad, but I wish most vegans would be a bit more empathetic and scientifically-minded rather than making people feel bad because, for many reasons, they live their life another way. A way, must I say, that is completely natural.
Honestly I'd rather have a discussion about nutrition with a vegetarian, than a preachy vegan that first insults me, shames me, before trying to hear my reasons.
And a corollary to that: when considering historical figures, before condemning them wholesale, consider how history would judge you if--for example--eating meat is considered in the future the way slavery is considered today
I disagree it was implied. Not to mention that in an honest conversation, I shouldn't have to point out that you've cherry picked a quote (which on its face doesn't mean what you apparently think it does) from its actual context.
The only people advocating for that are the same kind of people which were pitching the cloud as a solution for your hosting needs.
Ime the sweet spot for development with LLMs is to figure out what you need to do and then do that through AI. Yes, it'll still make some decisions there, but did you really get satisfaction from the decisions of eg what to call a class before? At last I didn't.
You can of course try to offload everything to the LLM and not tell it what to do, but only specify what it should enable (spec driven), but at that point youre gambling wherever the output will work and the project becomes unmaintainable - which may be fine too in certain scenarios, that's just pretty rare in a business context
> I wonder if reading so much LLM stuff lately has affected my idiolect and that I write (or worse, think) more machine-like than before...
Totally of topic ofc, but I always get triggered by the claim that llms are "machine-like".
I'm aware it's a total pet peeve and a lil irrational, but "machine-like" would imply to me that it's thinking like a machine, which in turn implies machine intelligence - which in turn implies they're doing something which they aren't.
I'm not trying to undersell their capabilities. Used well they're able to do a lot of things. But the way they achieve it is by mimicking human dialogue and rhetoric processes to facilitate this process. That's in my opinion anything but machine intelligence. I struggle finding an applicable word for it though
I didn't see your reply until now but "AI" is correctly describing the phenomenon. Most definitions for "artifice" converge around the idea of deception or insincerity.
The term "machine learning" also distinguishes itself from the organic process by authentic intelligence.
In other words, inferring "machine intelligence" is less correct than "artificial intelligence". By definition LLMs are machines pretending to think and they do it well enough to have a writing style.
Or did you mean the "big data" crowd which thought 500GB was noteworthy? I don't think anyone took those serious, neither in 2010s nor now. That was always "small" data
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