catdog

The thing is, there is next to no software that "doesn't need further changes" at all. There is always something, sure it might be infrequent and/or most of the time nothing really big or difficult (except sometimes) but the point is: someone needs to step up and do it.

If a see a project with recent activity, best from multiple people it is a strong signal that this will happen, if the last commit is a year ago I must assume it's completely abandoned because most of the time it just is. Sometimes it's clearly communicated that it is the way because the authors see it as essentially feature complete, there are some examples of this but not that many honestly.

It's an application issue but implementation wise it's probably way more straightforward to just open a separate network connection per thread.

An LLM is an impressive, yet still imperfect and unpredictable translation machine. The code it outputs can only be as good as your prompt is precise, minus the often blatant mistakes it makes.

Yep writing the code might have gotten a little bit easier but was never was the hard part to begin with.

Like with most technological change I think there is no need for FOMO. You run into problems if you completely ignore already established and proven tools and practices for years to come but you don't have to jump onto every "this changes everything, trust me bro" hype.

Independent of ones philosophical stance on the broader topic: I find it highly concerning that AI companies, at least right now, seem to be largely exempt from all those rules which apply to everyone else, often enforced rigorously.

Also it's not only the work of "the model" it's the work of human beings the model is trained on, often illegally.

> The key phrase here is “requirements analysis” and if you’re not good at it either your software sucks or you’re going to iterate needlessly and waste massive time including on bad architecture. You don’t iterate the foundation of a house.

This depends heavily on the kind of problem you are trying to solve. In a lot of cases requirements are not fixed but evolve over time, either reacting to changes in the real word environment or by just realizing things which are nice in theory are not working out in practice.

You don’t iterate the foundation of a house because we have done it enough times and also the environment the house exists in (geography, climate, ...) is usually not expected to change much. If that were the case we would certainly build houses differently than we usually do.

As it is so often in life, extreme approaches are often bad. If you do pure waterfall you risk finding out very late that your plan might not work out, either because of unforeseen technical difficulties implementing it, the given requirements actually being wrong/incomplete or just simply missing the point in time where you planned enough. If you do extreme agile you often end up with a shit architecture which actually, among other things, hurt your future agility but you get a result which you can validate against reality. The "oh, I didn't think of that" is definitely present in both extremes.

> A better formulation is "every feature is a liability". Taking it to the line of code level is too prescriptive.

Amount of code is a huge factor but maybe not the best wording here. It's more a thing of complexity where amount of code is a contributing metric but not the only one. You can very easily have a feature implemented in a too complex way and with too much code (esp. if an LLM generated the code but also with human developers). Also not every feature is equal.

> Occasionally writing more verbose code is preferable if it makes it easier to understand.

Think this is more a classic case of "if the metric becomes a goal it ceases to be a metric" than it being a bad metric per se.

> People talk about an AI bubble. What we actually have is a GPU bubble. NVidia makes really expensive GPUs for AI. Others also make GPUs.

Yes it is. I think even for multiple reasons. Competition in that space not sleeping is one but it's also a huge overestimation of demand combined with the questionable believe those GPUs and the Datacenters housing them can actually be built and put into operation as fast as envisioned.

> The reason that this 100B deal is apparently being reconsidered is that it is a bad deal for OpenAI. It was going to overpay for a solution that they can get cheaper elsewhere. It's bad news for NVidia, good news for OpenAI. This deal started out with just NVidia. But at this point there are also deals with AMD, MS, and others. OpenAI like the other hyperscalers is not betting the company on NVidia/CUDA. Good for them.

I think in case of OpenAI both may be true. While what you are saying makes sense, NVs first mover advantage obviously can't last forever, OpenAI currently does have little to no competitive advantage over other players. Combine this with the fact that some (esp. Google) sit on a huge pile of cash. In contrast for OpenAI the party is pretty much over as soon as investors stop throwing money into the oven so they might need to cut back a bit.

Maybe but it's far from profitable. People largely don't want to pay for it either.

Well they tried and they failed. In that case maybe the smartest move is not to play. Looks like the technology is largely turning into a commodity in the long run anyways. So sitting this out and letting others make the mistakes first might not be the worst of all ideas.

Maybe some/many even are? For "AI" companies it's not really a big expense in comparison and they depend hugely on keeping the hype going.

Exactly, other billionaires having calmer personality types does not make them less nuts.

I think it depends how visible the CEO is to (potential) customers, in this case very visible, he is in the media all the time.

There would be WebDAV which adds such features to HTTP but that's also not supported by web browsers.

Writing the code in the grand scheme of things isn't the hard part in software development. The hard parts are architecture and actually building the right thing, something an LLM can't really help you with.

It's not AI, there is no intelligence. A language model as the name says deals with language. Current ones are surprisingly good at it but it's still not more than that.

It probably depends if they also change eating habits. If they change nothing regaining the weight is no surprise.

Side effects? Also many might not be able to afford it long term as it's quite expensive.

LLMs are somewhat useful compared to NFTs and other blockchain bullshit which is nearly completely useless. It will be interesting what happens when the money from the investment bubble dries out and the real costs need to be paid by the users.

I would not say all of them but in general I agree, there is not one correct one but many correct ones.

Exactly that. Not only he got re-elected, during his first term he did bad things but what he did now while not even 2 months in office seems way worse. Also it's clearly visible that the checks and balances are now severely broken, you have an administration not even abiding its own countries laws in very fundamental areas, that does not spark trust. Heck he even discredits and breaks trade deals signed by himself, who can trust such a country?

It was easy to justify sitting out Trump I as a (former) US allied, Trump II demands immediate action.

That's not the main problem. They chose Debian Stable which by design is not and never was the best choice for bleeding edge hardware.

Consoles use AMD GPUs for years now.

Wouldn't say it ruined it. People used them as cheap computers because at the time there barely were good alternatives for that cheap of a computer.

> N100 is inexpensive, has impressive performance, and can support 16+ GB RAM.

Yep runs 32 GB just fine, even if not advertised. Also great Software support as usual on the PC Platform. Also more I/O, esp. PCIe than a Pi and you actually can buy boards with standard connectors. Also at least for server type use cases x86 is most of the time probably still a lot less painful than ARM.

> How to make the best of my situation?

Keep going with your shitty job, gain experience and keep trying. I don't know anything about options in your specific niche but in general with some experience it's usually easier to land a good job than directly after graduation, esp. during an economic downturn. Things might already look much better 1-2 years down the line.

Alternatively bite the other kind of bullet and be more flexible in what kind of job you apply to, with a bit of luck you might even like doing something else as much as what you do now.

> the economy in Europe is really just shitting itself and will likely only deteriorate in the coming years

I call bullshit, there is no reason why it can't recover.

YAML is fine, esp. compared to the huge collection of often 10x worse config formats you have to deal with in the VM world.

Those kind of articles often read like an ad for managed cloud services. "We got rid of that complicated, complicated Kubernetes beast by cobbling together 20 bespoke managed services from provider X which is somehow so much easier".