IMO, because it's good in a way or another. I'm not reading your writing because I imagine you toiled over every word of it, but simply because I started reading and it seemed worthwhile to read the rest.

Or, to use a different metaphor, these comments are mentally nutritional Doritos, not a nicely prepared restaurant meal. If your restaurant only serves Dorito-level food, I won't go there even if I do consume chips quite often at home.

I've heard people express that they liked working in retail. By extension somebody must have enjoyed being a bank teller. After all, why not? You get to talk to a lot of people, and every time you solve some problem or answer a question and get thanked for it you get a little rush of endorphins.

Many jobs that suck only suck due to external factors like having a terrible boss or terrible customers, or having to enforce some terrible policy.

But imagine working in a nice cafe in a quiet small town, or a business that's not too frantically paced, like a clothing store. Add some perks like not always doing the same job and a decent boss, and it shouldn't be too bad. Most any job can be drastically improved by decreasing the workload, cutting hours and adding some variety. I don't think being a cashier is inherently miserable. It's just the way we structure things most of the time makes it suck.

Just like you think a human touch makes art special, a human touch can make a mundane job special. A human serving coffee instead of a machine can tell you about what different options are available, recommend things, offer adjustments a machine might not, chat about stuff while it's brewing... You may end up patronizing a particular cafe because you like the person at the counter.

Something like 1.61B just doesn't mean much to me since I don't know much about the guts of LLMs. But I'm curious about how that translates to computer hardware -- what specs would I need to run these? What could I run now, what would require spending some money, and what I might hope to be able to run in a decade?

In practice, models can be quantized to smaller weights for inference. Usually, the performance loss going from 16 bit weights to 8 bit weights is very minor, so a 1 billion parameter model can take 1 gigabyte. Thinking about these models in terms of 8-bit quantized weights has the added benefit of making the math really easy. A 20B model needs 20G of memory. Simple.

Of course, models can be quantized down even further, at greater cost of inference quality. Depending on what you're doing, 5-bit weights or even lower might be perfectly acceptable. There's some indication that models that have been trained on lower bit weights might perform better than larger models that have been quantized down. For example, a model that was trained using 4-bit weights might perform better than a model that was trained at 16 bits, then quantized down to 4 bits.

When running models, a lot of the performance bottleneck is memory bandwidth. This is why LLM enthusiasts are looking for GPUs with the most possible VRAM. You computer might have 128G of RAM, but your GPU's access to that memory is so constrained by bandwidth that you might as well run the model on your CPU. Running a model on the CPU can be done, it's just much slower because the computation is so parallel.

Today's higher end consumer grade GPUs have up to 24G of dedicated VRAM (an Nvidia RTX 5090 has 32G of VRAM and they're like $2k). The dedicated VRAM on a GPU has a memory bandwidth of about 1 Tb/s. Apple's M-series of ARM-based CPU's have 512 Gb/s of bandwidth, and they're one of the most popular ways of being able to run larger LLMs on consumer hardware. AMD's new "Strix Halo" CPU+GPU chips have up to 128G of unified memory, with a memory bandwidth of about 256 Gb/s.

Reddit's r/LocalLLaMA is a reasonable place to look to see what people are doing with consumer grade hardware. Of course, some of what they're doing is bonkers so don't take everything you see there as a guide.

And as far as a decade from now, who knows. Currently, the top silicon fabs of TSMC, Samsung, and Intel are all working flat-out to meet the GPU demand from hyperscalers rolling out capacity (Microsoft Azure, AWS, Google, etc). Silicon chip manufacturing has traditionally followed a boom/bust cycle. But with geopolitical tensions, global trade barriers, AI-driven advances, and whatever other black swan events, what the next few years will look like is anyone's guess.

How do we know? Play a game with the computer, and see who wins.

There's no reason why we can't apply the same logic elsewhere. Set up a testable scenario, see who wins.

The error here is thinking that dogs understand anything.

Our perceptions are shaped by our cognitive limitations. A dog doesn't know what the Internet is, and completely lacks the cognitive capacity to understand it.

An ASI would almost certainly develop some analogous technology or ability, and it would be completely beyond us.

That does NOT mean we would notice we were being affected by that technology.

Advertising and manufactured addictions make people believe external manipulations are personal choices. An ASI would probably find similar manipulations trivial.

But it might well be capable of more complex covert manipulations we literally can't imagine.

The reason I mentioned my dog is because, even though dogs have limited intelligence compared to humans, my dog thinks he's better at playing ball than me. What he doesn't know is that I let him win because it makes him feel in control.

With dogs it’s less a question of intelligence but communication something more intelligent AI is unlikely to have a problem with.

What would our being baffled by a super-intelligence look like? Maybe some effect like dark matter. It would make less sense the more we found out about it, and because it's on a level beyond our comprehension, it would never add up. And the lack of apparent relevance to a super-intelligence's doings would be expected, because it's beyond our comprehension.

But this is silly and resembles apologies for God based on his being ineffable. So there's a way to avoid difficult questions like "what is his motivation" and "does he feel like he needs praise" because you can't eff him, not even a little. Then anything incomprehensible becomes evidence for God, or super-intelligence. We'd have to be pretty damn frustrated with things we don't understand before this looks true.

But that still doesn't work, because we're not supposed to be able to even suspect it exists. So even that much interaction with us is too much. In fact this "what if" question undermines itself from the start, because it represents the start of comprehension of the incomprehensible thing it posits.

It’s a form of communication. You can learn to distinguish different kinds of barking a healthy dog is making, but that doesn’t mean you’re going to care nearly as much about a large animal showing up.

A dog will walk around the house, look at everything, smell everything, and touch many things. It makes things like finding slippers much easier.

I'm not sure we'd enjoy a robot doing the same, randomly wandering around the house and poking at stuff for some unspecified and uncommanded purpose.

But I believe Ryanair considered trying not to use seats at one point.

Keep in mind, I also had a flight attendant tell me that using Zoom on a plane is a felony.

Although in both cases, it's hard to tell if they were serious, or just doing PR.

At peak season every year, O’Leary says something crazy like they are going to charge for the bathroom, or charge fat people extra, or get rid of arm rests, or have standing room only. The tabloids run the story, and always mention how cheap the flights are, including whatever the cheapest deal at the moment is.

It’s very, very obvious advertising. The tabloids go along with it because it makes people angry, which drives traffic.

Think of it: a lot of people listen to music as a background of some kind. That means they don't want to keep going "Ugh, this one sucks, next, next, next..."

But, there's thousands of absolutely excellent songs that are time tested. You can play top 100 from the 80s and not be annoyed most of the time.

But ever time somebody plays Prince or Duran Duran is a time they're not playing the song you just released.

I've had a DDS4 tape way back, which ended up dying, and that could well be the cause. My house is not going to be as clean as a server room.

I've seen tape drives taken apart and there seems to be a worrying lack of concern with any kind of air filtration on the ones I've seen at least. And I don't think it should be all that hard to deal with it. Maybe something like sucking air in through a replaceable filter and exhausting it out of the tape door.

Turns out that modern drives can stretch the tape to make tracks line up right. It makes sense that as density grows, the real world effects of things like temperature and humidity require more and more work to compensate for.

There are far better ways to do this, but they require software engineering, not €3 and 15 minutes.

How does the computer knows that? You mean the parts that can meassure temperature will meassure where it gets warmer, or where it doesn't get warmer, altough it should?

How does the system knows, it is not a local heat pipe, transferring heat away?

* In modern times, the practical benefit from a microkernel is minimal. Hardware is cheap, disposable, and virtual machines exist. The use case for "tolerate a chunk of the kernel misbehaving" are minimal.

* To properly tolerate a partial crash takes a lot of work. If your desktop crashes, you might as well reboot.

* Modern hardware is complex and there's no guarantee that rebooting a driver will be successful.

* A monolithic kernel can always clone microkernel functionality wherever it wants, without paying the price elsewhere.

* Processes can't trust each other.

The last one is a point I hadn't realized for a while was an issue, but it seems a tricky one. In a monolithic kernel, you can have implicit trust that things will happen. If part A tells part B "drop your caches, I need more memory", it can expect that to actually happen.

In a microkernel, there can't be such trust. A different process can just ignore your message, or arbitrarily get stuck on something and not act in time. You have less ability to make a coherent whole because there's no coherent whole.

> A different process can just ignore your message

> arbitrarily get stuck on something and not act in time

This doesn't make sense. An implementation of a microkernel might suffer from these issues, it's not a problem of the design itself. There are many ways of designing message queues.

Also:

> In a microkernel, there can't be such trust [between processes]

Capabilities have solved this problem in a much better and scalable way than the implicit trust model you have in a monolithic kernel. Using Linux as an example of a monolith is wrong, as it incorporates many ideas (and shortcomings) of a microkernel. For example: how do you deal with implicit trust when you can load third-party modules at run-time? Capabilities offer much greater security guarantees than "oops, now some third-party code is running in kernel mode and can do anything it wants with kernel data". Stuff like the eBPF sandbox is like a poor-man's alternative to the security guarantees of microkernels.

Also, good luck making sure the implicitly trusted perimeter is secure in the first place when the surface area of the kernel is so wide it's practically impossible to verify.

If you allow me an argument from authority, it is no surprise Google's Fuchsia went for a capability-based microkernel design.

It’s design largely failed at being a modern generic operating system and it’s become primarily an os used for embedded devices which is an entirely different set of requirements

It’s also not that widely used. There’s only a handful of devices that ship fuschia today. There’s a reason for that.

It’s quite disingenuous to use “success” as a metric when discussing the advantages microkernel vs monolithic, as the only kernels you can safely say have succeeded in the past 30+ years are three: Linux, NT and Mach, one of which is a microkernel (of arguably dated design), and the other is considered a “hybrid microkernel.”

Did L4 fail? What about QNX?

This topic was considered a flame war in the 90s and I guess it still isn’t possible to have a level-headed argument over the pros and cons of each design to this day.