I use cloud computing to run a lot of my computer stuff. Not a PC. I self-host some services on a home-server. Also not a PC. I can install a GUI on these if I want and RDP into them, still doesn’t make these PCs.

I can use my personal laptop as a server if I want (and I have!) with remote-access enabled; so it is both a PC and a not-PC?

I think we have to settle on PC being usecase-driven; not hardware-defined. Which is what I think you were trying to get at, but abstracting too far.

That’s fair. I see what I see at an engineering and architecture level. You see what you see at the business level.

That said. I stand by my statement because I and most of my colleagues in similar roles get continued, repeated and expanded-scope engagements. Definitely in LLMs and genAI in general especially over the last 3-5 years or so, but definitely not just in LLMs.

“AI” is an incredibly wide and deep field; much more so than the common perception of what it is and does.

Perhaps I’m just not as jaded in my tech career.

operations research, and conventional software which never makes mistakes if it’s programmed correctly.

Now this is where I push back. I spent the first decade of my tech career doing ops research/industrial engineering (in parallel with process engineering). You’d shit a brick if you knew how much “fudge-factoring” and “completely disconnected from reality—aka we have no fucking clue” assumptions go into the “conventional” models that inform supply-chain analytics, business process engineering, etc. To state that they “never make mistakes” is laughable.

Absolutely not true. Disclaimer, I do work for NVIDIA as a forward deployed AI Engineer/Solutions Architect—meaning I don’t build AI software internally for NVIDIA but I embed with their customers’ engineering teams to help them build their AI software and deploy and run their models on NVIDIA hardware and software. edit: any opinions stated are solely my own, N has a PR office to state any official company opinions.

To state this as simply as possible: I wouldn’t have a job if our customers weren’t seeing tremendous benefit from AI technology. The companies I work with typically are very sensitive to CapX and OpX costs of AI—they self-serve in private clouds. If it doesn’t help them make money (revenue growth) or save money (efficiency), then it’s gone—and so am I. I’ve seen it happen; entire engineering teams laid off because a technology just couldn’t be implemented in a cost-effective way.

LLMs are a small subset of AI and Accelerated-Compute workflows in general.

That was no steakhouse. You straight up walked into a Mafia front. Like out of Michael Jackson’s Smooth Criminal music video.

No, you’re thinking of a dead lach. A deadlock is an anti folk music pioneer—not really dead yet though he claims to be dead inside.

Who can get there first?

Sometimes old software just has too much legacy spaghetti written in to really build from though. Starting from scratch gives new ideas room to breathe and grow that might otherwise be impossible to implement in the previous framework—which while probably useful can also be stifling. See the reason why Wayland is being written to replace Xorg.

I feel so compressed.

I don’t think an SSD is the right choice here. SSDs have a limited lifespan that’s majority driven by the number of writes that happen to a certain block. Reads are cheap and near infinite though.

When you’re talking about a Lemmy instance, mail server, etc. my mind thinks this is likely to be many writes with several read-once ops. This is a better use case for a HDD.

A media server that oriented towards most consumption (reading) would be better for SSD.

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Also PRISM. Maybe the third—wait, wrong side of the array—worst.

I like draw.io for process diagrams.

You mention ThePicardManeuver but leave out Stamets@lemmy.world???

When I’m prototyping some model deployment/application/backend, I choose Ubuntu. I’ve also chosen Debian Stable before.

When te decision has been made to actually write the fucking thing for real enterprise deployment, it’s always Alpine Linux so that we have fine control over literally every aspect of the image.

I’d never recommend Alpine for any other use case, tbh.

It was /c/amotio? Pitchforks out; GET ‘EM!

Xean Connery hates this simple trick.

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Because starting with ‘X’ does not guarantee the ‘sh’ sound. See ‘xylophone’, ‘Xavier’, ‘Xenon’.

Xitter looks like ‘exiter’ to me.

LoRA models still have the underlying fully trained base model underneath; it is not a complete replacement or complete modification of the model weights.

A true Debian user would never tell us that they use Debian. They would say they use Debian Testing’. BTW.