Easily done:

1. Wait for AI bubble to burst
2. Buy render farm on the cheap
3. Avatar 4

Although I’m assuming that the raw rendering pipeline is what costs the most. I could be dead wrong about that - there’s a whole army of artists, technical people, and actors that go into such a production too.

Thank you for your service.

Oooh, rocking an HP? I too like to live dangerously.

But seriously, that’s good to know. Those are probably easier to come by out in the wild. It really looks like Thinkpads go from office deployments straight to refurb companies these days. I never see them at thrift stores, and I’m not brave enough to dumpster-dive at e-waste.

Sometimes, old machines are survivors. Beware of confirmation bias when trash/thrift-picking cheap systems though. IMO, Thinkpads can be tough as a coffin nail. Including work systems, I’m on number 8 at this point with no hardware failures in sight.

That said, I have a very lightweight Acer that’s about a decade old with the worst keyboard and trackpad ever manufactured. It also performs like a slug, even with Linux on it. Still, it refuses to break so I can get rid of it.

As someone that can’t do corn chips, “nachos” with potato chips are a darn good substitute. This dish is on the “loaded fries to side-of-fries” spectrum. 10/10 looks perfect.

This essay is brought to you by Raid: Shadow Legends.

FWIW, Sony owns a lot of other companies, and so does Sony Corp. of America. It’s entirely possible that they’re dodging this one by using a company that’s not Sony Pictures.

I mean, that happens with CloudWatch all the time. It’s the most plausible part about this.

I use a system prompt that forces it to ask a question if there are options or if it has to make assumptions

I’m kind of amazed that even works. I’ll have to try that. Then again, I’ve asked ChatGPT to “respond to all prompts like a Magic 8-ball” and it knocked it out of the park.

so I start a new chat frequently.

I do this as well, and totally forgot to mention it. Yes, I keep the context small and fresh so that prior conversations (and hallucinations) can’t poison new dialogues.

I also will do the same prompts on two models from different providers at the same time and cross reference the idiots to see if they are lying to me.

Oooh… straight to my toolbox with that one. Cheers.

That’s been my biggest problem with the current state of affairs. It’s now easier to research newer tech through an LLM than it is to play search-result-wack-a-mole, on the off chance that what you need is on a forum that’s not Discord. At least an AI can mostly make sense of vendor docs and extrapolate a bit from there. That said, I don’t like it.

When writing code, I don’t let AI do the heavy lifting. Instead, I use it to push back the fog of war on tech I’m trying to master. At the same time, keep the dialogue to a space where I can verify what it’s giving me.

1. Never ask leading questions. Every token you add to the conversation matters, so phrase your query in a way that forces the AI to connect the dots for you
2. Don’t ask for deep reasoning and inference. It’s not built for this, and it will bullshit/hallucinate if you push it to do so.
3. Ask for live hyperlinks so it’s easier to fact-check.
4. Ask for code samples, algorithms, or snippets to do discrete tasks that you can easily follow.
5. Ask for A/B comparisons between one stack you know by heart, and the other you’re exploring.
6. It will screw this up, eventually. Report hallucinations back to the conversation.

About 20% of the time, it’ll suggest things that are entirely plausible and probably should exist, but don’t. Some platforms and APIs really do have barn-door-sized holes in them and it’s staggering how rapidly AI reports a false positive in these spaces. It’s almost as if the whole ML training stratagem assumes a kind of uniformity across the training set, on all axes, that leads to this flavor of hallucination. In any event, it’s been helpful to know this is where it’s most likely to trip up.

Edit: an example of one such API hole is when I asked ChatGPT for information about doing specific things in Datastar. This is kind of a curveball since there’s not a huge amount online about it. It first hallucinated an attribute namespace prefix of data-star- which is incorrect (it uses data- instead). It also dreamed up a JavaScript-callable API parked on a non-existent Datastar. object. Both of those concepts conform strongly to the broader world of browser-extending APIs, would be incredibly useful, and are things you might expect to be there in the first place.

The answer is: binary, sometimes with electrical switches.

As late as the very early 1980’s, the PDP-11 could be started by entering a small bootstrap program into memory, using the machine’s front panel:

You toggle the switches to make the binary pattern you want at a specific location in RAM, then hit another button to store it. Repeat until the bootstrap is in RAM, and then press start to run the program from that first address. Said start address is always some hardwired starting location.

And that’s a LATE example. Earlier (programmable) systems had other mechanisms for hard-wired or manual input like this. Go back far enough and you have systems that are so fixed-function in nature that it’s just wired to do one specific job.

Goddamn. That might actually be worth it.

Well, now I wanna know. How much money is worth life-altering injuries, including a concussion?

Yeah, all I know are the occasional bits and pieces that wash up here on Lemmy. I knew he was bad news, but I didn’t know he was a trumper. Wow.

Some times, the old ways are best.

Eh, I didn’t have to get every last set, but the ones that were too rusted/gunked to work… yeah. I’m almost a contortionist and some of those were complete bastards to install. Everywhere the Makita didn’t fit, yeah, hand-cramp city.

I know it’s not in-line with the latest kitchen trends but holy cow is this a functional workspace. You don’t “prepare meals” here. You build cuisine in a space like this.

Have you got any cabinet modifications you have done to make everything easier?

New-old house this year. Drawer slides and drawer-pulls were first to go. All were sticky, impossible to clean, and didn’t work half the time.

Every time.

I have left this as an exercise for the reader.

Fixed: