Yeah, I haven’t gone since. And I’m not going to not tip because it’s expensive. It’s just that when you’re paying $18 for a cocktail, you don’t exactly expect the bar to turn into a vending machine.

This was also after being told I was “in the wrong line” for the cocktail I wanted to order. And other people were walking in wearing basketball shorts. It was really quite a scene.

It was $18.

I once went to a fancy rooftop bar where I was asked to pay in full (with tip) up front for a cocktail. No idea how that place is still in business.

I like how Misfits and Magic handles this where wizards straight just have never heard of nuclear weapons.

But he soon discovered that the same credentials that allowed him to see and control his own device also provided access to live camera feeds, microphone audio, maps, and status data from nearly 7,000 other vacuums across 24 countries. The backend security bug

I feel like “bug” is doing a looot of heavy lifting here.

Harry Harlow proven right once again

Ah thanks for the correction. Makes sense that it had to happen during TLI since the SM engine wouldn’t have enough fuel for TLI, entering moon orbit, and exiting moon orbit.

I guess in my memory I was thinking they wouldn’t do such a maneuver without an immediate abort plan, but I think the SM engine could do an immediate about face or at least (obviously) get back to Earth on the free-return path after one loop around the Moon.

It orbited Earth several times before heading to the Moon. The maneuver that connected the LEM to the top of the command module happened in Earth orbit.

I’m mostly trying to describe a feeling I don’t hear named very often

That Funny Feeling?

I’ll give that a shot.

I’m running it in docker because it’s running on a headless server with a boatload of other services. Ideally whatever I use will be accessible over the network.

I think at the time I started, not everything supported Intel cards, but it looks like llama-cli has support form Intel GPUs. I’ll give it a shot. Thanks!

Not to mention, if you try to swallow a potato whole (as one does), you risk choking to death.

Thanks for the link. I was gonna ask if you were a writer, heh.

I agree. The tone of the ads this year felt almost like lampshading. Like if we acknowledge the problem, we’re wise to what the audience is feeling, but we’re not going to do a damn thing to address it. It’s just something that needs to be done to make the ad feel remotely relevant.

AI is scary, but don’t be afraid of our surveillance device because we acknowledged that AI is scary

AI will sell you ads. Anyway, you’re watching an ad for AI

Work sucks amirite? Why not let us unemploy you?

There’s a wealth gap. Spend money on our stuff.

And I’m not going to even link the He Gets Us ads.

It was an especially interesting case because there was a question of whether the photographer lied about who actually took the picture. So he could either claim the monkey took it an lose the copyright or claim he took it and have it lose all value.

Thanks for taking the time.

So I’m not using a CLI. I’ve got the intelanalytics/ipex-llm-inference-cpp-xpu image running and hosting LLMs to be used by a separate open-webui container. I originally set it up with Deepseek-R1:latest per the tutorial to get the results above. This was straight out of the box with no tweaks.

The interface offers some controls settings (below screenshot). Is that what you’re talking about?

Well, not off to a great start.

To be clear, I think getting an LLM to run locally at all is super cool, but saying “go self hosted” sort of gloms over the fact that getting a local LLM to do anything close to what ChatGPT can do is a very expensive hobby.

Any suggestions on how to get these to gguf format? I found a GitHub project that claims to convert, but wondering if there’s a more direct way.

GO self-hosted,

So yours and another comment I saw today got me to dust off an old docker container I was playing with a few months ago to run deepseek-r1:8b on my server’s Intel A750 GPU with 8gb of VRAM. Not exactly top-of-the-line, but not bad.

I knew it would be slow and not as good as ChatGPT or whatever which I guess I can live with. I did ask it to write some example Rust code today which I hadn’t even thought to try and it worked.

But I also asked it to describe the characters in a popular TV show, and it got a ton of details wrong.

8b is the highest number of parameters I can run on my card. How do you propose someone in my situation run an LLM locally? Can you suggest some better models?

That’s not even close to the worst of it.

https://en.wikipedia.org/wiki/Lee–Jackson–King_Day

You didn’t come into this world. You came out of it.

Yo momma’s so fat, she sat on a binary tree and squashed it into a linked list in O(1) time.