There’s also the alternative “grills” vs. bouys" pair.

Instead of destroying the universe, can we destroy prior, failed shuffle/check iterations to retain o(1)? Then we wouldn’t have to reload all of creation into RAM.

It’s hard to explain. A lot of it is about vibes and focus over the last several years.

1. There’s a popular suspicion that, rather than fixing issues, Dems allowed them to persist so they could campaign on them during an election year.
2. Dems’ platform in 2016 was: Hillary’s more competent. In 2020: Trump’s a menace. In 2024: Trump’s a menace. Meanwhile, people cared more about putting food on the table, not dying of the plague, and war crimes. Sure, welfare was part of Dems plans and platform, but it weren’t the core message.
3. Related to #2, people felt unheard, ignored, and taken for granted. We’ve been losing faith in a 2-party system, where neither side has to be good, they just have to threaten that the other side is worse. Well, wehn people feel they have nothing to lose, they put a bull in the china shop and hope they wind up on top when the dust settles.

Bernie’s being a bit harsh in saying Dems didn’t try. Republicans blocked their efforts. But there’s also a feeling that they didn’t care all that much. At the end of the day, they’re career politicians, padding their pockets with corporate donations while demanding starving citizens vote for them because the other guy would be somewhat less palatable. And I guess Trump’s honesty about being apathetic and money-grubbing is more appealing than Dems’ feigned innocence and solidarity.

Reminds me of the Reboot hotel offices.

No, it just goes to its extraction point! …somehow.

For LLMs, I’ve had really good results running Llama 3 in the Open Web UI docker container on a Nvidia Titan X (12GB VRAM).

For image generation tho, I agree more VRAM is better, but the algorithms still struggle with large image dimensions, ao you wind up needing to start small and iterarively upscale, which afaik works ok on weaker GPUs, but will gake problems. (I’ve been using the Automatic 1111 mode of the Stable Diffusion Web UI docker project.)

I’m on thumbs so I don’t have the links to the git repos atm, but you basically clone them and run the docker compose files. The readmes are pretty good!

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As a highly sensitive person, what I’ve learned for me is:

1. It takes time - years, even - to understand what happened, and why. Which means there’s nothing productive to be done except avoid things you’d regret. Be your best self, even if it’s hard as hell. If you care about this person, give them the space they evidently need; and leave the door open to reconnecting later in until you’ve decided, with a clear head and understanding why, that you’ll never eant them in your life.
2. Prioritize caring for your basic mental and physical needs by getting enough sleep, food, exercise, and time outdoors.
3. Treat yourself like you’re sick with the flu or a cold. Get rest if you can. Find ways to relax. Give yourself time to heal. Mindless things like TV or videogames can be good. Socializing is also good.
4. Partners can ground us; make us feel secure, taken care of, connected to our world, full of purpose and value, etc. In the long term, without them, you need to re-ground and find things that give you those feelings. I had to come up with a list of things that make me feel connected and worthwhile, then take steps to engage in those. It included creative hobbies and dedicating time to good friends. Finding “myself” and things that felt meaningful took work: self-reflection and journaling, forcing myself to do hobbies until I enjoyed them, and becoming inspired by good art (TV, music) I love. Often our roots are in our upbringing, so it can be good to reconnect with things we loved. Once you have a life without your ex, you don’t need them. You don’t need any partner as much, for that matter, because what sustains you is more within your power and identity. And that’s how future relationships can be made safer, and heartbreak survivable.

I loved my course on patterns. It was tough, but I now regularly feel like I can apply mastery of this tricky subject to my software projects. The course used a variety of techniques:

• Read the seminal Design Patterns book by Gamma et al., for an overview of the concepts.
• Every week, we’d incorporate three patterns into a preexisting XML processor project. My final one had like 25 patterns, which was challenging to keep working amidst refactoring. (You don’t have to do them cumulatively, but I enjoyed it.)
• We’d have to ask pattern-specific questions of our classmates in forum threads; and occasionally we’d be assigned to answer some.
• We each wrote up our own pattern. (I designed one based on my experiences handling data exchange between web apps and clients.)

Together, this taught us

• How the patterns could concretely look in practice.
• Pros, cons, and other considerations for each.
• Similaraties, differences, and nuances. (We’d joke that everything was the Template pattern if you squinted.)
• The impact of modifications to the patterns.
• How to recognize, create, hone, collaborate on, and share patterns.

I appreciate this approach because patterns are an inherently fuzzy subject.

It’s more like languages evolved to incorporate the most common idioms and patterns of their ancestors. ASM abstracted common binary sequences. C abstracted common ASM control structures and call stacks. Java leaned hard on object orientation to enable compositional and inheritence-based patterns widely used in C and early OO languages. Python baselines a lot of those patterns, and makes things like the Null Object pattern unnecessary.

A cluster duck, if you will.

Some servers have a c/NoStupidQuestions

Passion. The people here care enough to have not only left Reddit, but to have made a new community here.

Shout out to Touhou.

I’m on a crusade to call them “lemlets”.

Can we call communities “lemlets?”