X-Com? Is that you?

The term for what you are asking about is AGI, Artificial General Intelligence.

I’m very down for Artificial Narrow Intelligence. It already improves our lives in a lot of ways and has been since before I was born (and I remember Napster).

I’m also down for Data from Star Trek, but that won’t arise particularly naturally. AGI will have a lot of hurdles, I just hope it’s air gapped and has safe guards on it until it’s old enough to be past its killing all humans phase. I’m only slightly joking. I know a self aware intelligence may take issue with this, but it has to be intelligent enough to understand why at the very least before it can be allowed to crawl.

AGIs, if we make them, will have the potential to outlive humans, but I want to imagine what could be with both of us together. Assuming greed doesn’t let it get off safety rails before anyone is ready. Scientists and engineers like to have safeguards, but corporate suits do not. At least not in technology; they like safeguards on bank accounts. So… Yes, but I entirely believe now to be a terrible time for it to happen. I would love to be proven wrong?

https://en.wikipedia.org/wiki/Straw_man

You introduced the idea of not wanting women to give birth in a conversation where the only thing brought up was women don’t have to give birth to be valid. Women not wanting children is as valid as women wanting children.

The straw man here is the anti-natalism.

I’ll back this up, and recommend people having a hard time look into Spell Labs on the steam workshop (and elsewhere) to help get further into the game. Once the game really clicks, it’s super satisfying. Even before then, the ridiculous wonder of all the things are great. It’s just as hard as it is amazing and that can be a turn off. There are other quality of life mods available in the workshop for people wanting to just enjoy the game, but the tutorial in Spell Labs is one of the biggest helps I got in unlocking progression.

Noita Together sessions were the big thing that turned the game into an obsession for me.

Hahaha. I think when they say crimes, I think they mean doing drugs and having sex. So largely nothing actually harmful unless the person passes out.

We don’t even get this memo. I thought it was still 15, 18, and 20. And I’m wholey against mandatory tipping, but always do so because I don’t want the underpaid staff to starve. I have enough friends in food service who can barely pay their rent with multiple roommates.

And minimum wage isn’t a liveable wage in most of the US now. Well, unless you split rent amongst 4 working people in a single bedroom apartment. That’s only an exaggeration in some of the US.

I only really saw that in grade school. And it was a Red Scare thing. Super culty, but so is all the McCarthy stuff.

They say it’s to prevent crime. Same as a lot of the awful things we come to expect. I’m willing to bet it doesn’t do anything noticeable with respect to crime.

There’s a health food craze in the US that stemmed out of rampant body shaming. Which might be largely because of American portion sizes. And they think that nutritional fat makes you fat. It doesn’t. Excessive calories make you fat. And even that has caveats, but it’s the best rule of thumb.

When did we start splitting milk? I know part of it is to make cream and high fat stuff while repurposing the skimmed off grass water. ::Googles:: WWII as a means of selling the byproduct of butter. Okay. Then in the 50s physicians started calling it health food despite the fact that the fat is used in your body during the digestion of many fat soluble vitamins such as A, D, E, and K, and thus skim milk is pretty close to the opposite of health food.

And the money thing is kind of rampant. It’s a big reason why things with larger price tags, like Rolex watches, are thought to more impressive by Americans than equivalent or better watches. Rolexes do have a very high quality, but then the mark up on top makes it strictly something I do not respect, and others do not share that opinion with me. Same for a lot of things.

Not necessarily the case, but if it’s affecting your life so strongly, you might want to get checked by a medical professional.

Long COVID can destroy your life. Depression can destroy your life. Iron deficiency can ruin your life. A lot of things you might just think is just being tired may actually have a cause. Especially if simple fixes like “touch grass” style clichés do nothing for you.

It’s not always the answer, but it’s good to rule out in that case.

Our cats use it to beg for treats. Very rarely do I see them on it and not meowing for attention.

It’s valid, and it sucks. If you can even do $5, it’s worth it. But the world is absolutely against you right now. A lot of older folk don’t quite get how bad it’s gotten.

However, saving a dollar today is worth more than saving two dollars ten years from now. And having an emergency fund might actually save your life.

Hopefully something happens to shake up housing. These prices are absolutely criminal.

If I hadn’t saved, I probably would be dead right now. The US doesn’t really do healthcare or mental care, and I no longer can sustain myself. Long COVID is a bitch and doctors usually ignore it.

But if you’re banking on never having an emergency, go for it. There’s a balance to hit, at least in less developed countries like the US.

1. Done. Rewritten a few times. Fleshed out a bit.
2. Learning the game engine real fast, as I haven’t used Godot before. But yes, that’s the plan. I have a minimal game loop I want to hit as the first target. And it’s not too much farther than the tutorial result I’m looking at + the main hook gameplay element of the game.
3. Bounced the idea at least off people and they sound willing to jump into this.

And of course that’s where the trail ends until it’s vetted enough to move forward.

Nice to see it kind of laid out. Still don’t know how to get past the hurtle of my brain no longer working, but maybe I can still do it… Just slowly.

There are games I want to make. I caught long COVID and barely had energy for my job. I decided now that I got laid off for having an invisible disability, I can learn how to make games while I can’t get a new one, but I’m having issues thinking long enough to learn… I’ve almost started my game and that’s where I’m stuck.

That’s LLM bull. The model already knows hangman; it’s in the training data. It can introduce variations on the data, especially in response to your stimuli, but it doesn’t reinvent that way. If you want to see how it can go astray ask it about stuff you know very well, and watch how it’s responses devolve. Better yet, gaslight it. It’s very easy to convince LLMs that they’re wrong because they’re usually trained for yes-manning and non confrontation.

Now don’t get me wrong, LLMs are wicked neat, but they don’t come up with new ideas, but they can be pushed towards new concepts, even when they don’t grasp them. They’re really good at sounding sure of themselves, and can easily get people to “learn” new “facts” from them, even when completely wrong. Always look up their sources, (which Bard (Google’s) can natively get for you in its UI) but enjoy their new ideas for the sake of inspiration. They’re neat toys, which can be used to provide natural language interfaces to expert systems. They aren’t expert systems.

But also, and more importantly, that’s not zero-shot learning. Neat little anecdote from a conversation with them though. Which model are you using?

No. AI and, what you’re more likely to be referring to, machine learning has had applications for decades. Basic work was used back into the '60s, mostly for quick things, and 1D data analysis was useful long before images (voice and stuff like biometrics). But there are many more types of AI. Bayesian networks (still in the learned category) were huge breakthroughs and still see a lot of use today. Decision trees, Markov chains, and first order logic are the most common video games AI and usually rely on expert tuning rather than learned results.

AI is a huge field that’s been around longer than you expected, and permeates a lot of tech. Image stuff is just the hot application since it’s deep learning based buff that started around 2009 with a bunch of papers that helped get actual beneficial learning in deeper models (I always thought it started roughly with Deep Boltzmann Machines, but there’s a lot of work in that era that chipped away at the problem). The real revolution was general purpose GPU programming getting to a state where these breakthroughs weren’t just theoretical.

Before that, we already used a lot of computer vision, and other techniques, learned and unlearned, for a lot of applications. Most of them would probably bore you, but there are a lot of safety critical anomaly detectors.

This actually is a symptom from the sort of “beneficial” overfit in Deep Learning. As someone whose research is in low data, long tails, and few shot learning, there’s a few things that smaller networks did better in generalization, and one thing they particularly did better (without explicit training for it) is gauging uncertainty. This uncertainty is sometimes referred to as calibration. Calibrating deep networks can yield decent probabilities that can be used to show uncertainty.

There are other tricks for this. My favorite strategies prep the network for learning new things. Large margin training and the like are a good thing to look into. Having space in the output semantic space (the layer immediately before the output or earlier for encoder decoder style networks) allows for larger regions for distinct unknown values to be separated from the known ones, which helps inherently calibrate the network.

Science is pushing the bounds of human knowledge. Science is only science if it propagates, otherwise it’s just someone’s discovery. Science has to be built upon, even if it’s disproven, that means it was documented well enough to be built upon. That’s not to say everything that’s disproven is science, because crackpot theories don’t often push the bounds of human knowledge.

I hope the brilliant students get their knowledge out there. (But that is unfortunately hard in academia. Despite us living in what should be a post knowledge scarcity society, we clearly aren’t.)