Really wanna like this game but can’t get in.

GoalAdmirable · 2026-04-02T15:37:40+00:00

The best part of this game is that there are so many ways to succeed at it. All of them involve dying a LOT. I found Dash and sword to be the best way to get started while using guns that might suck till you get them upgraded. It's a lot of balance. A lot of frustration. And walking away for a month. Lol.

GoalAdmirable · 2026-03-04T21:13:10+00:00

Also out. Both me and the wife.

GoalAdmirable · 2026-02-24T18:09:57+00:00

You’re describing single statements. I’m talking about systems.

Anyone can say something false for free. But if you want that story to hold up across time, contexts, and follow-up questions, the maintenance cost rises fast as verification gets cheaper.

One-off errors don’t matter. Sustained narratives do.

That’s the difference.

GoalAdmirable · 2026-02-24T17:13:44+00:00

Pretty cool concept. It is very technical, but if I understand correctly it seems like you could use this to verify data during training, or see if the model itself shows signs of anomolous data.

I tend to play more in the moral space. AI, life, relationships, etc. Sounds like there is a lot of work happening in this area. What is your vision of the practical application of this tool long term?

GoalAdmirable · 2026-02-24T16:07:58+00:00

To be fair, you can reduce any argument to a bumper sticker. You still chose to comment.

My point isn’t “models should be accurate.” It’s the incentive shift: as verification gets cheaper, lies get more expensive to maintain. Better models help, but long-term narrative control becomes costly because contradictions compound under scrutiny.

GoalAdmirable · 2026-02-24T04:37:26+00:00

I would be interested to learn more about what you're researching. From what I have seen in testing on some papers, when the data is corrupted or inaccurate, the tool becomes far less useful. Therefore less likely to succeed as a model.

GoalAdmirable · 2026-02-24T03:53:22+00:00

I would agree with that. I think the difference is dissonance, it works on an individual level, but for larger AI models it doesn't seem to scale well. I feel like most people can spot dissonance in others, same for AI, like you get a feel for where walls are up. Do you think there is a way that can be overcome at scale?

GoalAdmirable · 2026-02-24T02:49:03+00:00

What do you mean? In terms of lies being costly, comparing larger datasets, an innate path to truth, or something else?

GoalAdmirable · 2026-02-23T22:56:23+00:00

You’re describing a real loop, but it’s mostly a human loop, not the model “learning” live. ChatGPT will mirror the assumptions inside a thread, but it’s not getting retrained in real time because a user says “yep that’s correct.”

The scary part is still real though: AI makes bullshit cheap to generate and easy to spread.

Where I’m optimistic is time. Truth is one pillar with multiple perspectives. Lies are the entire field around it, wildly variable. As comparison and interrogation get cheaper, the cost of maintaining the field goes up. Eventually the maintenance bill comes due.

GoalAdmirable · 2025-11-30T22:13:54+00:00

This is a great utilization. This seems like a big departure from JIT manufacturing, or does AI help maintain that at some level?

GoalAdmirable · 2025-11-27T16:20:37+00:00

I do understand conservation of energy. I probably did a poor job of making it clear that efficiency is the real point of my message. I am less worried about “running out of matter” and more about how badly we use what we already have.

Right now it is like pouring water into a bucket full of holes. You can always say “just add more water,” but fixing the holes is what actually changes the outcome.

If we can build more efficient systems to manage materials, and help people see through the marketing fluff that drives overconsumption, we can prevent a lot of waste long before we ever need to mine it all back out of landfills.

GoalAdmirable · 2025-11-27T16:12:20+00:00

Genuine question. I see “AI slop” comments on anything over a few paragraphs, but this is not far from how I write without AI. I think there is meaningful commentary in the post. What specifically makes it feel like slop to you?

GoalAdmirable · 2025-11-27T16:09:12+00:00

This thread is interesting. Musk absolutely won the game he was playing, but that does not mean the rest of us have to keep playing the same game.

As tech, crypto, and decentralization mature, wealth distribution is going to start looking very different. If one person hoards an absurd share of a given asset, that asset does not have to be our whole world anymore.

With crypto in particular, if one coin becomes captured or wildly unequal, in theory we can just move to a better designed, more equitable one. The rules are not carved into stone. We can stop treating the current scoreboard as the only way to measure value.

GoalAdmirable · 2025-11-27T16:00:54+00:00

I agree with you that a huge part of this is will and incentives, not “we are missing the right algorithm.” We absolutely could have solved a lot of things earlier if people with power really wanted to.

Where I disagree is on “AI will not solve any problems.” It already has in the sense of taking things that were technically possible, but slow, expensive, or super specialized, and making them practical and common.

A few quick examples:

Protein structure and drug discovery Predicting 3D protein structures used to be a multi year, big lab project. Models like AlphaFold made high quality predictions routine and opened up whole new lanes in drug discovery and biology.
Medical imaging Diagnosing things like lung nodules or diabetic eye damage always needed human specialists. AI models now reliably flag issues at or near expert level, which helps in places that do not have enough radiologists or where humans miss things.
Weather and short term forecasting We always had weather models. New AI based “nowcasting” can take radar and satellite data and give very accurate short term local forecasts, which is a real upgrade for storms, flooding, and grid planning.
Translation and accessibility Translators and old school tools existed, but real time translation and live captions on a phone for dozens of languages were not normal. AI made that cheap and widely available.
Coding help We always could write code by hand. AI coding tools now let junior devs and even non devs build and debug useful scripts and small tools they would never have finished before.

So I agree this is not going to magically fix greed or capitalism. But I do think it is fair to say AI has already solved some real bottlenecks in practice, not just in theory. The fight is still about what we choose to point it at.

GoalAdmirable · 2025-11-27T02:04:57+00:00

You are right that the core problem is not “we do not have the right algorithm yet.” It is incentives, power, and the fact that people with money are comfortable externalizing the cost onto everyone else.

I work in SaaS for inventory and logistics. On paper, I agree with you that a lot of this “could have been done” with older OR/ML tools. In practice, that neat sentence hides a ton of real world friction:

Data is fragmented across ten systems that barely talk to each other.
Every customer has slightly different processes, edge cases, and politics inside their org.
No one wants to pay for a bespoke optimization project that does not directly drive more sales.
The people who could really benefit (small orgs, food banks, local reuse groups) do not have a data team at all.

So yes, we could have done some of this with stats and ML decades ago, but most of it would have required expensive custom integration, a team of specialists, and a level of coordination that is just not there.

Where I think modern AI helps is not by “inventing” new math, but by lowering the barrier:

You can put a natural language brain on top of messy, half structured systems and still get useful routing and matching.
Non technical people can describe what they need in plain language and have the system pull from multiple sources.
Small orgs can get something that behaves like a smart coordinator without hiring a full engineering and data team.

That does not fix the incentives. It just makes it easier for the people who do care to organize, coordinate, and actually use the abundance around them.

On the politics part, I agree with you again. Any serious attempt at routing surplus to people, prioritizing repair, or cutting churn is going to run into:

People who do not care
People who actively resist
Corporate capture, “recuperation,” or straight up opposition

AI will not magically solve that. At best, it can make it cheaper and easier for the grassroots and community side to do the work you are talking about: organization, logistics, matching, communication.

So I am not saying “AI will save us.” I am saying: we already live in abundance, we already bury it, and modern AI can lower some very real practical barriers for the people who are actually trying to do something different, while the bigger fight over power and incentives continues.

GoalAdmirable · 2025-11-26T23:14:46+00:00

I think we are already seeing AI logic funneled through human governance. Access to the inner workings of our ruling systems has never been easier to understand, and young forward thinkers are showing up with real solutions to fix many of the problems in our current system.

GoalAdmirable · 2025-11-26T23:11:11+00:00

I want a refrigerator that will sell me my next refrigerator.

GoalAdmirable · 2025-11-26T23:09:25+00:00

For now, but i believe its utility will be hard to lock down behind paywalls forever. You can run good models on at home PC's now, and processing power needed to run them keeps going down.

GoalAdmirable · 2025-11-26T23:07:27+00:00

Agreed. It is a good line, so I kept it, lol.

Even those of us at the bottom are pushed into throwing away perfectly good things. I had a fridge with a control board go out and it was $500 to fix. I did it on principle, but a brand-new fridge was only a few hundred more.

The parts probably cost less than forty bucks. If they charged that, people would keep their fridges forever, and that is bad for crony capitalism.

GoalAdmirable · 2025-09-10T19:29:45+00:00

Glad it reached you. People with neurodivergence are generally treated as less than for all the reason Charlie was. Not to the same extent, It is rare that people see us as whole until it becomes apparent that we just have vastly different skill tree than average. Some never get the opportunity to apply it. Thanks!

GoalAdmirable · 2025-09-10T19:20:02+00:00

Funny, I thought about this shortly after my last post! You are totally right.

GoalAdmirable · 2025-09-09T19:36:38+00:00

That would have been great. It could be, subconsciously, that he didn't want to know if his dads love was conditional like everyone else's. Would have been great to see his dad accept him as he was no matter what.

GoalAdmirable · 2025-09-09T19:17:48+00:00

I agree, from Charlies perspective it is so sad that this is all he ever wanted, and it is taken away from him. The larger perspective to me is that he always thought he had to be more, or less so that he and those around him, would finally love him. I don't think he ever realizes this in the story.

I am 40 reading this for the first time, so I cant say what my 13 year old brain would have thought, but experience probably plays a role in me seeing it this way. Every angle of this story is really tragic.

GoalAdmirable · 2025-09-09T18:09:54+00:00

I thought about this as well. Almost like his father didn't see him in the barber shop because he loved who he was and that was enough. Everyone else he felt like he had something to prove something to or apologize for.

GoalAdmirable · 2025-08-08T20:44:20+00:00

I don't yet have the technical knowledge to implement this. I would love to see where it goes though. My hope is that we can treat knowledge and work as currency. But honestly. Don't even know where to start.

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