theropost

Yeah, what bugs me about stuff like that is like they spend all this time and then they output several or minimal real testing to prove the theory It's like you're building your model to And just because it takes a long time to compute and do the testing, you'd rather publish your article and then try to get credit on something that hasn't really been proven. Look, prove your results. Study it. Ruggedize it. Make sure it works. Then, show us.

Pirate Game - trading/quests/voyages - inspired by KOEI games

https://ship-voyage-4zn.pages.dev/

(apologies for any bugs/glitches - still needs polish)

I remember playing Pirates on my 8086 in the 1980, mono-chrome screen, and I was amazed a a kid. Sid Meier's games were always a step above, and so immersive feeling for their day. I started a project from that too (one of many I suppose). I also was inspired by the KOEI games on SNES - Uncharted Waters.

It needs polish, content and more work but the kids like it.

https://ship-voyage-4zn.pages.dev/

I'm a bit sad.. I was using it quite often for making quick videos for Teams instead of using Meme's and Gifs.. I just made my own :(

It always kinda amazes me how people panic about gov data use but barely blink at the private sector doing the exact same thing… except way less transparently.

Like yeah, sure, governments collecting data deserves scrutiny. 100%. But at least in most democracies there are audits, oversight bodies, privacy commissioners, courts, access to information laws, etc. There are actual mechanisms where someone can ask “why are you doing this?” and force an answer.

Meanwhile we hand over our location, browsing habits, shopping patterns, sleep schedule, and probably our favorite pizza topping to dozens of private companies every day. Those companies can aggregate it, sell it, profile you, feed it into ad markets, train models with it, or ship it across borders… and most of the time nobody outside the company even knows it’s happening.

So yeah, data collection in general is worth debating. But the irony is wild when people lose their minds over the one place that at least has some governance and accountability, while the entire private ad-tech ecosystem is basically “trust us bro” with a 40-page terms of service nobody reads.

Fair enough, I didn't dig too deep though here's what I have come up with - I'm sure there are many factors, but it is quite interesting here:

Historically, Democratic and Republican administrations have followed distinct fiscal and economic patterns: Democrats typically oversee deficit reduction and falling unemployment, often achieved by maintaining or increasing the tax burden. Conversely, Republicans typically oversee deficit growth and rising unemployment, largely driven by decreased tax burdens through legislative cuts. Statistically, since 1945, real GDP has grown faster under Democrats (4.3% vs. 2.5%), while modern Democratic presidents (Clinton, Obama, Biden) have all reduced the deficits they inherited, whereas every modern Republican (Reagan through Trump) left office with a larger deficit than when they started

So you'd think tax cuts would create more jobs, less unemployment but it has not. It seems like the opposite, I'm sure there is much more to it.

I mean, part of this is just math. If a government spends more, it’s literally injecting money into the economy, so of course you get more jobs and growth in the short term. That spending is the jobs. If you tighten spending to cut waste or rebalance the books, growth slows and jobs shrink, but that’s kind of the tradeoff when you’re trying to fix long-term issues.

Over the last few decades, neither party has really cared about deficits anyway. Everyone’s been spending, just at different speeds. The real question isn’t “who creates more jobs,” it’s whether the spending is efficient, sustainable, and actually creates long-term value. Eventually the bills come due, interest costs rise, and priorities shift from growth to just keeping the lights on.

So yeah, Democrats tend to show stronger job numbers, but spending more will almost always do that. Whether it’s good spending is a separate debate. Budget discipline isn’t partisan, it’s just basic economics.

I’ve definitely hit that same pattern in the early iterations, but for me it hasn’t really been a blocker. I’ve found the iteration loop itself isn’t that bad as long as you treat it like normal software work. I still test, review, and check what it actually did each time, but that’s expected anyway. What’s surprised me is how quickly things can scale once the overall architecture is thought through. I’ve built out working pieces in a couple of weeks using Claude Code, and a lot of that time was just deciding on the architecture up front and then letting it help fill in the details. It’s not hands-off, but used deliberately, it’s been quite effective https://robos.rnsu.net

https://robos.rnsu.net

Mostly just experimenting with things, as a hobby and a way to delve deeper into new tech - probably lots of glitches.

I think there is a real issue here, but I do not think it is as simple as calling it theft in the same way as copying books. The bigger problem is incentives. We built a system where writing docs, tutorials, and open technical content paid off indirectly through traffic, subscriptions, or services. LLMs get a lot of value from that work, but they also break the loop that used to send value back to the people and companies who created it.

The Tailwind CSS situation is a good example. They built something genuinely useful, adoption exploded, and in the past that would have meant more traffic, more visibility, and more revenue. Now the usage still explodes, but the traffic disappears because people get answers directly from LLMs. The value is clearly there, but the money never reaches the source. That is less a moral problem and more an economic one.

Ideas like GPL-style licensing point at the right tension, but they are hard to apply after the fact. These models were built during a massive spending phase, financed by huge amounts of capital and debt, and they are not even profitable yet. Figuring out royalties on top of that, while the infrastructure is already in place and rolling out at scale, is extremely hard.

That is why this feels like a much bigger governance problem. We have a system that clearly creates value, but no longer distributes it in a sustainable way. I am not sure our policies or institutions are ready to catch up to that reality yet.

I think this kind of critique often leans too hard on “security through obscurity” as a cheap punchline, without acknowledging that real systems are layered, pragmatic, and operated by humans with varying skill levels. An open firmware repository, by itself, is not a failure. In many cases it is the opposite: transparency that allows scrutiny, reproducibility, and faster remediation. The real risk is not that attackers can see firmware, but that defenders assume secrecy is doing work that proper controls should be doing anyway.

What worries me more is security through herd mentality, where everyone copies the same patterns, tooling, and assumptions. When one breaks, they all break. Some obscurity, used deliberately, can raise the bar against casual incompetence and lazy attacks, which, frankly, account for far more incidents than sophisticated adversaries. We should absolutely design systems that are easy to operate safely, but there is a difference between “simple to use” and “safe to run critical infrastructure.” Not every button should be green, and not every role should be interchangeable. If an approach only works when no one understands it, that is bad security. But if it fails because operators cannot grasp basic layered defenses, that is a staffing and governance problem, not a philosophy one.

Just came back online here

Interesting point about touchscreens..I think it highlights a bigger issue with “safety” features sometimes backfiring. For example, that relentless beeping when the passenger seat detects weight but it’s just a backpack or groceries. I wonder how many drivers have been more distracted trying to silence the alarm than they would’ve been just ignoring the bag in the first place. Feels like we’ve traded one kind of risk for another. Do they really research this, or is it more of a gimmmic

But what if everything scales but what if no matter how complicated how obscure how mundane how niche what if everything I mean everything scales

Just tossing in my two cents - half the $25K cars people are asking for do exist, or did, but we’re basically banning them from the country with tariffs. It’s like we’re saying, “nah, we don’t really want cheap cars.”

Look at something like the Dolphin from China - it’s going for $8K–$9K USD over there. Ship a whole fleet of them and you’re still well under $25K. And we’re not talking junkers either - these are electric, decent build quality, ~300km range. Like... what exactly are we protecting here?

Feels like we’re pricing affordability out of the market on purpose.

Honestly, I’ve been thinking about this whole AGI timeline talk—like, people saying we’re going to hit some major point by 2027 where AI just changes everything. And to me, it feels less like a purely tech-driven prediction and more like something being pushed. Like there’s an agenda behind it, probably coming from certain elites or people in power, especially in the West, who see the current system and think it needs a serious reset.

What’s really happening, in my view, is a forced economic shift. We’re heading into a kind of engineered recession—huge layoffs, lots of instability—where millions of service and admin-type jobs are going to disappear. Not because the tech is ready in a full AGI sense, but because those roles are the easiest to replace with automation and AI agents. They’re not core to the economy, and a lot of them are wrapped in red tape anyway.

So in the next couple years, I think we’ll see AI being used to clear out that mental bureaucracy—forms, paperwork, pointless approvals, inefficient systems. AI isn’t replacing deep creativity or physical labor yet, but it is filling in the cracks and acting like a smart band-aid. It’ll seem useful and “intelligent,” but it’s really just a transition tool.

And once that’s done, the next step is workforce reallocation—pushing people into real-world industries where hands-on labor still matters. Building, manufacturing, infrastructure, things that can’t be automated yet. It’s like the short-term goal is to use AI to wipe out all the mindless middle-layers of the system, and the longer-term vision is full automation—including robotics and real-world systems—maybe 10 or 20 years out.

But right now? This all looks like a top-down move to shift the population out of the “mind” industries and into something else. It’s not just AI progressing—it’s a strategic reset, wrapped in the language of innovation.

I wish my AI would tell me when I'm going in the wrong direction, instead of just placating my stupid request over and over until I realize.. even though it probably could have suggested a smarter direction, but instead just told me "Great idea! "

150 lines? I find can quickly scale to around 1500 lines, and then start more precision on the classes, and functions I am looking to modify

Sounds interesting, I'll give it a look. I'm unfortunately limited to CSV, XML, or XLS from the source system, then am transforming it and loading it into another DB.

I need this, just finished 300GB of CSV extracts, and manipulating, data integrity checks, and so on take longer than they should.

Million dollar "dinners' seem to help.

https://www.tomshardware.com/tech-industry/artificial-intell...

There are consultants who bring real value. They’re experts at the top of their fields, offering skills not available in-house. They help upskill staff, deliver results, and provide knowledge transfer that has long-term benefits. Those people deserve to be paid well for what they bring.

But too often, consultants are brought in to do work that existing staff could already handle or to maintain systems that should’ve been fixed years ago. It’s not always outright corruption, but it props up managers who rely on outside help to get by. And many of these consultants aren’t adding value — they’re just billing for work that could be automated or easily solved.

One example involved consultants paid to babysit an outdated system. It was generating massive reports, and instead of fixing the root issue, someone had to manually delete files every few hours. Thousands per week were spent when a simple script or hardware upgrade could have fixed it. It’s wasteful and completely unnecessary.

This isn’t rare. It’s everywhere. And while it’s not always illegal, it’s driven by self-interest, favoritism, and comfort. That’s where the real waste is, and that’s where the cuts should happen.

Consulting used to be about value. It was a profession grounded in skill, purpose, and a drive to contribute. Now, it’s often about milking the system. People leave the public service knowing they can return as consultants and get paid two or three times as much, just because of who they know.

We’ve replaced public service and merit with opportunism. Instead of building better systems and serving the country, we’re incentivizing people to exploit it. And the worst part is, it’s become normal. But it shouldn’t be. This is structural corruption — accepted, embedded, and everywhere.

My take on all this is that everyone seems focused on the U.S. dollar’s dominance, the empire, trade deficits, and exchange rates. And sure, there’s some validity to that, but the real issue, or really the real goal, is getting people back to work.

You might not see it, and maybe I don’t fully see it either, but as office workers, bureaucrats, and technologists staring at screens all day, we’ve lost sight of the fact that America no longer produces like it used to. Yes, there are still people out there working with their hands, feeding the country, and running small industries. But broadly speaking, the U.S. relies heavily on other countries for complex manufacturing — for actual building. Shipbuilding is just one obvious example. A lot of critical industries have withered to the point where they can't even meet domestic demand, let alone compete globally. Meanwhile, other countries are pushing forward in tech, producing better, more efficient, more productive products — and pulling ahead.

It’s not happening all at once. It’s a slow decay. Generational knowledge industrial skills, trades, machinists are all fading. And when those go, the backbone of resilience and self-sufficiency starts to collapse. A nation that can’t produce can’t stand. Export power becomes a dream.

And I think part of the issue is that we’ve become lazy. People don’t want to work anymore — they want things handed to them. Entitlements, bonuses, luxury homes, multiple cars, the works. But someone has to build all that. Someone has to maintain the food supply. Someone has to assemble the vehicles. Someone has to keep production alive. Yes, technology can help fill gaps, and we’ve done amazing things — and still do — but America’s edge in tech? That’s slipping away. China has surpassed the U.S. in key areas of advanced technologies, auto manufacturing, aerospace, and absolutely obliterating in shipbuilding. U.S. industry? Ashes in many places.

So what’s the answer? Unfortunately, hardship. Nobody likes to say it, but raising prices and tightening the belt forces people to make hard choices. And when that happens, the jobs that matter won’t be office jobs or desk jobs — they’ll be builders, machinists, welders, factory workers. Producers. And those jobs will start commanding the wages. People who’ve been unemployed or living on subsidies will be pushed — or pulled — back into that kind of work. Slowly, painfully, maybe, but steadily. And maybe, just maybe, we’ll rebuild that base. Maybe industry will return. Maybe factories and production will grow again.

That’s the end goal here; even if we don’t like how it’s being done. Even if it’s painful. Even if it doesn’t work the way it’s intended. Because maybe we’re not as strong as we think we are. Maybe we fail. It’s happened before — look at the USSR collapse. It was a fake economy built on fake production and apathy. They endured 20 years of hardship, and they’re still trying to catch up.

So yeah, that’s where I think we’re headed. Is Trump the guy to do it? He’s doing it. Someone had to. Is it the right way? I don’t know. Is it going to work? No clue. Will we succeed? Who knows. Or maybe we just keep punting the problem further down the road; business as usual — until it breaks completely.

But either way, the path forward is either a slow crumble followed by a rebuild, or a brutal reset with the hope of rebuilding something stronger on the other side.

That’s just my two cents.

It kinda just depends on the agenda, one source says it’s nothing, another says it’s a trillion, and that huge gap usually means someone’s trying to push something, like tougher laws or justify some policy shift. Half the time it feels like the facts don’t even matter, just the story they wanna sell.

It's hard to tell I can imagine some motivated individuals could utilize all sorts of packaging systems and embed them in third-party applications and so on, and extract pertinent information using this type of surveillance, and then sell this data to data brokers which would sell it to the large ad networks. I mean there's lots of ways to transcribe even most of the whisper models can run all the way down to 150 megabyte file not to mention the quantization versions of these models. I have something that I run on my computer for my server not throughout my house that does real Time transcription and whatnot but I use it for my own purposes, so you know someone who makes money off advertising or even selling insights about people, would certainly find ways to do this. I mean it's simply not regulated is it?

https://huggingface.co/spaces/jilangdi/whisper-web

this.

I regularly use the request data button on ChatGPT, then parse the JSON and output HTML for each conversation, and a DB to search for the file(s) when needed.

I've been running this and a quantized version of the QwQ model and comparing the responses - so far, QwQ is working better, though that could change as I use them more and compare the outputs

I completely agree. I’ve had the privilege of working with a very small team of engineers—a team with diverse life experiences and unique areas of expertise but a shared work ethic: the willingness to try. We always said that most of our time was spent failing, and that’s what made the moments of success so rewarding. When we finally succeeded, it wasn’t just about the victory; it was the culmination of relentless effort that allowed us to push forward, improve our product, and refine our ideas.

Our approach was unique. We engaged directly with the people who did the work, learning from their insights and challenges, and built tools specifically for them. It wasn’t an Agile team or a Waterfall approach, or any other rigid corporate framework. It was an ad hoc team that came together organically to solve problems—and solved them faster than large corporations, consultants, or armies of workers ever could.

With just four people, we scaled applications, built automation systems, and tackled complex problems that delivered multi-million-dollar savings across the board. The process was simple: no micromanagement, no unnecessary oversight. Everyone contributed based on what made sense, and we all collaborated freely to solve problems as they arose, moving seamlessly from one challenge to the next. It was innovation through cohesion—a kind of synergy that can’t be forced or replicated through standard processes. It’s the magic of the right people, in the right place, at the right time.

Over the years, the tools we developed have grown into critical applications used by professional organizations, with over 3,000 users relying on them daily to make their work hundreds of percent faster. Yet, when these tools are handed over to large organizations for "modernization" or "corporatization," they often end up spending exorbitant amounts of money, adding no meaningful features, and making the tools less effective. Teams of 30 people fail to replicate what our small team accomplished. It’s a strange and frustrating reality.

I’ve tried to find ways to replicate this success, but I think it comes down to that intangible element—a “ragtag team” dynamic where the right people come together with a shared drive and passion. It’s rare, and perhaps it doesn’t exist as it once did. Maybe it’s out there, but we need to find ways to enable and foster it.

Copyright laws, in many ways, feel outdated and unnecessarily rigid. They often appear to disproportionately favor large corporations without providing equivalent value to society. For example, brands like Disney have leveraged long-running copyrights to generate billions, or even tens of billions, of dollars through enforcement over extended periods. This approach feels excessive and unsustainable.

The reliance on media saturation and marketing creates a perception that certain works are inherently more valuable than others, despite new creative works constantly being developed. While I agree that companies should have the right to profit from their investments, such as a $500 million movie, there should be reasonable limits. Once they recoup their costs, including a reasonable profit multiplier, the copyright could be considered fulfilled and should expire.

Holding onto copyrights indefinitely or for excessively long periods serves primarily to sustain a system that benefits lawyers and enforcement agencies, rather than providing meaningful value to society. For instance, enforcing a copyright from the 1940s for a multinational corporation that already generates billions makes little sense.

There should be a balanced framework. If I invest significant time and effort—say 100 hours—into creating a work, I should be entitled to earn a reasonable return, perhaps 10 times the effort I put in. However, after that point, the copyright should no longer apply. Current laws have spiraled out of control, failing to strike a balance between protecting creators and fostering innovation. Reform is long overdue.