MurphyA/hacker-news huggingface dataset:
by mattnewton | 2025-05-24 22:21:35+00:00
The article kinda dances around this point, but I think the largest reason "old games never die" is simply the old games mentioned were the good ones of their generation.

Similar to the lindy effect[0] where shows that had been around a while were likely to stay around a while longer. The are the games good enough for people to host fan servers and make mods, and behind each good game there is a lot of forgotten stuff that didn't inspire anyone to preserve it.

[0] https://en.wikipedia.org/wiki/Lindy_effect#:~:text=The%20Lin...
by johnea | 2025-05-24 22:21:54+00:00
> What unsettles us about AI is not malice, but the vacuum where intention should be. When it tries to write poetry or mimic human tenderness, our collective recoil is less about revulsion and more a last stand, staking a claim on experience, contradiction, and ache as non-negotiably ours.

Vacuous BS like this sentence make me think this whole article is LLM generated text.

What unsettles me isn't some existential "ache", it isn't even the LLM tech itself (which does have _some_ very useful applications), it's the gushing, unqualified anthropomorphization by people who aren't technically qualified to judge it.

The lay populous is all gaga, while technically literate people are by and large the majority of those raising red flags.

This topic of the snippet about "life in NYC": is the perfect application for the statistical sampling and reordering of words, already written by OTHER PEOPLE.

We can take the vacuous ramblings of every would-be poet who ever moved to NYC, and reorder them into a "new" writing about some subjective topic that can't really be pinned down as correct or not. Of course it sounds "human", it was trained on preexisting human writing. duh...

Now, try to apply this to the control system for your local nuclear power plant and you definitely will want a human expert reviewing everything before you put it into production...

But does the c-suite understand this? I doubt it...
by marcodavid | 2025-05-24 22:22:22+00:00
An even crazier consequence was pointed out by J.P. Jones in 1982. He explained:

"Via Gödel numbering, the theorems of an axiomatizable theory T become in effect an recursively enumerable set. The search for proofs becomes the search for solutions of a Diophantine equation. [...]

"Theorem. For any axiomatizable theory T and any proposition P, if P has a proof in T, then P has another proof consisting of 100 additions and multiplications of integers."

See https://www.jstor.org/stable/2273588
by jiggawatts | 2025-05-24 22:22:58+00:00
The institutions that they work for have been thoroughly bribed to make that difficult. You can't get tenure unless you publish in a "reputable" paper, for example.

For IT people, the rough equivalent is why a 1 KB file costs $50/year despite containing not much more than a random number and a text field verified with a single API call.

Sure, you can have a HTTPS certificate for free! You can!

Just not through Azure Key Vault CA automation, because Let's Encrypt couldn't afford the kick-back to a middle manager in Redmond. Or more charitably, because "there's no margin on free".

Never underestimate the ability and willingness of billions of managers to insert themselves into the middle and collect rent on everybody below them.
by tombert | 2025-05-24 22:23:08+00:00
I don't think it's naive. That was in all of Google's marketing, and at the time I think that marketing was broadly true. It's impossible to know how long a good culture will last, certainly a high school kid wouldn't be expected to assume that.

They've become a typical evil BigCo now, but I don't think it's naive for not assuming that that was inevitable, just optimistic.
by DarkNova6 | 2025-05-24 22:24:03+00:00
A good and interesting article, but mimicing old games will simply not work.

While it would be admirable to have old features back, some of the largest problem these days is fragmentation.

Up until the 2000s, a new AAA game was a shared event. Fewer games were released, magazines acted as moderators for a common understanding of the market and each game tried to trump its competitors.

Games these days simply left more of an impact than a game nowadays ever could. Not to mention a younger average target demographic, which is now sticking to games of their prime.
by trod1234 | 2025-05-24 22:24:23+00:00
When vetting how useful answers are, I and most reasonably intelligent people always pay most attention to the answers that are negative because you typically learn something that helps you better able to approach the problem even if it doesn't solve the problem which you are intending to solve.

Looking over this post, there's a problem here. Where are the posts that disagree? That are negative but provide constructive criticism, the very thing that provides value.

I see 62 replies here, and this isn't a new question, and there are many caveats which easily come to my mind when learning languages, and yet no ones saying a thing. It begs some serious questions about the environment you are asking in.

OP, I would suggest that before wasting your time listening to yes-people, you need some not-so-nice answers for perspective if you really want to solve that problem in an expedient way.

That should necessarily include can AI solve that problem for you really? What are the risks of learning language improperly in a professional environment where reputation is important? What are the risks of improperly conveying meaning you didn't intend?, and so forth; you get the gist of the line of questions you should naturally come up with when seeking the truth of things.

I'm reminded of all the Japanese anime fans that pick up phrases without understanding the meaning, which is what you are learning to convey when you learn a langauge: like men using watashi (instead of boku), using improper honorifics (-kun, -sama, diajo, aniki), and other aspects that while cute in an entertainment show reflect very poorly on the person if conveyed in reality.
by kotaKat | 2025-05-24 22:24:37+00:00
> Can a lender buy access to them? How about your abusive ex, who knows and/or is a cop? The stalker who somehow knew just where that woman would be when he killed her, was that just bad luck or did he slip someone a few hundred bucks or buy the data from a data broker?

Good news! Basically... yes! https://drndata.com

Lenders are already buying that data by the boatload along with everyone else throwing cameras up.
by kevvok | 2025-05-24 22:25:48+00:00
This reminds me of how Sarah at the Connections Museum in Seattle wrote a driver to allow an Asterisk soft PBX on a Linux box to speak revertive pulse signaling to the pre-DTMF trunks on their old telephone switches

https://www.youtube.com/watch?v=35N5vKKGDy8
by gylterud | 2025-05-24 22:26:22+00:00
In Haskell, I see mtl and algebraic effects (say freer-simple) as giving you the same kind of expressiveness. The difference to me is that for mtl you need to figure out and abstract a new type class for every kind of effect and then write n^2 instances. While the freer monad construction needs only a single data type (often a GADT) and some glue function (calling send on constructors of said data type), and you are off to the races.

The algebraic reason for this is that effects are combined with sum, which is commutative up to isomorphism. While transformers are not naturally commutative, so mtl must write all the commuters as instances.

This, along with the reinterpret functions means that you can quickly spin up custom effects for your program, which do exactly what you need to express your program logic. Then all the glue coddle to make your program interact with the real world becomes a series of handlers, usually refining in several steps until you reach IO.

When I have used mtl, I end up only using the standard monad classes, and then I have to remember the semantics of each one in my domain.
by kristopolous | 2025-05-24 22:26:29+00:00
I usually like fear, shame and guilt based prompting: "You are a frightened and nervous engineer that is very weary about doing incorrect things so you tread cautiously and carefully, making sure everything is coherent and justifiable. You enjoy going over your previous work and checking it repeatedly for accuracy, especially after discovering new information. You are self-effacing and responsible and feel no shame in correcting yourself. Only after you've come up with a thorough plan ... "

I use these prompts everywhere. I get significantly better results mostly because it encourages backtracking and if I were to guess, enforces a higher confidence threshold before acting.

The expert engineering ones usually end up creating mountains of slop, refactoring things, and touching a bunch of code it has no business messing with.

I also have used lazy prompts: "You are positively allergic to rewriting anything that already exists. You have multiple mcps at your disposal to look for existing solutions and thoroughly read their documentation, bug reports, and git history. You really strongly prefer finding appropriate libraries instead of maintaining your own code"
by NeoMag | 2025-05-24 22:28:20+00:00
Hey HN,

I’m an independent creator and builder, and I just launched an open-source experiment called NeoUMG — short for Universal Modular Generation.

It’s a block-based UI that lets you visually construct intelligent outputs using modular roles:

Primary – what you want (intent)

Merge – what to include (context/data)

Blueprint – how it should feel (style/philosophy)

The idea is to move past linear prompting and instead compose AI logic like you’d build a strategy or program flow — using discrete, editable blocks. The blocks don't just feed the AI, they define the structure of thought.

Right now you can:

Select and assign modular blocks

Edit custom instructions per block

Export structured outputs

Review our white paper that positions this as an early interface for AGI-level modular cognition

It's still early, but we’re aiming to push this toward something bigger: a toolset for composable intelligence that stays human-aligned and legible.

Would love feedback, critiques, or ideas!

Live Demo: https://replit.com/@krysssativa/UniversalModularGeneration

Whitepaper: https://github.com/NeoMagCustoms/NeoUMG/blob/main/docs/NeoUM...
by isaacremuant | 2025-05-24 22:28:23+00:00
I love how you selfishly think about your agency as if there was no team involved dealing with your "snowflake creation".

When I give this advice it usually means I don't think the output is better than the existing thing and the dependency cost is better paid in the form of integration.I probably don't think you'll really maintain your creation or think about others using it when you do.

As long as we are throwing shitty incentives around.

But on a more neutral note, it's a tradeoff with many moving parts. Different choices for different scenarios.
by spamizbad | 2025-05-24 22:28:33+00:00
If you're in the AI space you need roughly the same infrastructure as any other SaaS PLUS your LLM costs. Take a look at AWS Bedrock costs [1] and you'll soon realize your costs can escalate rapidly unlike traditional SaaS infra which is easier (er, less difficult) to predict costs.

[1] https://aws.amazon.com/bedrock/pricing/
by sfpotter | 2025-05-24 22:28:53+00:00
It actually isn't that hard to come up with something better than what's in a standard library, but that requires understanding what better means for what you're working on. That's the hard part. In my experience, people who say "don't reinvent the wheel" are also the people who have the poorest understanding of requirements: what "better" means.

A standard library data strucute or algorithm has to be something for everyone, so it can't be truly great at a specific thing. If you understand your specific use case extremely well it (and are competent...) it can be very easy to run circles around the standard library.
by godelski | 2025-05-24 22:30:24+00:00
To change your mind, what would I need to demonstrate? I'm providing third party sources, I have personal experience, I can quote from the original source. What is missing that results in being unconvincing? I want to make sure, there are ways to change your opinion, right?

I really encourage you to read that wiki page.

| The quantum theory of the Lamb shift, as conceived by Bethe and established by Schwinger, is a purely mathematical theory and the only direct contribution of experiment was to show the existence of a measurable effect. The agreement with calculation is better than one part in a thousand."

I think you're missing a lot of context in that physics was highly non-mathematical in the past. Physicists called Einstein a mathematician. It isn't too hard to see when he asserted that his theories were correct and didn't need experimental confirmation.

| Hamming argues that Albert Einstein's pioneering work on special relativity was largely "scholastic" in its approach. He knew from the outset what the theory should look like (although he only knew this because of the Michelson–Morley experiment), and explored candidate theories with mathematical tools, not actual experiments. Hamming alleges that Einstein was so confident that his relativity theories were correct that the outcomes of observations designed to test them did not much interest him. If the observations were inconsistent with his theories, it would be the observations that were at fault.

Hell, go read Ian Hacking, any metaphysics, or ask ChatGPT. They will confirm what I'm saying. Even some of this is discussed in An Opinionated History of Mathematics[0], though much more focused on math. I'm more mentioning it because it is good and helps provide some of that historical context.

It is kinda crazy that a thing we created, without the specific intent of modeling the world, ended up being so great at modeling the world. That's the unreasonable effectiveness.

In fairness, to change my opinion, you would need to show me some chain of reasoning or a conversation Wigner is clearly responding to that involves religion. Because this is what I see, but around math not being physics, and is what drives my interpretation.

[0] https://intellectualmathematics.com/opinionated-history-of-m...
by Waterluvian | 2025-05-24 22:30:50+00:00
90% of the time it’s wrong to “reinvent the wheel.” If you chose this option dogmatically, you’d be making the right choice 90% of the time. But this also represents a below average outcome as a one-sided die would roll this choice right 90% of the time, too.

Your job as the decision-making engineer is to develop the expertise to be able to make the right choice more than 95% of the time.
Network Meetup in Atl?
by Thebothersuman | 2025-05-24 22:31:03+00:00
Active land stewards, farmers, problem solvers and people leaders interested in discussing overlooked data capture opportunities in agriculture.

If you are interested drop and email via the bio [Funnyfencefarm@gmail.com].

Briefly, After several years in managed care insurance industry, I've been working on a housing project for at-risk groups while developing formulas to address and identify risk care opportunities. Partnering with tech to build on the aquired data would be awesome as we seek to expand and help various risk groups and rural communities.
by Buttons840 | 2025-05-24 22:31:07+00:00
We're lacking a middle ground in copyright law that would allow people to play Mario Bros 3 on the NES for free, but doesn't give everyone the right to use the Mario IP, or to resell it en masse. (It's only possible right now because of incomplete law enforcement.)

The purpose of copyright is to encourage creation, but rent-seeking on a decades old game is not it.

Copyright and patents encourage creation and invention. Trademarks protect consumers. These laws should not do more than this.
by gmuslera | 2025-05-24 22:32:35+00:00
I would put focus in the survivorship bias too. He is looking and the survivors, and trying to figure out why they survived, and not the ones that didn't make it and could had some the same strengths, but still are not around anymore (and not even counted as "old games").

You have MAME and other console emulators with thousands of games, but how much of them are present on today's culture?
by giraffe_lady | 2025-05-24 22:33:14+00:00
Nah people with the "hacker inclination" are just as easy to buy but in other ways. There are people who will solve any interesting problem put in front of them and have a great time doing it without reflecting on why someone put it there or what it will be used for when they're done. Giving them more interesting problems, more autonomy to pursue intellectually stimulating solutions to them, is the reward you can use to keep them building your drone assassination algorithms or whatever.

In fact the overwhelming consensus on this site has long been that skillfully solving problems that are personally interesting to you is at worst morally neutral. I'll bet significant number of the people who work at for example palantir are like this. Curiosity-driven "little eichmanns."

https://en.wikipedia.org/wiki/Little_Eichmanns
by vram22 | 2025-05-24 22:33:42+00:00
J. F. C.

... And angels (how many) can dance on the head of a pin.

https://en.m.wikipedia.org/wiki/How_many_angels_can_dance_on...

(Something theologians debate about endlessly and absolutely uselessly. That is all they are good, er, bad, for.)

Yeah, right. Pontificating much? Pathetic.

How do you know he/she is "weak"? No argument provided. And the same for "incorrect".

And who the hell are you to judge them?

Let me apply some of your own judgement "ointment" on you:

>essentially always incorrect.

Your use of the word essentially in that phrase is essentially inessential. :) The meaning is equally well conveyed without that word. IOW, it's fluff, and can be done away with, fluffy kid. (wags wings at you. hi!)

Grok what I mean?

Grr.

;)
by dr_coffee | 2025-05-24 22:34:03+00:00
what about computational methods? i have always wondered how stacking many short exposures without tracking compares to deconvolution of a single long exposure. it seems that there is software able to do this by taking into account both motion blur and the PSF of the imaging system:

https://siril.readthedocs.io/en/stable/processing/deconvolut...
by boricj | 2025-05-24 22:34:12+00:00
This wheel: https://github.com/boricj/ghidra-delinker-extension

It's a Ghidra extension that can export relocatable object files from any program selection. In other words, it reverses the work done by a linker.

I originally built this as part of a video game decompilation project, having rejected the matching decompilation process used by the community at large. I still needed a way to divide and conquer the problem, which is how I got the funny idea of dividing programs. That allows a particular style of decompilation project I call Ship of Theseus: reimplementing chunks of a program one piece at a time and letting the linker stitch everything back together at every step, until you've replaced all the original binary code with reimplemented source code.

It's an exquisitely deep and complex topic, chock-full of ABI tidbits and toolchains shenanigans. There's next to no literature on this and it's antithetical to anything one might learn in CS 101. The technique itself is as powerful as it is esoteric, but I like to think that any reverse-engineer can leverage it with my tooling.

In particular, resynthesizing relocations algorithmically is one of those problems subject to the Pareto principle, where getting 80% of them right is reasonably easy but whittling down the last 20% is punishingly hard. Since I refuse to manually annotate them, I've had to relentlessly improve my analyzers until they get every last corner case right. It's by far the most challenging and exacting software engineering problem I've ever tackled, one that suffers no hacks or shortcuts.

Once I got it working, I then proceeded in the name of science to commit countless crimes against computer science with it (some of those achievements are documented on my blog). Cross-delinking in particular, that is delinking an artifact to a different platform that it originates from, is particularly mind-bending ; I've had some successes with it, but I sadly currently lack the tooling to bring this to its logical conclusion: Mad Max, but with program bits instead of car parts.

Ironically, most of my users are using it for matching decompilation projects: they delink object files from an artifact, then typically launch objdiff and try to create a source file that, when compiled, generates an object file that is equivalent to the one they ripped out of the artifact. I did not expect that to happen at all since I've built this tool to specifically not do this, but I guess when everything's a nail, people will manage to wield anything as a hammer.
by iamwil | 2025-05-24 22:35:06+00:00
It's mistaken that you don't need a new language to implement full-blown algebraic effects.

Full-blown algebraic effects are multi-shot, meaning that you can "resume the thrown exception" multiple times. The only way to do that is through delimited continuations, which isn't available as a feature in most languages, and can't be emulated by other language features--unless you reimplement the call stack in userland.

In addition, the handler can decide not to resume a raised effect at all, at which point it can exit. When it does, it's as if all the computation that it did when the handler wrapped the computation didn't happen at all. It's a way of doing backtracking. This is also possible due to delimited continuations.

Both are things that you can't do in the effects library.
by hengheng | 2025-05-24 22:35:47+00:00
Nowadays, most people who say astrophotography don't mean Deep Sky photography, hunting planets, nebula and galaxies. It's mostly the sky over a wide-angle landscape. "Astrophotography" happens at < 20mm.

Totally viable untracked. The classic 14mm prime has gone from f2.8 to f1.8 to f1.4, and sensors have become really good at high sensitivity for a 15 second exposure. Quite often, that's enough.

The hairy part is when it's not quite enough, and exposures have to be stacked. I have a crop sensor camera (canon 1.6x, so 40% area) with an f/2 lens that I like to step down further, and a good Starscape this way will take 10-40 exposures. I can stack those no problem, but it's trees on the horizon that are problematic. The ground stack and the sky stack have to clash, and a complex shaped border will always look photoshopped, because it is.

Old school Deep Sky is losing its appeal due to a) pictures being available online, meaning that you've already seen the better version of the same photo, and b) the images being sterile and without context, with no relation to the photographer's story. Milky Way in a national park says "I've been there!" in a way that a shot of the Whirlpool Galaxy just can't.
by wenc | 2025-05-24 22:37:17+00:00
Frequentist methods are unintuitive and seemingly arbitrary to a beginner (hypothesis testing, 95% confidence, p=0.05).

Bayesian methods are more intuitive, and fit how most be reason when they reason probabilistically. Unfortunately Bayesian computational methods are often less practical to use in non-trivial settings (usually involves some MCMC).

I'm a Bayesian reasoner, but happily use frequentist computation methods (max likelihood estimation) because they're just more tractable.
by tim333 | 2025-05-24 22:37:37+00:00
I'm skeptical there is much AI backlash to spill out. Obviously some people don't like it, some do. Overall it's probably a positive thing or we wouldn't be investing so much in it. Unemployment levels are fairly low by historical standards (eg https://data.worldbank.org/indicator/SL.UEM.TOTL.ZS). For each taxi driver laid off due to Waymo there are probably more people hired to make and operate the Waymos.

The Luddites were kind of unusual in the history of things. We've had all sorts of tech innovation over the last two centuries and not much has lead to riots. The luddite riots happened at time of high unemployment and inflation after the Napoleonic wars and may have been more a last straw rather than the root cause of the dissatisfaction.