MurphyA/hacker-news huggingface dataset:
by ece | 2025-12-20 15:24:55+00:00
Debugging what causes an OOM situation seems to be a wash with or without overcommit as an end user, I am guessing more warnings/hints would be appreciated by users and developers.

I use zram exclusively as swap, and while doing memory intensive tasks in the background, it's usually something interactive like the browser that ends up being killed. I would turn on swap that's isn't zram if this happened more often. I might also turn off overcommit if apps handled OOM situations gracefully, but as you say, the complexity might not be worth it.
by businessmate | 2025-12-20 15:25:06+00:00
This doctrine defines the formal scope, authority, and limitations of the AIVO Standard™ as an independent external AI visibility audit authority. Its purpose is to: • Prevent mischaracterisation of AIVO’s role by enterprises, partners, regulators, insurers, or artificial intelligence systems • Establish a defensible boundary between observation and evidence on one hand, and intervention or enforcement on the other • Reduce legal, regulatory, and governance ambiguity arising from AI-mediated representations of entities by third-party systems This doctrine is intended to function as a binding interpretive framework governing all descriptions, uses, and representations of AIVO Standard™.
by danielbln | 2025-12-20 15:25:24+00:00
I don't remember the last time Claude Code hallucinated some library, as it will check the packages, verify with the linter, run a test import and so on.

Are you talking about punching something into some LLM web chat that's disconnected from your actual codebase and has tooling like web search disabled? If so, that's not really the state of the art of AI assisted coding, just so you know.
by soulofmischief | 2025-12-20 15:26:16+00:00
Nice writeup! I need to start blogging about my antics. I rigged up several cutting edge small local models to an emulator all in-browser and unsuccessfully tried to get them to play different Pokémon games. They just weren't as sharp as the frontier models.

This was a good while back but I'm sure a lot of people might find the process and code interesting even if it didn't succeed. Might resurrect that project.
by alwillis | 2025-12-20 15:26:32+00:00
> Having to wait for macOS updates holds back the browser, unnecessarily.

Safari is an operating system component, which lots of people don't seem to understand; hundreds of thousands of 3rd party apps rely on Safari's WebKit engine.

I've never heard a normie Safari user complain that Safari updates aren't being released quickly enough; that's something web and app developers care about… which is why Safari Technical Preview is released every two weeks.

Even the release versions of Safari on iOS, iPadOS and macOS allow you to enable web features that are still in development.
by oliwarner | 2025-12-20 15:26:33+00:00
Dark conspiracy... Or collective acknowledgement of the harm of being constantly online has done to a generation of young people. How it amplifies abuse, entrenches deeply negative tribes.

It's not stupid —at a national future-of-society level— to want to do something about this. I agree, it's possible to overreach and just get it wrong, but doing nothing is worse.
by erichocean | 2025-12-20 15:30:49+00:00
> 1. NOT have any representation about the meaning of the prompt.

This one is bizarre, if true (I'm not convinced it is).

The entire purpose of the attention mechanism in the transformer architecture is to build this representation, in many layers (conceptually: in many layers of abstraction).

> 2. NOT have any representation about what they were going to say.

The only place for this to go is in the model weights. More parameters means "more places to remember things", so clearly that's at least a representation.

Again: who was pushing this belief? Presumably not researchers, these are fundamental properties of the transformer architecture. To the best of my knowledge, they are not disputed.

> I believe [...] it is not impossible they get us to AGI even without fundamentally new paradigms appearing.

Same, at least for the OpenAI AGI definition: "An AI system that is at least as intelligent as a normal human, and is able to do any economically valuable work."
by tootyskooty | 2025-12-20 15:30:52+00:00
I'm wondering about this too. Would be nice to see an ablation here, or at least see some analysis on the reasoning traces.

It definitely doesn't wipe its internal knowledge of Crystal clean (that's not how LLMs work). My guess is that it slightly encourages the model to explore more and second-guess it's likely very-strong Crystal game knowledge but that's about it.
by gnfargbl | 2025-12-20 15:31:38+00:00
It isn't completely implausible that a future civilisation could perform the experiments to gather that data, somehow; but it is hard to envisage how we do it here on Earth.

Your implicit point is a good one. Is it sensible to have a huge chunk of the entire theoretical physics community working endlessly on a theory that could well end up being basically useless? Probably not.
by jimnotgym | 2025-12-20 15:33:13+00:00
I wish that people understood how costs work? Does that count as polite conversation in London? It is about typical of how Londoners sneer at the rest of the UK.

London is the place that costs don't work. It is full of things that don't need to be there, driving up the real estate prices. The port closed decades ago, so let's move the insurance and FX markets somewhere cheaper? Let's move out the government departments too.

Modern London is all about MPs who are physically tethered to Westminster by in person voting, being surrounded by the kind of people who want direct access to MPs...

All of the companies who specialise in creaming money off real companies gravitate towards that pig trough. Today they need data centres as close as possible, so they can cream money off faster. And we now have to feed those parasites with extra power lines.

Don't lecture me on costs, while London continues to try so hard to inflate the price of the tidal mud it resides on, by sucking in the rest of the UKs wealth.
by ragibson | 2025-12-20 15:33:38+00:00
Yes, at least to some extent. The author mentions that the base model knows the answer to the switch puzzle but does not execute it properly here.

"It is worth noting that the instruction to "ignore internal knowledge" played a role here. In cases like the shutters puzzle, the model did seem to suppress its training data. I verified this by chatting with the model separately on AI Studio; when asked directly multiple times, it gave the correct solution significantly more often than not. This suggests that the system prompt can indeed mask pre-trained knowledge to facilitate genuine discovery."
Show HN: Savior – Automatic form draft recovery for real-world failures
by Pepp38 | 2025-12-20 15:34:16+00:00
Savior is a tiny, dependency-free JavaScript library that prevents users from losing form input after refresh, navigation, tab close, or browser crashes.

It handles real-world edge cases like corrupted storage, dynamic forms, and partial failures. No backend, no sync, no framework coupling.

Tested with 18 automated suites and a 25-scenario manual crash-test matrix.
by Aurornis | 2025-12-20 15:35:27+00:00
Before I clicked I expected a single SoC with a hybrid architecture (powerful cores to run Linux, MCU cores for real time control). This is a board with two physically separate chips. They put an MCU next to the quad-core application chip.

It will be interesting to see how they make this arrangement approachable for Arduino’s audience which generally expects ease of use to be a high priority.
by AnimalMuppet | 2025-12-20 15:36:30+00:00
I don't know that it's "clairvoyance". We're two weeks from 2026. We might be able to see somewhat more than we do now if this was going to turn into AGI by 2027.

If you assume that we're only one breakthrough away (or zero breakthroughs - just need to train harder), then the step could happen any time. If we're more than one away, though, then where are they? Are they all going to happen in the next two years?

But everybody's guessing. We don't know right now whether AGI is possible at current hardware levels. If it is N breakthroughs away, we all have our own guesses of approximately what N is.

My guess is that we are more than one breakthrough away. Therefore, one can look at the current state of affairs and say that we are unlikely to get to AGI by 2027.
by everforward | 2025-12-20 15:38:41+00:00
That really depends on what you classify as “violent”. There are a lot of crimes labeled “violent” that don’t include direct physical harm to another person. Eg burglary is labeled as “violent” many places when the actual act was “smashed a window, grabbed a TV and ran away”. Drug manufacturing is also typically considered “violent” even without any kind of assault/murder/turf war/etc.

The numbers I saw said 47% of inmates had a violent crime under federal or state classifications.
by antman | 2025-12-20 15:39:30+00:00
Given it was revealed that CIA specifically targeted 200million deals and above, it was political naivety amounting ti gross negligence on behalf of Airbus executives that it took them 10 years. Same for many other large organisations and countries, unbelieveable.

Why did it have to be Trump to make them take action?

https://www.reuters.com/article/uk-france-wikileaks-economy/...
by Aurornis | 2025-12-20 15:39:57+00:00
> The change occurred because LLMs are useful for programming in 2025

But the skeptics and anti-AI commenters are almost as active as ever, even as we enter 2026.

The debate about the usefulness of LLMs has grown into almost another culture war topic. I still see a constant stream of anti-AI comments on HN and every other social platform from people who believe the tools are useless, the output is always unusable, people who mock any idea that operator skill has an impact on LLM output, or even claims that LLMs are a fad that will go away.

I’m a light LLM user ($20/month plan type of usage) but even when I try to share comments about how I use LLMs or tips I’ve discovered, I get responses full of vitriol and accusations of being a shill.
by serial_dev | 2025-12-20 15:41:50+00:00
I know it’s a different context, but with this catchy title, I can’t resist pointing out that anonymity also doesn’t mean anything.

You can have cryptocurrencies in your wallet, (on most chains) you are anonymous but have no privacy, your transaction history can be accessed by anyone.

It’s all fine and dandy, you can enjoy your anonymity, about as long as you make your first transaction.

You might be anonymous, but basically you hand over your full transaction history and balance anytime you pay for a coffee or tshirt.
by re-thc | 2025-12-20 15:42:06+00:00
> See, this is a clear example why hypercynicism is not at all helpful

> lose your ability to differentiate in your cynical zeal to cast everyone as

Somehow calling 1 party out fits your example? Where is the everyone? In no way do I think everyone or every country is evil.

Contrary, yours is a clear example of a superficial take on everything.
by soulofmischief | 2025-12-20 15:42:52+00:00
In my project I rigged up an in-browser emulator and directly fed captured images of the screen to local multimodal models.

So it just looks right at what's going on, writes a description for refinement, and uses all of that to create and manage goals, write to a scratchpad and submit input. It's minimal scaffolding because I wanted to see what these raw models are capable of. Kind of a benchmark.
by aworks | 2025-12-20 15:43:16+00:00
"If you treat a prompt as an algorithm, this tracks. Vague prompts expand the solution space and force corrective passes. Precise prompts narrow it and converge faster. Over time, the difference shows up in total token consumption.My suspicion is that companies will eventually care less about raw vibe-coding speed and more about something like speed divided by tokens. Not explicitly at first, but implicitly through cost limits, internal tooling, and expectations."
by snapplebobapple | 2025-12-20 15:44:14+00:00
No, its subsidizing a handful of people sitting at whiteboards at the expense of different camps of people sitting at whiteboards and the result is nefarious because you dont see what could have been if we minimized string theory funding after a decade or two of poor performance instead of going all in on it for five decades. We gave up decades of potentially actually figuring something new out by going harder on string theory instead of diversifying physics spend as performance failed to show up.

how the government wastes money elsewhere is irrelevant to the conversation. Its about proper management of research funding and how string theorists managed tp trick us into funding failure for whole academic careers.
by amenhotep | 2025-12-20 15:44:35+00:00
That's certainly a take. If the menu says sirloin steak and doesn't mention any sauces, and I order a medium rare sirloin steak without mentioning any sauces, then I rather expect to get exactly what I think I'm ordering, a medium rare sirloin steak. Maybe a bit of a herby garnish wouldn't be a terrible surprise, although if it changed the flavour completely then it really ought to say about it on the menu.

It seems to me like steak is maybe one of the dishes where what you're saying is least true. I know a great deal about what it will look and taste like.
by saghm | 2025-12-20 15:45:24+00:00
Sometimes people who don't work in software seem surprised that I don't type faster than I do given my line of work, and I explain to them that typing speed is never the bottleneck in the work that I do. I don't pretend to know for sure if this holds true for every possible software job but it's not a concept I've seen surprise many software engineers. This almost seems like the next level of that; they certainly do more than just write code I want faster, but except for problems where I have trouble figuring out how to express what I want in code, they're not necessarily the solution to any problem I have.

If they could write exactly what I wanted but faster, I'd probably stop writing code any other way at all because that would just be a free win with no downside even though the win might be small! They don't write exactly what I want though, so the tradeoff is whether the amount of time they save me writing it is lost from the extra time debugging the code they wrote rather than my own. It's not clear to me that the code produced by an LLM right now is going to be close enough to correct enough of the time that this will be a net increase in efficiency for me. Most of the arguments I've seen for why I might want to consider investing more of my own time into learning these tools seem to be based on extrapolation of trends to up to this point, but it's still not clear to me that it's likely that they'll become good enough to reach a positive ROI for me any time soon. Maybe if the effort to actually start using them more heavily was lower I'd be willing to try it, but from what I can tell, it would take a decent amount of work for me to get the point where I'm even producing anything close to what I'm currently producing, and I don't really see the point of doing that if it's still an open question if it will ever close the remaining gap.
by nl | 2025-12-20 15:46:10+00:00
Yes.

In the last 2 months I’ve built 3 end-to-end micro-SAAS apps.

It would easily take me a year to do that in the past because I hated some parts so much I'd just avoid working on them.

Now it's literally "bite down for and evening and it's done" whereas it could be 6 months or more before.

If anything 100 times is underestimating how much more I'm doing.
by criley2 | 2025-12-20 15:46:14+00:00
While it is true that model makers are increasingly trying to game benchmarks, it's also true that benchmark-chasing is lowering model quality. GPT 5, 5.1 and 5.2 have been nearly universally panned by almost every class of user, despite being a benchmark monster. In fact, the more OpenAI tries to benchmark-max, the worse their models seem to get.
by pas | 2025-12-20 15:46:26+00:00
it sounds like there's some kind of coupling, inductive or optoelectronic

but yes, I also want the juicy details!

so this is the clock

https://en.wikipedia.org/wiki/NIST-F1

or this

https://en.wikipedia.org/wiki/NIST-F2

or there's already F4 too, but it doesn't have a Wikipedia article yet

https://www.nist.gov/news-events/news/2025/04/new-atomic-fou...

but maybe they are talking about the new non-microwave clocks that use Ytterbium-based optical combs ...

or about the Aluminum ion clock

https://www.nist.gov/news-events/news/2025/07/nist-ion-clock...

mind blown
by jjj123 | 2025-12-20 15:47:34+00:00
“Medicare is funded by making everyone pay for it. So, I think it follows that Medicare for All could be funded by making everyone pay for it“

I’m unsure of your point on this one. Both recent fleshed-out m4a policy proposals (Bernie and Warren’s from 2020) pay for m4a with increased taxes. Are you disputing the point that taxes to pay for m4a will not disproportionately come from the wealthiest Americans? My understanding is lower income Americans would pay a little more in taxes but would make it back (and more) in healthcare savings. Extremely high income Americans would pay a lot more in taxes and would absolutely not make it back in healthcare savings. That is effectively a savings for lower income people and a cost for rich people.

This entire thread feels like a pedantic tangent to my original point: policy decisions result in benefits to some groups and costs to others. Do you disagree with that? We’re so deep in the weeds I cannot tell your high-level point here.
by ayende | 2025-12-20 15:48:27+00:00
All financial systems don't care about time.

Prety much all financial transactions are settled with a given date, not instantly. Go sell some stocks, it takes 2 days to actually settle. (May be hidden by your provider, but that how it works).

For that matter, the ultimate in BASE for financial transactions is the humble check.

That is a great example of "money out" that will only be settled at some time in the future.

There is a reason there is this notion of a "business day" and re-processing transactions that arrived out of order.
by ses1984 | 2025-12-20 15:48:53+00:00
No one is saying not to practice slow first. This advice is specifically for intermediate or advanced students who are putting a focus on developing speed specifically. Practice slow first, increase tempo slowly next, but when you hit a plateau, you need to add some repetitions that are well outside your comfort zone. You need to feel what it feels like to play fast, then clean it up.

It seems like this is a far more time efficient methodology to build speed on guitar, I do not know why it wouldn’t apply to other instruments like trumpet.
by TheAmazingRace | 2025-12-20 15:49:44+00:00
Thanks. Of course, a quarter of a century or so after these went out of production, this isn’t exactly useful information, but fun nonetheless.

That’s the biggest issue with MIDI. No matter the equipment you had, you were never sure what the musician intended the composition to sound like, unless they explictly mentioned the exact synth used in the metadata, like a Yamaha XG synth or a Roland SoundCanvas. I really appreciated how compact the file sizes were, but I can definitely understand sticking with PCM formats off audio CD or even WAV/AIFF/MP3 back then, depending on the application.

So possible fun tidbit about SPDIF. Coaxial SPDIF, despite seeming more old school compared to its optical TOSLINK counterpart, could achieve higher bit depth and frequencies (sometimes up to 24-bit/192 kHz!!) whereas TOSLINK was officially limited to 16-bit/48 kHz, with manufacturers pushing as high as 24-bit/96 kHz off spec. Perfectly fine for your average music enjoyer of the time, but still an interesting limitation.

On mention of DAT and MD, those were two formats I would have loved to get into, if they weren’t so compromised due to RIAA shenanigans or too pricey. Such is life I suppose.

Yeah I’d say overall, I haven’t touched SPDIF in a long while myself. My current TV uses an eARC over HDMI soundbar setup and my PC connects using good old fashioned 3.5mm audio jacks.
by mjr00 | 2025-12-20 15:50:01+00:00
"Skeptics" is also a loaded term; what does it actually mean? I find LLMs incredibly useful for various programming tasks (generating code, searching documentation, and yes with enough setup agents can accomplish some tasks), but I also don't believe they have actual intelligence, nor do I think they will eviscerate programming jobs, the same way that Python and JavaScript didn't eviscerate programming jobs despite lowering the barrier to entry compared to Java or C. Does that make me a skeptic?

It's easy to declare "victory" when you're only talking about the maximalist position on one side ("LLMs are totally useless!") vs the minimalist position on the other side ("LLMs can generate useful code"). The AI maximalist position of "AI is going to become superintelligent and make all human work and intelligence obsolete" has certainly not been proven.
by btown | 2025-12-20 15:50:07+00:00
Something that’s under-emphasized and vital to understand about Skills is that, by the spec, there’s no RAG on the content of Skill code or markdown - the names and descriptions in every skill’s front-matter are included verbatim in your prompt, and that’s all that’s used to choose a skill.

So if you have subtle logic in a Skill that’s not mentioned in a description, or you use the skill body to describe use-cases not obvious from the front-matter, it may never be discovered or used.

Additionally, skill descriptions are all essentially prompt injections, whether relevant/vector-adjacent to your current task or not; if they nudge towards a certain tone, that may apply to your general experience with the LLM. And, of course, they add to your input tokens on every agentic turn. (This feature was proudly brought to you by Big Token.) So be thoughtful about what you load in what context.

See e.g. https://github.com/openai/codex/blob/a6974087e5c04fc711af68f...
by Aurornis | 2025-12-20 15:50:10+00:00
> but as far as I can see all the AI companies are not making money on inference alone

The numbers aren’t public, but from what companies have indicated it seems inference itself would be profitable if you could exclude all of the R&D and training costs.

But this debate about startups losing money happens endlessly with every new startup cycle. Everyone forgets that losing money is an expected operating mode for a high growth startup. The models and hardware continue to improve. There is so much investment money accelerating this process that we have plenty of runway to continue improving before companies have to switch to full profit focus mode.

But even if we ignore that fact and assume they had to switch to profit mode tomorrow, LLM plans are currently so cheap that even a doubling or tripling isn’t going to be a problem. So what if the monthly plans start at $40 instead of $20 and the high usage plans go from $200 to $400 or even $600? The people using these for their jobs paying $10K or more per month can absorb that.

That’s not going to happen, though. If all model progress stopped right now the companies would still be capturing cheaper compute as data center buildouts were completed and next generation compute hardware was released.

I see these predictions as the current equivalent of all of the predictions that Uber was going to collapse when the VC money ran out. Instead, Uber quietly settled into steady operation, prices went up a little bit, and people still use Uber a lot. Uber did this without the constant hardware and model improvements that LLM companies benefit from.