MurphyA/hacker-news huggingface dataset:
by Mooshux | 2026-03-10 21:22:57+00:00
MCP integration is the obvious next question. The language-level guardrails solve execution safety but the credential problem is still orthogonal. Even with Aegis, the agent needs API keys to call external services, and those keys still have to come from somewhere with some scope. Would be interesting to see how Aegis handles the "what does this agent actually have permission to do at the API layer" question vs just the "what code can it run" question.
by mrguyorama | 2026-03-10 21:22:59+00:00
No one worth listening to makes that argument.

Torpedo boats didn't make Battleships obsolete. Aircraft carriers did. Because they could do the same role but better.

AntiTank rifles didn't make tanks obsolete. Neither did anti-tank mines. Nor anti-tank rocket launchers, nor anti-tank artillery, nor really freaking good anti-tank missiles, nor anti-tank helicopters etc etc. Turns out, putting a box of steel around soldiers is pretty much always better. IFVs are even less survivable than a tank in all cases and they have only become more important and prominent because what capability they provide is what matters.

Artillery and Air power did not make the army obsolete. Air power did not make Artillery obsolete though the USA wanted that reality.

Submarines didn't make any boat obsolete.

SAM systems did not make planes obsolete. Hell, America decided the solution to missiles aimed at your planes was fly planes at the missile launcher! And it works because war is stupid.

"Cheap drones" only work against things that haven't yet adapted to cheap drones in the exact same way that Navy had to adapt to anti-ship missiles. With EW, those "cheap" drones get less cheap. With any sort of advancement in protection, those drones get less cheap. War is about achieving physical control, and you can't really do that with cheap drones. There's always back and forth in weapons systems. We still use bayonets in the right circumstances!

Cheap drones cannot establish air superiority, and certainly not air supremacy. Actual air combat drones are far more expensive, involved, and in development than quadcopters.

The primary power drones bring is ISR, making the entire battlefield utterly transparent, including at nighttime. That's insane, and really really bad for any of us who might be forced to fight in the future, as lethality to the average soldier is likely to go up.
Tell HN: Beware of Mac Studio Scams on eBay
by laweijfmvo | 2026-03-10 21:23:09+00:00
The tell-tale signs seem obvious in retrospect, but even the best of us can be fooled sometimes:

1. The lowest price, by quite a bit
2. An eBay "classified" ad, which doesn't support purchasing through eBay (why does eBay even offer this?)
3. Some sort of rug pull at the last minute, to make the payment non-refundable.

I'll give a detailed story: I found a Mac Studio M3 Ultra for ~$500 less than the closest "Buy it Now" machine. Emailed the seller, which requires filling out a basic form, and they responded that they would send a PayPal invoice once I confirmed my PayPal and shipping address. Now, if you do a minimum amount of research on these "classified" ads, this is generally recommended as the safest option to complete the transaction, as PayPal will allow you to confirm the product before releasing the funds to the seller. However, I noticed that the seller replied/quoted my message and the form was translated to German, although the product was listed in Chicago. Hint #1. I confirmed my PayPal info anyway, and they responded that due to a "PayPal issue", I'd have to send them a "gift" payment first. Hint #2, and at this point I reported the account. eBay emailed me a couple hours later warning me that the account had been hijacked and was being used for scams.

Going back to the search results, there are several of these Macs, all listed below market value, all as "classified" ads, and probably all either scam accounts or account take-overs.

So, be aware and use common sense.
by keeda | 2026-03-10 21:23:25+00:00
Something I have not seen discussed is the highly dynamic semantics of the annoying Gen Alpha variant of BrainRot. It has this fascinating aspect of slang with meanings that can shift in combination with other terms: Skibidi, Sigma, 6-7, Ohio -- Not only do these have flexible semantics in the first place, their meaning can dynamically change in the context of other such terms... if any meaning is intended at all.

As an example, "sigma" could be used as "He's so sigma!" (positive connotations) or "What the sigma!" (negative connotations) or "Sigma skibidi Ohio!" (what the sigma?!?)

And then there are suffixes like "maxxing" which seem straightforward ("bench-maxxing") but can be used in creative combinations, like somebody used "second-story-maxxing" to mean "going upstairs." Not quite Shakespeare, but funny.

I am no linguist but this seems unprecedented. At least ChatGPT thinks there is precedence, but only gave examples of nonsense terms in literature (like "The Jabberwocky") and counter-cultural slang or art (like Dadaism) or meanings that shifted over time.

However this idea of semi-defined words and memes that get combinatorially and dynamically redefined -- or even undefined -- seems different. I think this is more than just The Algorithm, it's more a spillover of a subculture into the mainstream. It's like slang that has intentionally internalized trolling and arbitrary word-coining as part of normal discourse.
by silentsvn | 2026-03-10 21:23:25+00:00
One thing I've been wrestling with building persistent agents is memory quality. Most frameworks treat memory as a vector store — everything goes in, nothing gets resolved. Over time the agent is recalling contradictory facts with equal confidence.

The architecture we landed on: ingest goes through a certainty scoring layer before storage. Contradictions get flagged rather than silently stacked. Memories that get recalled frequently get promoted; stale ones fade.

It's early but the difference in agent coherence over long sessions is noticeable. Happy to share more if anyone's going down this path.
by pash | 2026-03-10 21:23:39+00:00
> Even for billion-parameter theories, a small amount of vectors might dominate the behaviour.

We kinda-sorta already know this is true. The lottery-ticket hypothesis [0] says that every large network contains a randomly initialized small network that performs as well as the overall network, and over the past eight years or so researchers have indeed managed to find small networks inside large networks of many different architectures that demonstrate this phenomenon.

Nobody talks much about the lottery-ticket hypothesis these days because it isn’t practically useful at the moment. (With the pruning algorithms and hardware we have, pruning is more costly than just training a big network.) But the basic idea does suggest that there may be hope for interpretability, at least in the odd application here or there.

That is, the lottery-ticket hypothesis suggests that the training process is a search through a large parameter space for a small network that already (by random initialization) exhibit the overall desired network behavior; updating parameters during the training process is mostly about turning off the irrelevant parts of the network.

For some applications, one would think that the small sub-network hiding in there somewhere might be small enough to be interpretable. I won’t be surprised if some day not too far into the future scientists investigating neural networks start to identify good interpretable models of phenomena of intermediate complexity (those phenomena that are too complex to be amenable to classic scientific techniques, but simple enough that neural networks trained to exhibit the phenomena yield unusually small active sub-networks).

0. https://en.wikipedia.org/wiki/Lottery_ticket_hypothesis
by cptskippy | 2026-03-10 21:24:08+00:00
Core evolved from the Banis (Centrino) CPU core which was based on P3, not P4. Banias used the front-side bus from P4 but not the cores.

Banias was hyper optimized for power, the mantra was to get done quickly and go to sleep to save power. Somewhere along the line someone said "hey what happens if we don't go to sleep?" and Core was born.
by ashton314 | 2026-03-10 21:24:26+00:00
The core of this little essay seems to be this:

Instead of "I understand the causal mechanism and can predict what happens if I change X," you get something more like "I have a sufficiently rich model that I can simulate what happens if I change X, with probabilistic confidence." The answers are distributions, not deterministic outputs. That's a different kind of knowing.

At the beginning this sounded like, "hard problems are complex, machine learning can help us manage complexity, therefore we will be able to solve hard problems with machine learning", which betrays a shallowness of understanding. I think what this essay argues here is a little deeper than that trite tech-bro hype meme.

But I disagree with this conclusion: I don't know that we can begin to build these models to begin with or that our new LLM/transformer-powered tools can help solve these problems. If simulation were the answer to everything, why will new ML tools make a significant difference in ways that existing simulation tools do not?

Stuff like AlphaFold is amazing—I'm not saying that better medical results won't come about from ML—but I feel like there's some substance missing and that even this level of excitement that the author expresses here needs more and better backing.
by joshstrange | 2026-03-10 21:24:38+00:00
> Claude Code is very likely to soon offer 1 million tokens as well

You can do it today if you are willing to pay (API or on top of your subscription) [0]

> The 1M context window is currently in beta. Features, pricing, and availability may change.

> Extended context is available for:

> API and pay-as-you-go users: full access to 1M context

> Pro, Max, Teams, and Enterprise subscribers: available with extra usage enabled

> Selecting a 1M model does not immediately change billing. Your session uses standard rates until it exceeds 200K tokens of context. Beyond 200K tokens, requests are charged at long-context pricing with dedicated rate limits. For subscribers, tokens beyond 200K are billed as extra usage rather than through the subscription.

[0] https://code.claude.com/docs/en/model-config#extended-contex...
by mr-wendel | 2026-03-10 21:24:51+00:00
> I'm going to play with getting Gemini to look at the photo of the receipt and categorize and add up the categories for me.

FWIW, I have a pet project for a family recipe book. I normalize all recipes to a steps/instructions/ingredients JSON object. A webapp lets me snap photos of my old recipes and AI reliably yields perfectly structured objects back. The only thing I've had to fix is odd punctuation. For production, use is low, so `gemini-2.5-flash` works great and the low rate limits are fine. For development the `gemma-3-27b-it` model has MUCH higher limits and still does suprisingly well.

I'd bet you can pull this off and be very happy with the result.
by tylerjaywood | 2026-03-10 21:25:03+00:00
I have this in open beta on Android right now so you're welcome to give it a shot and let me know :)

One difference is cost. I know that mine is lower cost, and is a one time unlock -- no subscription. So there's that. I'm also therefore positioned a little bit more towards the casual user, I prioritize speed of completion which means I need high confidence in a good signal quickly and don't hesitate to cancel mid-flow.

I think one thing alternatives offer is the ability to run for longer -- like a 10 minute check for instance. There are marginal gains in precision for every additional second, but they seem to diminish pretty quickly past 30 secs or so. But that's one difference I'm aware of.
by hrmtst93837 | 2026-03-10 21:25:11+00:00
One thing compilers still struggle with is exploiting weird microarchitectural quirks or timing behaviors that aren't obvious from the ISA spec, especially with memory, cache and pipeline tuning. If a new RISC-V core doesn't expose the same prefetching tricks or has odd branch prediction you won't get parity just by porting the same backend. If you want peak numbers sometimes you do still need to tune libraries or even sprinkle in a bit of inline asm despite all the "let the compiler handle it" dogma.
by traderj0e | 2026-03-10 21:25:17+00:00
Isn't there a way for Uber to do this in a way that doesn't give preferential treatment to female drivers, assuming they have higher demand? One of:

1. Force the same market rate for female-only vs regular mode. This means a shortage of female drivers and higher wait times for users in that mode, but anyone who really wants it can use it.

2. Charge more for female-only mode, but pay the driver the same rate either way.
by HarHarVeryFunny | 2026-03-10 21:25:18+00:00
Forget 2023 - the advances in coding ability in just last 2-months are amazing. But, they are still not AGI, and it is almost certainly going to take more than just a new training regime such as RL to get there. Demis Hassabis estimates we need another 2-3 "transformer-level" discoveries to get there.
by daxfohl | 2026-03-10 21:26:00+00:00
Sounds like we've just gotten into lazy mode where we believe that whatever it spits out is good enough. Or rather, we want to believe it, and convince ourselves that some simple guardrail we put up will make it true, because God forbid we have to use our own brain again.

What if instead, the goal of using agents was to increase quality while retaining velocity, rather than the current goal of increasing velocity while (trying to) retain quality? How can we make that world come to be? Because TBH that's the only agentic-oriented future that seems unlikely to end in disaster.
by STKFLT | 2026-03-10 21:26:18+00:00
I'd guess that the issue is running the `%install` and `%check` stages of the .spec file. The Python library rpy (to pull a random example from Marcin's PRs) runs rpy's pytest test suite and had to be modified to avoid running vector tests on RISC-V.

Obviously a solvable problem to split build and test but perhaps the time savings aren't worth the complexity.

https://src.fedoraproject.org/rpms/rpy/pull-request/4#reques...
by deadlyllama | 2026-03-10 21:26:32+00:00
Sharing filesystems is hard when you make users do it in advance.

I was thinking of the server end of an ffmpeg-over-ip system bringing up a FUSE filesystem backed by something similar to your VFS-served-by-the-client. Combine that either with argument rewriting, or chrooting into the FUSE filesystem.

As another commenter said, where's plan 9 when you need it? If you go the FUSE route there are existing 9P implementations for both server and FUSE client you can use.
by demosito666 | 2026-03-10 21:26:43+00:00
> Even if everyone has been 10x’ed, the math still strongly favours not making mistakes in the first place

The math depends on importance of the software. A mistake in a typical CRUD enterprise app with 100 users has zero impact on anything. You will fix it when you have time, the important thing is that the app was delivered in a week a year ago and was solving some problem ever since. It has already made enormous profit if you compare it with today’s (yesterday’s ?) manual development that would take half a year and cost millions.

A mistake in a nuclear reactor control code would be a total different thing. Whatever time savings you made on coding are irrelevant if it allowed for a critical bug to slip through.

Between the two extremes you thus have a whole spectrum of tasks that either benefit or lose from applying coding with LLMs. And there are also more axes than this low to high failure cost, which also affect the math. For example, even non-important but large app will likely soon degrade into unmanageable state if developed with too little human intervention and you will be forced to start from scratch loosing a lot of time.
by danso | 2026-03-10 21:26:49+00:00
The beginning of the thread is here:
https://bsky.app/profile/randyhermanlaw.com/post/3mgq5nrqa2s...

Context from the OP:

> Today at 4:00 I will go over to Raleigh and sit in on a show-cause hearing. This will be my first time attempting to live-post a hearing in person. The case is Fivehouse v. DOD and the question is whether the DOJ attorney fabricated quotes in a brief.
by fidotron | 2026-03-10 21:26:53+00:00
> RISC-V doesn't have the pitfalls of Sparc (register windows, branch delay slots),

You're saying ISA design does have implementation performance implications then? ;)

> There's no one that expects it'll be hard to optimize for

[Raises hand]

> There are at least 2 designs that have taped out in small runs and have high end performance.

Are these public?

Edit: I should add, I'm well aware of the cultural mismatch between HN and the semi industry, and have been caught in it more than a few times, but I also know the semi industry well enough to not trust anything they say. (Everything from well meaning but optimistic through to outright malicious depending on the company).
by yukapero | 2026-03-10 21:27:36+00:00
Interesting idea
Im checking it from Japan with my system language set to Japanese, but the product descriptions are still showing up in English. The platform UI itself seems to be localized, so this might be a bug.

As for the token costs, have you looked at Gemini 3.1 Flash-Lite (preview)? The quality is solid and it's dirt cheap: $0.25 per 1M input and $1.50 per 1M output. Unless you have massive traffic, it would probably only cost a few dollars a month. Seems like a very reasonable overhead for the value it adds
by kqr | 2026-03-10 21:27:36+00:00
> If you're not using Emacs, it would be crazy to fire up Magit just to do a git commit or rebase.

What makes you say that?

> what do you mean "save is C-x C-s?" what does that even mean?

Magit never asks you to C-x C-s save anything. Magit has its own independent set of discoverable keybinds.
by tylerjaywood | 2026-03-10 21:27:41+00:00
This is the way. I got one as well to validate my results. Cost is the difference. If you're okay with close-enough and saving $145, I think the apps fit in a nice place.

I will say, this flow is not the primary concept for the app. My intended design, and what it's been for 2+ years, is a tool that provides structured flows for inputting the time on your device and comparing it to atomic time (provided in my app). If you stagger these measurements over 6 or so hours for a day or two, you get a very precise reading and I still recommend this approach as being better.
by ethin | 2026-03-10 21:28:33+00:00
This may be an unpopular opinion, but I fully support the no-AI stance. AI-generated code belongs nowhere in an operating system or it's low level/kernel components. Especially considering the shear amount of power the kernel has over the machine. The last thing you want is an AI-generated bug crashing systems because it flipped a bit that is reserved or silently corrupting memory (or worse) because it ran in kernel mode (or similar privileges) and therefore the system didn't prevent it from doing what it was going to do. An OS (of any kind or architecture) and computer firmware is the last place I would ever want AI-generated code.
by WarOnPrivacy | 2026-03-10 21:28:54+00:00
Is archive.xx working for everyone? I haven't been able to satisfy the captcha for a few days. I've tried switching extensions, browsers, computers and locations. Same results for .ph, .md, .eu, .si, .is, .fo, .today.

(and 1min later this link worked for me https://archive.is/Mw5bh but only this link.)
by kmeisthax | 2026-03-10 21:29:00+00:00
In ARM, TrustZone[0] is a higher level of privilege than hypervisors (EL3 vs. EL2); it's morally equivalent to x86 System Management Mode. That means it categorically can steal your data. There's nothing EL2 code can do to prevent inspection or manipulation from a malicious EL3.

A less awful design would have been to keep the security code at EL2 and have CPU hardware that can isolate two EL2s from one another[1]. This is ultimately what ARM wound up doing with S-EL2, but you still need to have EL3 code to define the boundary between the two. At best the SoC vendor can design a (readable/auditable!) boot ROM that occupies EL3 and enforces a boundary between secure and non-secure EL2s.

[0] Or, at least, TrustZone's secure monitor. TZ can of course run secure code at lower privilege levels, but that doesn't stop a TZ compromise from becoming a full system compromise.

[1] If you're wondering, this is morally equivalent to Apple's guarded exception levels.
by hkonte | 2026-03-10 21:29:04+00:00
Defining prompt regions and measuring attention per region is the right level of abstraction. The interesting question is whether named semantic blocks (role, constraints, output format, examples) actually get attended to differently, or whether position in the token stream is what dominates.

If blocks do carry distinct attention signatures, that would be strong evidence for structuring prompts that way rather than writing them as flat text. I built flompt (github.com/Nyrok/flompt) around the block decomposition idea, and empirical attention maps like yours are exactly the kind of signal that would validate or kill the thesis.
Markdown Files Won't Make You an Engineer
by _pdp_ | 2026-03-10 21:29:30+00:00
Recent advancements in AI has convinced 99% of the population that engineering is just writing markdown files. Well, it's not and it never will be.

Deep knowledge of systems, engineering, and programming will be in demand for as long as technology exists. Relying on AI without that foundation is like trying to advance material science without understanding chemistry, or pioneering new techniques in biology without grasping the underlying mechanisms. The tools change, the need for real understanding doesn't.

Remember Deep Thought, the greatest computer ever built that spent 7.5 million years computing the Answer to the Ultimate Question of Life, the Universe, and Everything? The answer was 42. Perfectly correct, utterly useless because nobody understood the question they were asking. That's what happens when you hand everything to a machine without understanding the problem yourself. AI can give you correct answers all day long, but if you don't understand what you're building, you'll end up just like the people of Magrathea, staring at 42 and wondering what to do with it.

And if you need a role model, Neo wasn't chosen because he could dodge bullets. He was a developer first. He understood the system before he could bend it. There's a reason The One was a programmer, not a prompt engineer.
by galangalalgol | 2026-03-10 21:29:31+00:00
Montesquieu, Wittfogel, and Sachs are the old ones. Modern writers acknowledge geography isn't destiny, but it would definitely be fighting uphill for Russia to maintain democracy. Mobile middle class seems to be the real driver of democracy, and coastal trade is what created that in most modern democracies. Seems like maybe technology could change that. But big regions make mobility harder. If you have to move half a world away to reach different laws the pressure to retain you is less. Where a doctor in Hungary can pack up and take a train to find a government more to their liking. The shrinking of the middle class drives authoritarianism fairly reliably according to these sources. Sometimes the older ones call it the merchant class.
by konaraddi | 2026-03-10 21:29:51+00:00
I booted chromeos flex on a >12 year old laptop earlier this year and had a good experience with it. I wrote a bit about it here https://konaraddi.com/writing/2026-01-01-chromeos-flex/ (tl;dr tried to use fedora at first but no luck with WiFi out of the box then I used chromeos flex and it worked out of the box)