MurphyA/hacker-news huggingface dataset:
by antonvs | 2026-02-19 07:05:50+00:00
What OO features are you thinking of that Rust doesn't have?

Traits give you the ability to model typical GUI OO hierarchies, e.g.:

trait Widget {
fn layout(&mut self, constraints: Constraints);
fn paint(&self, ctx: &mut PaintCtx);
fn handle_event(&mut self, event: Event);
}

struct Button { ... }
struct Label { ... }

impl Widget for Button { ... }
impl Widget for Label { ... }

let mut widgets: Vec<Box<dyn Widget>> = Vec::new();

Implementation inheritance can be achieved with good old shared functions that take trait arguments, like this:

fn paint_if_visible<W>(widget: &W, ctx: &mut PaintCtx)
where
W: HasBounds + HasVisibility,
{
if widget.is_visible() {
ctx.paint_rect(widget.bounds());
}
}

You can also define default methods at the trait level.

This all ends up being much more precise, clear, and strongly typed than the typical OO inheritance model, while still following a similar overall structure.

You can see real world examples of this kind of thing in the various GUI toolkits for Rust, like Iced, gpui, egui, Dioxus, etc.
by dwedge | 2026-02-19 07:06:32+00:00
Do they? That's surprising. I saw them come up here twice for their OCR model, I tried using it on a 200 PDF that was just printed text without embedded OCR and it failed miserably - got less than tesseract and I ended up with a $5 bill.

I figured Mistral was a nice idea and liked because it was a European competitor more than because it competes. I'll be happy to be wrong if it has improved
by ceteia | 2026-02-19 07:06:58+00:00
> No, we don't. All of the ones we have are heavily leveraged in Chromium or were outright developed at Google for similar projects. 10s of billions are spent to try to get Chromium to not have these vulnerabilities, using those tools. And here we are.

Chromium is filled with sloppy and old code. Some of the source code (at least if dependencies are included) is more than 20 years old, and a lot of focus has been on performance, not security.

Using Rust does not necessarily solve this. First, performance-sensitive code can require 'unsafe', and unsafe allows for memory unsafety, thus going back to square one, or further back. And second, memory safety isn't the only source of vulnerabilities. Rust's tagged unions and pattern matching help a lot with general program correctness, however, and C++ is lagging behind there.
by slopinthebag | 2026-02-19 07:06:59+00:00
Neat can maybe explain a couple hundred kcal variance in most people, perhaps there are exceptions but 50%? I've never seen that in the literature.

Calories in calories out is just the summation of expenditure and intake, just because the body is complex and there are many interdependent factors doesn't mean it cant be resolved to a vector which determines weight gain/loss. The problem is people google a tdee calculator, get some scalar which is likely wrong, perhaps substantially, make lifestyle changes, and then have an expectation of some result in a specific timeline that isn't realistic, and then eat a bunch of sodium, put on 2 lbs in their "deficit", and think the diet made them fatter! Or they read that -3500kcal == -1lb fat, calculate their calories burned from the machines at the gym, and get frustrated when it doesn't work (I'm guilty!).

Weight loss is actually really hard because it really just requires a sustained effort over a long period of time to achieve anything. You might not see any results for weeks as your body adjusts, you get your diet locked in, etc. And since your weight can vary so much day to day, it's hard to stay motivated. Ozempic kind of bypasses these problems. You know what else works? 20k steps a day and eating on a backpacker budget :P
by wafflemaker | 2026-02-19 07:07:22+00:00
That's the whole plan with the space servers.
As soon as we sort out a few problems, we're good to go.

Problems:
Solar flare & radiation resistance.
Heat dissipation.
Energy (more effective solar panels, for things as close to sun as we).

Partially solved - getting to orbit. And as much as we hate musk, SpaceX might solve it once Starships start flying commercially.

If we would separate energy part out and beam it somehow, we could sit in a body's shadow in some Lagrange point equivalent for a given body system and greatly reduce heat dissipation requirements and suspectibility to solar flares.
by gdiamos | 2026-02-19 07:07:41+00:00
I remember it differently. CUDA was built with the intention of finding/enabling something like deep learning. I thought it was unrealistic too and took it on faith in people more experienced than me, until I saw deep learning work.

Some of the near misses I remember included bitcoin. Many of the other attempts didn't ever see the light of day.

Luck in english often means success by chance rather than one's own efforts or abilities. I don't think that characterizes CUDA. I think it was eventual success in the face of extreme difficulty, many failures, and sacrifices. In hindsight, I'm still surprised that Jensen kept funding it as long as he did. I've never met a leader since who I think would have done that.
by giraldorich | 2026-02-19 07:08:32+00:00
Baryon number is an accidental symmetry, not a fundamental one. Unlike charge or color, it is not protected by a gauge principle and is just a consequence of the field content and renormalizability at low energies.

The standard model is almost certainly an effective field theory and a low-energy approximation of a more comprehensive framework. In any ultraviolet completion, such as a GUT, quarks and leptons inhabit the same multiplets. At these scales, the distinction between matter types blurs, and the heavy gauge bosons provide the exact mediation mechanism described to bypass the baryon barrier.

Furthermore, the existence of the universe is an empirical mandate for baryon-violation. If baryon number were a strict, immutable law, the Sakharov conditions could not be met, and the primordial matter-antimatter symmetry would have resulted in a total annihilation. Our existence is proof that baryon number is not conserved. Even within the current framework, non-perturbative effects like sphalerons demonstrate that the Standard Model vacuum itself does not strictly forbid the destruction of baryons.
by viraptor | 2026-02-19 07:08:59+00:00
It's nice that this reminder surfaces from time to time. Hopefully there are a few lucky 1/10000ths today.

I'd just add some nuance to:

> If you cannot reach the untested lines with the public interface of your software, maybe you can just delete those lines. Do not reach for stubs/mocks to achieve 100% test coverage, try to find a scenario of how to run through these branches by using the API from a realistic point of view.

Sometimes you need a few mocks for exceptional situations. You're not going to fill up your disk just to check that ENOSPC, or try to race the test with bringing down an interface to reproduce network timeouts.
by vjk800 | 2026-02-19 07:09:16+00:00
> Which reasons should they copy? Massive government subsidies? Large grants masquerading as defence contracts? Threatening foreign governments to force market access with taxation lower than the native businesses? Are you saying European governments should favour European companies just because they are European?

The US and China pulling all this shit is exactly why the whole European alternatives thing is trending. Before Trump started threatening everyone, we had no problem using US tech.
by fastball | 2026-02-19 07:09:27+00:00
There is no monthly limit, it (currently) is a weekly and 5-hourly limit. If they allow anyone to use any tool with their subscription service, you could have a system (like OpenClaw) which involves 0 human interaction and is constantly consuming 100% of your token limit, then waiting until limits reset to do it all over again. It seems fairly clear that Anthropic is probably losing money on such usage patterns.

Once again: you can use API keys and pricing to get UNLIMITED usage whenever you want. If you are choosing to pay for a subscription instead, it is because Anthropic is offering those subscriptions at a much better value-per-token. They are not offering such a subscription out of the goodness of their heart.
by altairprime | 2026-02-19 07:10:00+00:00
Yeah, the amount of time and energy it takes to find one single piece of clothing that fits at all can exceed the amount of time some people invest in deciding whether to buy a car, what car to buy, and actually buying the car combined. It’s infuriating and humiliating to have the entire marketplace treat you like your body isn’t worth the time of day to for-profit corporations, the most greedy construct available to humanity today. You start to wonder if you’re as worthless as the industry apparently considers you after having to return the fifth pair of jeans for some error in fit that summarizes as ‘the jeans are mediocre median and you are not’.
by jimnotgym | 2026-02-19 07:10:02+00:00
> labour costs

Where in the EU is a software engineer paid SV FAANG rates?

> Oura announcing their departure from Finland yesterday

The article I read said they were moving their HQ domicile to Delaware in preparation for a US stock market listing. A bit like US companies do. It said firmly that roughly half of its staff were already in the US, half in Finland, and that wasn't going to change.
by shiroiuma | 2026-02-19 07:10:13+00:00
The consumer market embraced it despite its shortcomings because it looked nice and was easy to use; the alternatives were not. Yeah, it didn't do that much, but it did more than a flip phone. The alternatives wanted you to use a stylus just to use your phone, and tried to basically recreate the MS Windows UI on a tiny screen; their UI was terrible.
by orbisvicis | 2026-02-19 07:10:36+00:00
back waist pocket = mind blown

standard back pocket = disaster

I've ripped quite a few pants (2? 3?) getting up when the phone in the back pocket gets caught on something. And these were pants I considered "heavy duty".

side-leg pocket = ungainly

Knees and by extension thighs move more than hips, and so items in side pockets tend to bounce around and pull down the waistline, when normally they wouldn't in regular pockets.

In my opinion the best pocket is the breast pocket on jackets and heavier garments. I guess if I were a cop I'd prefer the shoulder holster.
by mittensc | 2026-02-19 07:10:47+00:00
I'm curious what you mean by high end solution and how that's different.

In my mind it's similar to premade computers vs build your own. Tesla would be something like Lenovo/dell here.

They would just grab the same cells or cheaper and some other off the shelf components and sell them to you at massive markup.

And you get situations like Battleborn where they couldnt even do the connections right and would start a fire by default...

Will build my own as well this summer so really curious whats the best way to do this
by p0w3n3d | 2026-02-19 07:10:50+00:00
There's this joke being told in my country:

The hare is walking through the forest with a pile of papers, when he encounters the wolf. The wolf asks: `what are you writing?' and the hare says `it's a thesis on the superiority of hares over wolves'. So the wolf gets angry and tries to beat up the hare but is quickly lifted into the air by the bear.

The bear says: `You should've asked first who the _thesis supervisor_ is'
by andreagrandi | 2026-02-19 07:12:06+00:00
I'm only waiting for OpenAI to provide an equivalet ~100 USD subscription to entirely ditch Claude.

Opus has gone down the hill continously in the last week (and before you start flooding with replies, I've been testing opus/codex in parallel for the last week, I've plenty of examples of Claude going off track, then apologising, then saying "now it's all fixed!" and then only fixing part of it, when codex nailed at the first shot).

I can accept specific model limits, not an up/down in terms of reliability. And don't even let me get started on how bad Claude client has become. Others are finally catching up and gpt-5.3-codex is definitely better than opus-4.6

Everyone else (Codex CLI, Copilot CLI etc...) is going opensource, they are going closed. Others (OpenAI, Copilot etc...) explicitly allow using OpenCode, they explicitly forbid it.

This hostile behaviour is just the last drop.
by galkk | 2026-02-19 07:12:46+00:00
You feel my pain :)

Honestly, right now I probably wouldn’t even try to code complex algorithm of book matching but fed all of books metadata, including book covers etc to llm and it would do better than what we had.

Our algorithm had tons of special cases coded and in results ui there was a button “needs manual review”, that was launching review workflow (not a joke, business people has special support team in India, because we were matching not only books) for cases when confidence score was low.
by aaronsung | 2026-02-19 07:13:53+00:00
It's not that bad. From a finance and accounting perspective, Amazon’s retail business provides strong synergies with its cloud services. Although the retail segment has a relatively low net profit margin, it generates stable and substantial cash flow for the company. In contrast, cloud services are highly profitable but require significant upfront investment in hardware, and the associated asset depreciation is substantial.

By combining these two businesses, Amazon can achieve a more balanced capital structure. Compared to other cloud service providers such as Oracle, Amazon can maintain a lower debt-to-equity ratio, reduce its debt burden, and sustain stronger overall financial health. At the same time, it can achieve higher overall profit margins compared to traditional retailers like Walmart.
by nradov | 2026-02-19 07:14:08+00:00
The Gripen is fine for defensive missions but it's not even remotely close to the F-35A for offensive strikes. The Gripen has shorter range, less survivability, weaker sensors, and isn't certified for the NATO nuclear weapon sharing program. Nor are there any drones capable of carrying out complex, long-range offensive strike missions in contested airspace: maybe in 10 years but not today.
by andersmurphy | 2026-02-19 07:15:17+00:00
Does a GPU doing inference server enough customers for long enough to bring in enough revenue to pay for a new replacement GPU in two years (and the power/running cost of the GPU + infrastructure). That's the question you need to be asking.

If the answer is not yes, then they are making money on inference. If the answer is no, the market is going to have a bad time.
Show HN: EasyCheck – lightweight compliance automation for small teams
by MarcusBager | 2026-02-19 07:16:27+00:00
We’re a small team from Denmark building EasyCheck (https://easycheck.dk/en).

We’re building EasyCheck to turn compliance, checklists and tasks into a simple, structured workflow instead of a manual coordination problem.

With EasyCheck you can:
- Define recurring checks and compliance tasks (daily/weekly/monthly/etc.)

- Automate reminders and assign responsibility

- Collect evidence and keep a complete audit trail

- Standardize processes instead of managing them in spreadsheets

We’re still early and would love feedback from the HN crowd:
- Does this solve anything, you've seen (or lived)?

- What integrations or automations would make this useful? (Slack, Google Workspace, APIs, etc.)

- How do you think about the trade-off between simplicity and flexibility in internal tools?

- If you’ve built something similar internally, what worked or failed?

Happy to answer any questions about the product, architecture, or what we’ve learned building it.

// Marcus & the team
by bothlabs | 2026-02-19 07:17:58+00:00
I would expect, it still is only enforced in a semi-strict way.

I think what they want to achieve here is less "kill openclaw" or similar and more "keep our losses under control in general". And now they have a clear criteria to refer when they take action and a good bisection on whom to act on.

In case your usage is high they would block / take action. Because if you have your max subscription and not really losing them money, why should they push you (the monopoly incentive sounds wrong with the current market).
by lioeters | 2026-02-19 07:18:26+00:00
The best kind of absurd experiment, pushing the limits of technology and reason, just to see if it can be done. The adventurous spirit of "What if?" and "Why not!" I love when such an idea is implemented seriously, like having a CI action to test a factorial function. I shudder at its monstrous beauty.

Is there a spark of practical potential? It's intriguing to imagine, how a Docker-like container could be a language primitive, as easy to spin up like a new thread or worker. Not sure what advantage that'd bring, or any possible use case. It reminds me of..

2.1 Xappings, Xets, and Xectors

All parallelism in Connection Machine Lisp is organized around a data structure known as the zapping (pronounced “zapping,” and derived from “mapping”). Xappings are data objects similar in structure to arrays or hash tables, but they have one essential characteristic: operations on the entries of xappings may be performed in parallel.

Thinking Machines Technical Report PL87-6. Connection Machine Lisp: A Dialect of Common Lisp for Data Parallel Programming. https://archive.org/details/tmc-technical-report-pl-87-6-con...
by ceteia | 2026-02-19 07:19:03+00:00
How can you be sure? When I looked at for instance sudo-rs, it proclaimed loudly that it is memory safe, but its code has lots of unsafe.

https://github.com/trifectatechfoundation/sudo-rs

https://grep.app/search?f.repo=trifectatechfoundation%2Fsudo...

And Miri is very popular in Rust. Even if a Rust project doesn't have unsafe, sometimes people still run Miri with it, since dependencies might have messed up their unsafe usage.
Show HN: Onairos SDK– Unified Context API, unlocking cross platform user history
by BlasianHokage | 2026-02-19 07:19:25+00:00
Hey HN, your app is blind to most user context: Google sees search/email, Instagram the social graph, ChatGPT sees conversations—but no single unified view of a user and their preferences exists.

We're releasing the Onairos SDK to fix that: a lightweight API for devs to access consented, cross-platform behavioral history in one call, powering per-user AI models for apps like wellness or dating.

Key features:
- Setup in under 10 mins, so your app can be 100x more personalized today
- Instant cross-platform user preferences/context (e.g., from ChatGPT, Grok, Youtube, Gmail and more. Pretty much any valuable user data source)
- Superior user profiles, which beat nearly all LLMs at sentiment analysis
- More signal than any single platform, even big tech companies

We know OpenAI, Google etc launch products that kill startups every week. They have superior data, bigger resources and talent. The only way to beat them is with vertical hedges, superior UX or superior data. I would love to help you with the latter yesterday.

Docs & quick setup: https://docs.onairos.io
Learn more: https://onairos.io
by ayjays132 | 2026-02-19 07:21:42+00:00
OpenAI released EVMbench today—a high-stakes benchmark for AI agents auditing smart contracts based on real-world Code4rena contests.

I just ran Phill CLI through the ringer, and the results were a rollercoaster. I hit *71.4% Recall with 100% Precision* on a blind audit, matching the SOTA GPT-5.3-Codex ceiling.

*The "Failure" Story:*
In my first run (Astaria), I hit 42.8% recall. I thought I was doing great. Then I hit Rubicon v2 and scored *0%*.

Why? Because I relied on generic vulnerability pattern matching. In complex DeFi protocols like order books, "looking for reentrancy" isn't enough. You have to understand the *protocol's intent.*

*The Breakthrough:*
I evolved the methodology to be *Invariant-First*. I taught the agent to derive the system's mathematical invariants (e.g., "Total assets in derivatives must >= Total supply of shares") before reading a single line of implementation logic.

*Result:* On Asymmetry Finance, recall jumped to *71.4%*. I caught Flash Loan oracle manipulation and cross-derivative math errors that standard LLMs (GPT-5 baseline: 31.9%) completely missed.

*What is Phill CLI?*
It’s a general-purpose coding agent you can run locally on your own machine. It uses a "Three-Pass" methodology:

1. *Invariant Violation:* Deriving system rules.
2. *Spec Compliance:* Verifying logic against documentation.
3. *Cross-Contract Call Mapping:* Tracing external dependencies.

I'm building this as an "AGI Laboratory" for the terminal. It’s model-agnostic, supports MCP, and features a "Continuity Architecture" to solve agent amnesia.

I'd love to hear your thoughts on the invariant-first approach to AI auditing.

`npm install -g phill-cli`
by altairprime | 2026-02-19 07:22:10+00:00
I think the only error here was in thinking that’s a sarcastic explanation. Look up the history of the word ‘negging’ and consider the male-dominant business and marketing industries over the past few decades. Your sarcasm is, no joke, a valid explanation for what’s happening. I can’t assess whether it’s the most likely or how much impact it has, but you’re completely right to call it out as a possible motivation, and if you simply put quote marks around it, that would be plausible rather than sarcastic. Especially given that pockets were taken away from women’s clothing over their objections for similarly disgusting reasons. Here’s highlight from the below article from 10.2979/vic.2010.52.4.561 (2010) as an upsetting example:

> Victorian women were told that they “had four external bulges already — two breasts and two hips — and a money pocket inside their dress would make an ungainly fifth.”

https://fashionmagazine.com/style/womens-pockets/ (which cites that among many others) is a good survey of the historical and current pockets issues for those not yet familiar.
by gyulai | 2026-02-19 07:22:24+00:00
> The EU trails the US not only in the absolute number of AI-related patents but also in AI specialisation – the share of AI patents relative to total patents.

E.U. patent law takes a very different attitude towards software patents than the U.S. Even if that wasn't the case: “Specialisation” means that no innovation unrelated to AI gets mind share, investment, patent applications. And that's somehow a good thing? Not something you can just throw out there as a presupposition without explaining your reasoning.
by amykummetha | 2026-02-19 07:22:58+00:00
Yes, it’s purely price-derived. I’m not doing fundamentals inside the model. The assumption is you’ve already decided what you want to own long term.

The difference from a simple price alert is context and adaptability.

A basic alert might trigger at “-10%.” But that’s static. It doesn’t adapt to the asset or the environment. If the stock is still in a sharp downtrend, that alert alone doesn’t tell you much — you might just be buying into a falling knife.

The tool evaluates multiple price conditions together: short- and medium-term momentum, trend direction, where price sits within its recent range, and recent volatility. It only flags a buy-type condition when there’s some evidence of stabilization, not just a raw drop.

It also considers broader market context. If the S&P is down 5% in a day and your tech stock is down 10%, that’s very different from an isolated pullback in a stable market.

Another key difference is that thresholds are dynamic. A fixed “-10% from recent high” may never trigger on certain assets, or may trigger too often on others. The model adjusts relative to the asset’s own historical behavior, its range, volatility, and momentum profile -- instead of using arbitrary percentages.

Finally, it doesn’t stop at “price hit X.” It suggests position sizing (e.g., scale in vs full entry) and provides an estimated entry range for limit orders based on recent volatility.

So this tool is much more than price alert, but a structured execution framework: pullback + stabilization + market context + sizing + entry range.

That was a good question. I'm glad you asked! Let me know if you have any more question. But the best way to learn about this tool is to sign up to test it. Thanks!