MurphyA/hacker-news huggingface dataset:
by CuriouslyC | 2025-09-03 20:53:24+00:00
I also have a 24gb card. Local LLMs are great for a lot of things but I wouldn't route coding questions to them, the time/$ tradeoff isn't worth it. Also, don't use LiteLLM, it's just bad, Bifrost is the way.

You can use a LLM router to direct questions to an optimal model on a price/performance pareto frontier. I have a plugin for Bifrost that does this, Heimdall (https://github.com/sibyllinesoft/heimdall), it's very beta right now but the test coverage is good, I just haven't paved the integration pathway yet.

I've got a number of products in the works to manage context automatically, enrich/tune rag, provide enhanced code search. Most of them are public and you can poke around and see what I'm doing. I plan on doing a number of launches soon but I like to build rock solid software and rapid agentic development really creates a large manual qa/acceptance eval burden.
by matheusmoreira | 2025-09-03 20:53:41+00:00
> until 1985, Brazil was a dictatorship

It's a dictatorship today. Has been since at least 2019. The unelected supreme court is ruling the country.

> The kind that "disappears" and tortures journalists and political opponents.

Nothing's changed, that's still the case today. Plenty of journalists, opponents, judges dead in mysterious circumstances. Including the judge who mysteriously died and made room for Alexandre de Moraes, who the USA would go on to sanction via Magnitsky. Even Bolsonaro himself suffered an assassination attempt.

> People like the current president Lula, who was imprisoned during the dictatorship.

Yeah, because he's a socialist who openly schemes to install socialism in Brazil. You know, the exact thing the military dictatorship wanted to prevent.

He was also imprisoned during our democracy for record breaking corruption, before the supreme court threw out all the evidence and set him free to take out Bolsonaro.

> The USA on the other hand, has never had a dictatorship in living memory.

They've never had presidents that openly admit to plotting to install socialism in their country either. Good thing they have the CIA to get rid of such subversives. Socialism should be criminalized, just like nazism.
by kfreds | 2025-09-03 20:54:15+00:00
The way I see it there's four use cases:

- protecting your privacy from your local ISP, WiFi, school, government etc

- protecting your privacy from some forms of online tracking

- circumventing censorship

- circumventing geographical restrictions

If you combine masking of your IP address with a web browser that protects you from various types of browser-based fingerprinting, you are more in control of your privacy online. You get to decide, to a greater extent, who you share very personal information with. That doesn't seem very silly.

(disclosure: I'm one of the deeply silly cofounders of Mullvad)
by recroad | 2025-09-03 20:54:24+00:00
Elixir/Phoenix is awesome, no complaints overall. A few small things:

- Passing data from LiveComponent's/JS is a bit of a pain (need to use update())

- phx-hook doesn't always pay well with re-rendering state changes

- Directly calling JS functions (e.g, getting Apple Pay to work) isn't clean

- Can't use attr when using LiveComponents (need to wrap them in a functional component)

- Unique ID requirement for LiveComponent is a pain (so is wrapping them in a div)

- No great APIs for updating session data when using sockets

- Can't pass params to LiveView in live_render, have to use session
by dilipdasilva | 2025-09-03 20:54:36+00:00
VDX.tv (http://www.vdx.tv) | Remote Engineers & Developers | Full-time | REMOTE Established company (20+ years) looking for mature generalists to contribute remotely. You can be anywhere in the world so long as you:

● Are self-motivated and can work independently

● Driven to constantly learn and are always searching for the bigger picture

● Strong in clear thinking and written communication

● Have experience with many languages but can be effective in any language

● Appreciate that all mature software solutions accumulate technical debt and understand how to continually reduce debt and complexity

● Understand how to build highly reliable systems and be responsible for taking code to production

● Understand that code simplicity and readability are more important for long term maintainability

● Want to work on challenging problems and impactful work without being micromanaged

We're hiring across disciplines for engineers who work with Unix and have fluent written and spoken English:

● Backend Servers: Strong in C, Concurrency and Distributed Computing

● Backend Servers: Strong in Java

● Infrastructure: Strong in building infrastructure tooling to program infrastructure.

● Frontend: Strong in Javascript, Typescript, React, and advanced UI and browser applications

● Artificial Intelligence: Strong in Neural Networks, AI Workflows, AI Models.

● Product Design: Ability to spec and build out clean UIs and dashboards.

We value people who are generalists and are interested in learning, developing, and applying expertise across multiple areas. Although our core business is in digital video advertising, we do research and development in areas such as programming languages, databases, distributed computing, infrastructure, and ai. We are private, which gives us the freedom to explore many areas without investors and profits being the sole objective.

Full-time only. Remote only. We start out on a full-time trial contract basis for up to 3 months and use this period as an extended work interview for both sides to assess fit for long-term employment.

Please email hn.remote.jobs@vdx.tv if this sounds like the right fit for you.
by magicalist | 2025-09-03 20:54:42+00:00
This is cool it works so well (less the performance claims and more the correct translations).

Not to take away from the nice writeup, but for anyone not getting far enough into the writeup, this is essentially taking https://github.com/ScalingIntelligence/KernelBench and seeing if it can generate Metal kernels in addition to the CUDA kernels the benchmark is written for. The dataset was released in November 2024, it looks like, with a paper on arXiv in February and a bunch of discussion at the time[1], so worth keeping likelihood of inclusion in training data in mind when comparing models.

The different levels are interesting. Level 1 and 3 are successfully (5-shot) translated to Metal kernels by gpt5 97% and 88% of the time , but in both cases, the majority of generated kernels are slower than the reference compiled pytorch versions. The speculation about more simple op fusion opportunities in the Level 2 kernels vs the very simple Level 1 kernels and the complex architecture Level 3 kernels seems plausible. From the KernelBench paper, it looks like Level 2 kernels were mostly automatically generated from randomly picking operators and then getting an LLM to generate a kernel combining them, while Level 1 were mostly hand written and Level 3 came from well-known ML architectures.

The swarm part seemed a bit of a stretch. They fired off requests to 8 different models to do the translation, and the "supervisor" benchmarked the returned kernels and picked the fastest one. Technically a swarm, I guess, but feels like we're devaluing the term :)

The correctness testing used made my eye twitch a bit:

> We tested the generated kernel's output against the default implementation's output on 100 random inputs. We set a 0.01 tolerance for both relative and absolute. Let a be the generated kernel output, and b be the reference kernel output. Outputs were considered equal if for every element in the output, absolute(a - b) ≤ (atol + rtol absolute(b)) held true.*

For a numerical kernel, this seems way too loose, but turns out those bounds come straight from KernelBench, which only tested for correctness on 5 random inputs by default in their harness, not the 100 they used here. KernelBench mentions the clear tradeoff they get between how strictly they define correctness and kernel performance, but for Level 1 kernels in particular, which are really just single operations, it seems like the bounds should be multiple orders of magnitude smaller to ensure robust translation. For instance, the all 0s "optimization" mentioned in the writeup allowing for trivially translating the kernel looks like it's due to those loose tolerances[2] and KernelBench was looking to make the evaluation more robust.

[1] Like https://metr.org/blog/2025-02-14-measuring-automated-kernel-...

[2] https://github.com/ScalingIntelligence/KernelBench/pull/25
by norman784 | 2025-09-03 20:55:20+00:00
OTOH I'd ten to prefer as less plugins as possible in VSCode, just because they are inherently dangerous, I'd like Zed plugins that are WASM, so they don't have access to the world.

But I agree that VSCode Typescript support is better than Zed, it works with weird projects setup, while Zed has more troubles. I at work VSCode and Zed/Helix for my projects, generally I use Zed when want to do some AI stuff, otherwise I just use Helix.
If Trump Offered Zero Tariffs on Indian Products, Would India Buy Russian Oil?
by rohan_shah | 2025-09-03 20:55:20+00:00
I don't think India will have any incentive to buy Russian oil if Trump makes favourable trade deals with India, it is known that USA can't manufacture a lot many goods because of lack of cheap labour which India has in abundance along with democracy and a rule of law.

Why is USA being so hostile to India, I simply don't understand!
by I_dream_of_Geni | 2025-09-03 20:55:44+00:00
I am really confused about this article and responses. We ALL knew this was coming years ago. Fake news, faked photos, faked videos have been out there for EONS. Kids in school have been using AI to create term papers that don't pass the fact-check. And AI has "hallucinated" since the beginning. Now people are shocked when a news outlet doesn't double-check the sources...
by pavel_lishin | 2025-09-03 20:55:52+00:00
I disagree with the bicycle analogy or by how much AI currently improves productivity, but I do agree that these code tools are likely here to stay - so my advice would be to at least become familiar with them.

You don't have to love them, you don't even necessarily have to use them, but if we're sticking with the bicycle analogy, you do need to know to look before crossing the street, and you need to be able to put a bike into the correct gear if you have to ride it.
by troupo | 2025-09-03 20:56:03+00:00
And that's the biggest problem with Shadow DOM (and most web component specs): you can't chose the good parts. Style encapsulation is useful, slots are useful, Shadow DOM is just all around bad, having a crazy amount of edge cases and broken behaviours [1].

Can you use style encapsulation and slots without Shadow DOM? Why can't you? I only need the horse, not the horse, and the cart, and the driver, and all the cargo in the cart.

You can't because people pushing all this stuff forward never ever stopped to think whether this was a good idea, and never ever talked to anyone outside of their own group.

[1] I will keep quoting this report by Web Components Working Group to death:

--- start quote --

It's worth noting that many of these pain points are directly related to Shadow DOM's encapsulation. While there are many benefits to some types of widely shared components to strong encapsulation, the friction of strong encapsulation has prevented most developers from adopting Shadow DOM, to the point of there being alternate proposals for style scoping that don't use Shadow DOM. We urge browser vendors to recognize these barriers and work to make Shadow DOM more usable by more developers.

...

Shadow boundaries prevent content on either side of the boundary from referencing each other via ID references. ID references being the basis of the majority of the accessibility patters outlines by aria attributes, this causes a major issue in developing accessible content with shadow DOM. While there are ways to develop these UIs by orchestrating the relationships between elements of synthesizing the passing of content across a shadow boundary, these practices generally position accessible development out of reach for most developers, both at component creation and component consumption time.

...

Selection does not work across or within shadow roots. This makes fully-featured rich-text editors impossible to implement with web components. Some of the web's most popular editors have issues that are blocked on this functionality.

--- end quote ---
by magicalist | 2025-09-03 20:56:45+00:00
Feels like they should have released some code, yeah, but gpt5 success rate was high enough that it looks like you can just pass the kernels they got from https://github.com/ScalingIntelligence/KernelBench/ to gpt5 (with up to five rounds of feeding back compilation/correctness errors back to the model) and get the results yourself.
by chermi | 2025-09-03 20:56:52+00:00
Ignoring energy costs(!), I'm interested in the following. Say every server generation from nvda is 25% "better at training", by whatever metric (1). Could you not theoretically wire together 1.25 + delta more of the previous generation to get the same compute? The delta accounts for latency/bandwidth from interconnects. I'm guessing delta is fairly large given my impression of how important HBM and networking are.

I don't know the efficiency gains per generation, but let's just say to get the same compute with this 1.25+delta system requires 2x energy. My impression is that while energy is a substantial cost, the total cost for a training run is still dominated by the actual hardware+infrastructure.

It seems like there must be some break even point where you could use older generation servers and come out ahead. Probably everyone has this figured out and consequently the resale value of previous gen chips is quite high?

What's the lifespan at full load of these servers? I think I read coreweave deprecates them (somewhat controversially) over 4 years.

Assuming the chips last long enough, even if they're not usable for LLM training/serving inference, can't they be reused for scientific loads? I'm not exactly old, but back in my PhD days people were building our own little GPU clusters for MD simulations. I don't think long MD simulations are the best use of compute these days, but there's many similar problems like weather modeling, high dimensional optimization problems, materials/radiation studies, and generic simulations like FEA or simply large systems of ODEs.

Are these big clusters being turned into hand-me-downs for other scientific/engineering problems like above, or do they simply burn them out? What's a realistic expected lifespan for a B200? Or maybe it's as simple as they immediately turn their last gen servers over to serve inference?

Lot of questions, but my main question is just how much the hardware is devalued once it becomes previous gen. Any guidance/references appreciated!

Also, anyone still in the academic computing world, do people like de shaw still exist trying to run massive MD simulations or similar? Do the big national computing centers use the latest greatest big Nvidia AI servers or something a little more modest? Or maybe even they're still just massive CPU servers?

While I have anyone who might know, whatever happened to that fad from 10+ years ago saying a lot of compute/algorithms would be shifting toward more memory-heavy models(2). Seems like it kind of happened in AI at least.

(1) Yes I know it's complicated, especially with memory stuff.

(2) I wanna say it was ibm Almaden championing the idea.
by UncleEntity | 2025-09-03 20:56:53+00:00
From what I understand the three plate method is when you are going from 0 to flat as the errors are averaged out.

Doing the "covered with dye and rubbed together to find the high points, which are then scraped off" thing is only if you already have a flat reference surface as you wouldn't have a way to know if the thing you're trying to make flat is really flat.

The real question is how do you get the first flat reference surface when all you have are a few somewhat flat things?
by phatskat | 2025-09-03 20:56:57+00:00
Git always baffled me with revert - I learned early on that if I wanted to “undo” something, the best bet was to either branch from a commit before the thing I want undone, and maybe rebase/cherry pick later commits, or just start over.

This seems like the ideal case for revert, but the way that it alters the history stings - the fact that reverting a commit essentially means that said commit can’t show up later as a change is frustrating - also I’m sure it’s a case of user error, but…”merge branch, realize there’s a big oops in there, revert, fix the oops on the branch” feels like it shouldn’t result in a state where git doesn’t accept the branch as mergable.
by dotnet00 | 2025-09-03 20:57:02+00:00
This attitude is dumb, people don't just have one thing open on their machine at a time.

If you're designing software like a music player (that is, something people are likely to want to keep running in the background while doing other things), you're just giving people a reason to switch to something else by taking up a bunch of memory carelessly, as it'll be one of the first things to go when the user needs the memory.
by awesome_dude | 2025-09-03 20:57:26+00:00
I think that the difference can be best explained thus:

I guess that you are most likely going to have cereal for breakfast tomorrow, I also guess that it's because it's your favourite.

vs

I understand that you don't like cereal for breakfast, and I understand that you only have it every day because a Dr told you that it was the only way for you to start the day in a way that aligns with your health and dietary needs.

Meaning, I can guess based on past behaviour and be right, but understanding the reasoning for those choices, that's a whole other ballgame. Further, if we do end up with an AI that actually understands, well, that would really open up creativity, and problem solving.
by measurablefunc | 2025-09-03 20:57:54+00:00
What part about backtracking is baseless? Typical Prolog interpreters can be implemented in a few MBs of binary code (the high level specification is even simpler & can be in a few hundred KB)¹ but none of the LLMs (open source or not) are capable of backtracking even though there is plenty of room for a basic Prolog interpreter. This seems like a very obvious shortcoming to me that no amount of smooth approximation can overcome.

If you think there is a threshold at which point some large enough feedforward network develops the capability to backtrack then I'd like to see your argument for it.

¹https://en.wikipedia.org/wiki/Warren_Abstract_Machine
by lovich | 2025-09-03 20:57:56+00:00
Well then congratulations, you seem to have progressed high up enough in your career to not have to deal with that.

I have literally never had an interview process with a company consist of less than 4-5 hours of interview rounds or an equivalent sized take home project. Roughly 50-60 interview cycles over 12 years. That includes companies where I was referred in by the hiring manager.
by wtallis | 2025-09-03 20:58:06+00:00
You're still dodging the issue. Your article title accusing Apple of an "assault on standards" is implicitly treating Google's proposals as a fait accompli that Apple is resisting, which is not at all what the situation is for many of the Chrome features you are trying not to be specific about.

You say that shipping ahead of others is risky, but can't seem to acknowledge when the negative outcome comes to pass and other browser vendors aren't interested in adopting questionable feature proposals.
by tom_ | 2025-09-03 20:58:45+00:00
I'd say it's definitely weird for a standalone assembler. For standalone 6502 assemblers, some approximation of the standard MOS-type syntax has always been near-universal. Though you're quite correct about some of the advantages of doing it this way.

(I say "near universal", because Acorn's MASM had a similar syntax. (See, e.g., https://github.com/stardot/AcornDmosBasic/blob/master/src/DB...) I don't remember ever seeing that described as anything other than an oddity.)

And, also, there are probably assemblers smooshed into Forth or Lisp (or implemented with assembler macros for an assembler targeting some completely unrelated CPU) that work in a similar way, because you're limited by the pre-existing syntax rules. But that feels like a separate category
Show HN: I made a stock image generator
by jblox | 2025-09-03 20:58:56+00:00
Lots of products I have seen are very AI intensive, with things like selectors for the model to use. Yet 99% of the end users for these tools are not in our AI bubble and don't know what all of these models are! So I've taken a different approach and just made a simple, ask for what you want tool. The user provides a prompt and/or some input images along with a style and then the product handles everything else in the background - it enhances the prompt, selects the best model and generates the content.
by Borg3 | 2025-09-03 20:58:58+00:00
The only valid reason you mention here are legacy Windows, like 9x series. Anything NT based is happy with LF only if you have right tools.

I never touched ReactOS, but I suspect is modern enough to handle LF only too. It was targeting Win2003 AFAIR.

So yeah, I stand corrected abit. If you develop only for windows (especially legacy), use CRLF. Anything w/ portability in mind, go for LF only...
by nielsberkhout | 2025-09-03 20:59:05+00:00
As a SaaS platform in HR, we believe everyone should have the opportunity to try smart sourcing and personalized outreach.

That's why we’ve opened up SourceGeek for anyone who’d like to give it a try.

The free trial gives you enough time to run one or more campaigns and gain detailed insights into potential candidates, including their soft skills.

Start your free trial today and experience the real benefits of AI and automation in your search for the best talent for your company or clients.
by chrispiemonte | 2025-09-03 20:59:28+00:00
Location: Chicago, IL

Remote: Open for Remote, In-Office, or Hybrid

Willing to relocate: Yes

Technologies: JavaScript, TypeScript, Ruby, Python, SQL, React, Express, Sinatra, Jest, Vitest, AWS, DocumentDB, MongoDB, PostgreSQL, RDS, Docker, RAG, MCP, AI/LLM, WebSockets, SSE

Résumé/CV: https://drive.google.com/file/d/1x21eDXHTo1fWlgYakfyiuc-0k0w...

Email: chrisjpiemonte@gmail.com

I am a Full-Stack Software Engineer based in Chicago with multiple years of experience in the JavaScript/TypeScript, Ruby, and Python ecosystems, and have worked extensively with AWS and Docker. In collaboration with two other software engineers I recently co-created Pendulum, a comprehensive Backend-as-a-Service platform that provides real-time synchronization out-of-the-box while keeping you in control of your data and infrastructure.
by asdefghyk | 2025-09-03 21:00:07+00:00
Google of 3 words Vermont Views, software still picks up several links

Borland Turbo Pascal and Borland Delphi where also (similar) products from around that time. These products where popular at the time. ( The development system provide include some kind of windows system for the application )

Microsoft even hired key Delphi person ....
by crowbahr | 2025-09-03 21:00:14+00:00
Really? It sure seems like we're at the top of the S curve with LLMs. Wiring them up to talk the themselves as reasoning isn't scaling the core models, which have only made incremental gains for all the billions invested.

There's plenty more room to grow with agents and tooling, but the core models are only slightly bumping YoY rather than the rocketship changes of 2022/23.