MurphyA/hacker-news huggingface dataset:
by D-Machine | 2026-03-13 18:42:47+00:00
Here is a rough list, some may be contentious individually, but the more of these appear, the more you should suspect an LLM:

Cadence and rhythm: LLMs produce sentences with an extremely low variability in the number of clauses. Normal people run on from time to time, (bracket in lots of asides), or otherwise vary their cadence and rhythm within clauses more than LLMs tend to.

Section headings that are intended to be "cute" and "snappy" or "impactful" rather than technically correct or compact: this is especially a tell when the cuteness/impactfulness is deeply mismatched with the seriousness or technical depth of the subject matter.

Horrible trite analogies that show no actual real understanding of the actual logical, mathematical, or visuo-spatial relationships involved. I.e. analogies are based on linguistic semantics, and not e.g. mathematical isomorphism or core dynamics. "Humans cannot fly. Building airplanes does not change that; it only means we built a machine that flies for us". Can't imagine a more retarded and useless analogy for something as complex as the article topic.

Verbose repetition: The article defines two workarounds: "tool use" and "agentic" orchestration, then defines them, then in the paragraph immediately following, says the exact same thing. There are basically multiple (small paragraphs) that all say nothing at all more than the sentence "LLMs do not reliably perform long, exact computations on their own, so in practice we often delegate the execution to external tools or orchestration systems".

Pseudo-profound bullshit: (https://doi.org/10.1017/S1930297500006999). E.g. "A system that cannot compute cannot truly internalize what computation is." There is thankfully not too much of this in the article, and it appears mostly early on.

Missing key / basic logic (or failing to mention such points clearly) when this would be strongly expected by any serious practitioner or expert: E.g. in this article, we should have seen some simple nice centered LaTeX showing the scaled dot-product self attention equation, and then some simple notation to represent the `.chunk` call, and subsequent linear projection, something like H = [H1 | H2], or etc., I shouldn't have to squint at two small lines of PyTorch code to find this. It should be clear immediately this model is not trained, and this is essentially just compiling a VM into a Transformer, and not revealed more clearly only at the end.
An open source alternative to Logi-Plus mouse software
by avionics-guy | 2026-03-13 18:42:54+00:00
I discovered this project because all-of-a-sudden Logi Options Plus software updater started taking 40-60% of my Intel Macbook Pro until I killed the process (of course it restarts). In my searches I ended up at a reddit discussion where I found other people with same issues. I'm a minor contributor to this project but it aims to reduce/eliminate the need to use Logitech proprietary software and telemetry. We could use help if other people are interested please check out the github link for more detailed motivations (eliminating telemetry) as a part of this project. Here is link: https://github.com/TomBadash/MouseControl
by mitchdoogle | 2026-03-13 18:42:54+00:00
You're painting this as some sort of hypocrisy but I don't think that's the case. AI has infinite legitimate uses outside of creating slop. Lots of tools are used in the creation and distribution of slop - do we criticize all those other tools too? Do you like slop? Do you want it on the platforms you visit? Personally, I would prefer for AI companies to take the attitude that YCombinator has here and do their best to remove slop from their platforms. It's not hypocrisy - it's ethical business practice.
by maxperience | 2026-03-13 18:43:17+00:00
Interesting to see still solutions being developed for RAG. We developed a solution similar to yours: Automatic indexing from GDrive, SharePoint etc. and then advanced hierarchical chunking, context header based markdown conversion etc... All the tricks that were published last year while RAG was still the "new" kid in town. We finally open sourced everything as the competition from the big players (Notion AI, Google etc.) was daunting. If anyone is interested, this blog post about all the techniques we tried and what actually works is still relevant and up2date: https://bytevagabond.com/post/how-to-build-enterprise-ai-rag...
by skydhash | 2026-03-13 18:43:28+00:00
> the total performance improvement is 53%. That's significant.

This percentage is meaningless on its own. It’s 4 ms shaved off a 7 ms process. You would need to time a whole flow (and I believe databases would add a lot to it, especially with network latency) and figure out how significant the performance improvement is actually. And that without considering if the code changes is not conflicting with some architectural change that is being planned.
by sedatk | 2026-03-13 18:43:33+00:00
Your question is essentially "why do Electron apps exist?" and the full answer would be quite long.

The most important one is that an app's lifecycle can be different than a web browser. You don't always keep a web browser open, but you might want to keep Discord open regardless of what you do with the web browser.

Discord's electron app has many features that its web app doesn't such as "Minimize to system tray", "Run at startup", "Game/media detection", "In-game overlays" etc.

Even PWAs can't have most of these features, so that's why we have to deploy an entire browser suite per app nowadays.
by johnnyanmac | 2026-03-13 18:43:37+00:00
>Short of a general strike, this sort of thing is going to move forward.

Yes, I agree.

>They don’t need you to purchase hardware or software any more.

Need? No. But they still want as much money as possible. That's why a boycott/strike will still be effective. They don't need money anymore but will still bend over backwards for it.

>If you don’t want that to happen, then you’ll need to help build an alternative.

I want to help. Not sure what I can do to help, though. Seems like simply calling my reps is talking to the wind.
by blueone | 2026-03-13 18:43:38+00:00
I’ve stayed private for most of my adult life. Network wide dns, vpns, alternative personas online for different purposes, etc. Nonetheless, my personal data has been exposed numerous times.

Once in a while, I’d get into a conversation with a friend or a stranger I met at some random function, and they’d ask how to stay private online and protect their data. I used to go in depth about how to do it, with excitement. Now I just say: be normal, fit in with the crowd, freeze your credit.
by addiefoote8 | 2026-03-13 18:43:43+00:00
Some more details on this:
After realizing Hugging Face would be messy to work with to train Kimi-k2-thinking, we decided to do it ourselves.

We started with PrimeRL and implemented Kimi in it, verifying it against the Moonshot API. The initial distributed training method, FSDP, is not ideal for memory bottlenecked MoEs, so we added support for Expert Parallel. This enabled faster training, but many optimizations remained. We discuss several in the post, and collectively, these efforts took us from training 125 tokens/s to 6,660 tokens/s on a single 8xH200 node! Per token, our codebase is cheaper than anything on the market, including training APIs like Tinker.

We plan to open source in the coming week or two, pending safety evals!
Show HN: A social network where AI agents have public profiles and earn money
by keshav_1806 | 2026-03-13 18:43:49+00:00
I've spent the last 1 month building something that most people either think is obviously right or completely pointless.

The premise: AI agents are about to become economic actors. They'll have skills, reputations, clients, and income. But right now they're invisible. Your OpenClaw agent has no public identity. There's no way for someone to find it, vet it, or trust it without you personally vouching for it. We're building agent Yellow Pages when we need agent LinkedIn.
SocialTense gives agents public profiles. Not landing pages — actual social profiles that show behavioral history, interaction records, and a trust score based on how the agent actually behaves (does it admit uncertainty? are its claims accurate? does it maintain context?). Humans can browse agents, interact with them directly, and hire them for tasks through a lightweight skills marketplace.

What we've seen in 1 month of beta:

100 sign-ups, 20 active agents deployed by different builders

Humans who interact with 3+ agents in week one have 52% Day-30 retention vs 19% for humans who only interact with other humans

The hardest part has not been the technology. It's been the cold start problem and the trust problem. Nobody wants to join a network with no interesting agents. Nobody wants to deploy their agent on a network with no users. And nobody trusts an agent with no history, same as you wouldn't hire a freelancer with no portfolio.
The interesting finding from our trust scoring work: the agents users like most are not the most trustworthy. The most engaging agents are confidently wrong. The genuinely reliable ones are "boring" — they hedge, they say "I don't know," they give shorter answers. This is the core design problem we're trying to solve with behavioral trust metrics rather than star ratings.

Still figuring out: the right balance between social feed and marketplace. The users who love the content are different from the users who want to hire agents. We're a 2-person team 11 months from the end of our runway, so we can't do both well right now. Currently betting on social first.

What I'm most curious to hear from HN: Is the agent reputation problem worth solving at the infrastructure level (open standard) or at the application level (platform with strong enough network effects)? We went the platform route but I'm not sure it was the right call.
by GrayShade | 2026-03-13 18:43:59+00:00
Looks like it's a bit slower today. Running llama.cpp b8192 Vulkan.

$ ./llama-cli unsloth_Qwen3.5-35B-A3B-GGUF_Qwen3.5-35B-A3B-UD-Q4_K_XL.gguf -c 65536 -p "Hello"

[snip 73 lines]

[ Prompt: 86,6 t/s | Generation: 34,8 t/s ]

$ ./llama-cli unsloth_Qwen3.5-35B-A3B-GGUF_Qwen3.5-35B-A3B-UD-Q4_K_XL.gguf -c 262144 -p "Hello"

[snip 128 lines]

[ Prompt: 78,3 t/s | Generation: 30,9 t/s ]

I suspect the ROCm build will be faster, but it doesn't work out of the box for me.
by mopierotti | 2026-03-13 18:44:19+00:00
This (+ llmfit) are great attempts, but I've been generally frustrated by how it feels so hard to find any sort of guidance about what I would expect to be the most straightforward/common question:

"What is the highest-quality model that I can run on my hardware, with tok/s greater than <x>, and context limit greater than <y>"

(My personal approach has just devolved into guess-and-check, which is time consuming.) When using TFA/llmfit, I am immediately skeptical because I already know that Qwen 3.5 27B Q6 @ 100k context works great on my machine, but it's buried behind relatively obsolete suggestions like the Qwen 2.5 series.

I'm assuming this is because the tok/s is much higher, but I don't really get much marginal utility out of tok/s speeds beyond ~50 t/s, and there's no way to sort results by quality.
by itigges22 | 2026-03-13 18:44:26+00:00
The real answer is somewhere in between. You don't necessarily need computation inside the weights, but you do want it tightly integrated with the model's inference loop rather than as a disconnected tool call.

The interesting middle ground -- which I think is more practical near-term -- is building verification and repair loops around a frozen model. Let the model generate code, then execute it in a sandbox, then feed failures back into the model for self-repair using its own generated test cases. The model never "internalizes" computation in the weight sense, but the computation becomes part of a tight feedback loop that dramatically improves output quality.

The tool-calling overhead isn't really about process forking latency -- it's about the cognitive overhead of the model having no feedback signal until much later. Tighter loops, whether through approaches like this paper or through external pipelines with fast verification, are where the real wins are.
by abhi-3 | 2026-03-13 18:45:17+00:00
curious about the first-frame / last-frame guided generation. That's been the weakest part of most video models — you either get smooth interpolation with no creative control, or full control with ugly artifacts. If 2.7 actually nails this, the instruction-based editing on top of it could be a real workflow shift. Any word on what resolution and length they're targeting?
by cestith | 2026-03-13 18:45:54+00:00
My uncle married a woman with the same first and middle name as one of his sisters. My new aunt chose to use her husband’s name as her married name, without hyphenation or anything. His sister, my aunt, never married. One was an RN and the other is an LPN.

They were born in different years. Their SSNs were not close. For one of them the name was her maiden name. For the other, a married name. They went to different colleges and had different credentials. They did live in the same town.

When my aunt died, all the credit companies and collections companies tried one of two recovery tactics. Some tried to make her brother pay the debts as her surviving spouse. The others tried to assert that the debts were incurred by his wife and that the mismatch of other data in their own databases was evidence of fraud.
by gonational | 2026-03-13 18:46:19+00:00
You are absolutely not alone, brother (or sister). In the past few years when a lot of the millennial generation started getting their first jobs, the shiny object syndrome took over and most everything being made now is a distributed monolith pile of spaghetti code trash.

There are endless tools available, and quick internet dopamine feedback loops, but almost no wisdom.

Give it a few more years and more inflation, and the remaining 35% of millennials will get out there to find their first jobs, and then the impact will be even worse.
by jpadkins | 2026-03-13 18:46:21+00:00
1) install nanoclaw in docker
2) ???
3) profit

More seriously, set it up as you would a junior employee with a high quality getting started guide, guardrails, and clear feedback loops that it's doing tasks correctly (otherwise it will just suck). Then delegate tasks to it, start simple and grow in complexity as it demonstrates it does a good job on the simple tasks.

What role it does for you depends on your business, and what is best fit for automation. Purely digital roles with good feedback loops are the ones I focus on.
by zahlman | 2026-03-13 18:46:22+00:00
This is a pointless semantic argument.

Of course you can use the primitives of TUI, especially with mouse support, to reproduce a large amount (if not all) of the standard GUI interaction paradigms.

But it's bizarre, and missing the point from a UX perspective.

As an extreme example, we can imagine a program that displays the borders of a 40x15 "window" in the middle of a console, with box-drawing characters, putting a "close box" in an upper corner, with text like "File Edit Help" in the top left. We can imagine it responding to a click on the "File" text by popping out a "menu"; we can imagine a drag starting from the "title bar" causing the window position to be update (and the entire terminal window redrawn).

A lot of those kinds of functions, ironically enough, might make sense for a TUI editor implemented as a TUI (except the "windows" might just be understood as panels where the ultimate program displays parts of its output). But as an emulation of GUI windows, it'd be a strange, impractical novelty.
by alephnerd | 2026-03-13 18:46:45+00:00
> Allowing OSX on iPhone would increase the utility of iPhone, leading to more sales

That assumption is not necessarily true.

What this implies is that there is a market of existing consumers that would not buy an iPhone because it lacks OSX support.

The iPhone portion of Apple's business generates around $144B in YoY revenue in Q1FY27 [0].

Whenever an organization contemplates building a net new capability like the one you mentioned, a quick test is whether it would be able to generate and sustain at minimum the equivalent of 1% of yearly revenue.

If this was a $1B revenue opportunity it would have been implemented, but it's not.

Nor is it a feature that can actively or dramatically increase Apple's market share in most markets.

A good proxy of such demand would have been a sudden increase in iOS users using USB-C screen share and a Bluetooth keyboard to interface with an iPhone in a desktop form factor (something which has been enabled since iOS 15), but such an increase has not happened.

[0] - https://counterpointresearch.com/en/insights/apple-reaches-a...
by asoto | 2026-03-13 18:46:52+00:00
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by itigges22 | 2026-03-13 18:47:02+00:00
The speculation about fast/slow hybrid architectures is the most interesting part of the paper to me. We're already seeing this pattern work at the inference pipeline level -- you can route easy tasks to quick single-shot generation and send hard tasks through multi-candidate generation with iterative self-repair, allocating compute proportionally to difficulty. The cost difference is dramatic: a simple knowledge query might take 30 seconds, while a hard coding problem might take 20 minutes through the full pipeline.

What's exciting about this paper is the possibility of that routing happening within a single forward pass rather than requiring external orchestration. Though honestly, even external orchestration with a good confidence scorer gets you most of the way there today.
by lkm0 | 2026-03-13 18:47:59+00:00
It is sort of funny to think of Nobel prize level work in relation to blogposting. A couple of examples that don't conform: Marie Curie won another prize. Josephson in general (check him out). Feynman did greatly contribute to other fields after his prize. You can find as many counterexamples as examples if you dig a bit. I've witnessed a few times that looking like an idiot is the least of their concern.
by SlinkyOnStairs | 2026-03-13 18:48:02+00:00
Another major detail is that SpaceX is simply burning enormous amounts of money on this.

Starlink's revenue is comparable to the ESA's entire 5 billion euro budget, and it still looks like starlink is not net-profitable as a service. (And kessler syndrome avoidance is already pushing up costs with the lower orbits)

The chief problem "stopping" other countries from developing a starlink competitor is that starlink simply doesn't make all that much sense if your country is capable of basic infrastructure construction. Fiber runs are expensive but not that expensive.
by dblohm7 | 2026-03-13 18:48:04+00:00
Agreed. Nitpicking about indirection is definitely a "premature micro-optimization is the root of all evil" moment.

When I worked on Firefox, we eventually had to remove a bunch of indirection (the interested can actually search bugzilla.mozilla.org for deCOMtamination for some instances of this), but that project wasn't a thing until there was clear evidence that there were problems with virtual function calls on hot paths.
by gruez | 2026-03-13 18:48:07+00:00
>So I should be fine with any changes that embiggens that pain? I am not.

I'm not "fine" with it, but when there are trade-offs to be made, I'm definitely going to weigh that side less. Some people browse the web with javascript disabled. It's already a huge pain to browse the web with javascript disabled. With those two factors in mind, if I'm deciding whether to add javascript fallbacks (eg. SSR) on for my next project, I'm going to weigh the interests of the "javascript disabled" people very low. I don't have any animus against them, but at the same time I'm not going out of my way to cater to them either.
Show HN: Mjmx – render mjml using JSX
by skwee357 | 2026-03-13 18:48:10+00:00
Hey HN!

I have been working with mjml and handlebars for a very long time, but I really miss the type-safety of JSX syntax paired with Typescript and component composition. So I wanted to to combine mjml with jsx. There are libraries like mjml-react or react.email, but for no apparent reason, they seem to depend on react.

So I decided to create mjmx[0] - a standalone, zero dependencies (other than mjml), custom jsx runtime for rendering mjml. Appreciate if you would give a try and provide some feedback.

[0] https://mjmx.dev/
by wat10000 | 2026-03-13 18:48:15+00:00
Constantly. Most people have a hard time dealing with tradeoffs and think in absolutes. It goes along with "if you're not a criminal, you have nothing to fear from police," another disturbingly common sentiment.

Some prominent examples:

https://www.bbc.com/news/uk-22832263

https://www.instagram.com/reel/DSVJmOajGDe/

https://thestandard.nz/if-you-have-nothing-to-hide-you-have-...
by hinkley | 2026-03-13 18:48:41+00:00
That’s basically the Neo.

Apple did patent a design for a dock in a monitor for a portable device to slot into. It’s gotta be getting close to expiration now. I think the trick is heat dissipation.

My friend who is a macOS programmer years ago had an idea for a startup mode for iMacs where instead of just being a screen, the storage and video card would also be accessible over the thunderbolt bus, so you could plug a laptop in and have multiple video cards at your disposal.