MurphyA/hacker-news huggingface dataset:
Show HN: a glimpse into the future of eye tracking for multi-agent use
by dochrty | 2026-02-07 21:14:42+00:00
Hi HN, I’m the creator of glimpsh.

glimpsh is an experimental project exploring gaze input inside the terminal. The idea is to treat eye tracking as a secondary input signal alongside keyboard and mouse.

One motivating use case is multi-agent management. Using gaze to quickly switch focus between running agents or processes, inspect state, or trigger context-sensitive actions without constant keybindings.

I’m also interested in pushing on the quality of commodity eye-tracking software as an HCI tool. Webcam-based eye tracking is widely available but often inaccurate and underexplored in real interfaces. This project is a way to stress-test those tools in a demanding UI environment.

I’m curious about combining gaze with other high-bandwidth input, especially voice. Systems like Wispr suggest that voice plus gaze could work well together, for example in terminal multiplexors where gaze establishes focus and short commands trigger actions.

This is not meant to replace efficient keyboard-driven workflows. Many users are already extremely fast with keybindings. The goal is to explore whether gaze and voice can act as complementary tools when managing many concurrent agents or streams of information.

This is very early and experimental. I’d especially love feedback on:

whether gaze as a secondary input makes sense in terminal workflows

multi-agent or TUI use cases that might benefit

accessibility implications

thoughts on combining gaze and voice in developer tools

Happy to answer questions or dig into implementation details.
by colechristensen | 2026-02-07 21:14:54+00:00
Russia has been working on Trump for decades, he's an amusing idiot. They manipulated him, people around him, the electorate, and the election to engineer the situation where this fool is in the presidency. They have hard power over him (compromising pictures, information, loans, etc) and soft power over him (he admires strongmen autocrats).

The rise of the alt-right took weaknesses in the right and left and amplified them to engineer the situation where there was a populist takeover of the Republican party. Epstein met moot. 4chan took a turn from being the asshole of the internet that was the original source of the concept of memes and a lot of other internet culture and turned it political and the conspiracies and thought processes jumped from 4chan to your dimwitted fox news loving uncle.

All of this is taking and molding stupidity and weaknesses in order to achieve outcomes: international conflict and weakening America on the world stage with both its allies and adversaries. Not outright commanded by foreigners but shaped by them taking advantages of the post-9/11 fear and general stupidity and anti-intellectualism and fear of immigration.
by esbranson | 2026-02-07 21:15:59+00:00
It's a lagging indicator meant to credit or discredit administrations for past administrations' actions, handpicked to obfuscate cycle capture. CES is backward-looking by definition, so it is being abused here.

Also think of average populations under constant growth, as under Obama and Trump I pre-COVID: Trump's average would be higher in absolute terms than Obama, despite no fundamental change, and Biden higher still, and Trump II higher yet. Absolute populations and jobs go hand in hand. Averages without normalization are statistical theater.

Us Wikipedians have done a poor job on the federal statistical system (FSS or NSS), and this one of many results, this HN thread. I am working on it with the help of chat bots, but progress is slow given my focus on US healthcare and welfare systems. Fundamental laws have been documented, but the actual systems they enable are poorly documented.
by godelski | 2026-02-07 21:16:04+00:00
> it's still just six months away

Reminds me of another "just around the corner" promise...[0]

I think it is one thing for the average person to buy into the promises but I've yet to understand why that happens here. Or why that happens within our community of programmers. It is one thing for non-experts to fall for obtuse speculative claims, but it is another for experts. I'm excited for autonomous vehicles, but in 2016 is was laughable to think they're around the corner and only 10 years later does such a feat seem to start looking like it's actually a few years away.

Why do we only evaluate people/claims on their hits and not their misses? It just encourages people to say anything and everything, because eventually one will be right. It's 6 months away because eventually it will actually be 6 months away. But is it 6 months away because it is actually 6 months away or because we want it to be? I thought the vibe coder's motto is "I just care that it works." Honestly, I think that's the problem. Everyone care's about if it works or not and that's the primary concern of all sides of the conversation here. So is it 6 months away because it is 6 months away or is it 6 months away because you've convinced yourself it is 6 months away. You got good reasons for believing that, you got the evidence, but evidence for a claim is meaningless without comparing to evidence that counters the claim.

[0] https://en.wikipedia.org/wiki/List_of_predictions_for_autono...
by jjav | 2026-02-07 21:16:16+00:00
The claim at the top of the thread was "essentials being a 30-45m drive away".

I clicked on each of those links and asked for directions to food shops and in every case google maps gave me a route less than 10 minutes drive.

So I remain unconvinced that suburbs with "essentials being a 30-45m drive away" are somehow a common thing. You need to go pretty far off into the boonies for that to be the case but then it is no longer a suburb.
by josephg | 2026-02-07 21:16:40+00:00
Yeah I’m having a similar experience. I’ve been wanting a standard test suite for JMAP email servers, so we can make sure all created jmap servers implement the (somewhat complex) spec in a consistent manner. I spent a single day prompting Claude code on Friday, and walked away with about 9000 lines of code, containing 300 unit tests for jmap servers. And a web interface showing the results. It would have taken me at least a week or two to make something similar by hand.

There’s some quality issues - I think some of the tests are slightly wrong. We went back and forth on some ambiguities Claude found in the spec, and how we should actually interpret what the jmap spec is asking. But after just a day, it’s nearly there. And it’s already very useful to see where existing implementations diverge on their output, even if the tests are sometimes not correctly identifying which implementation is wrong. Some of the test failures are 100% correct - it found real bugs in production implementations.

Using an AI to do weeks of work in a single day is the biggest change in what software development looks like that I’ve seen in my 30+ year career. I don’t know why I would hire a junior developer to write code any more. (But I would hire someone who was smart enough to wrangle the AI). I just don’t know how long “ai prompter” will remain a valuable skill. The AIs are getting much better at operating independently. It won’t be long before us humans aren’t needed to babysit them.
by tines | 2026-02-07 21:17:04+00:00
For me, the whole goal is to achieve Understanding: understanding a complex system, which is the computer and how it works. The beauty of this Understanding is what drives me.

When I write a program, I understand the architecture of the computer, I understand the assembly, I understand the compiler, and I understand the code. There are things that I don't understand, and as I push to understand them, I am rewarded by being able to do more things. In other words, Understanding is both beautiful and incentivized.

When making something with an LLM, I am disincentivized from actually understanding what is going on, because understanding is very slow, and the whole point of using AI is speed. The only time when I need to really understand something is when something goes wrong, and as the tool improves, this need will shrink. In the normal and intended usage, I only need to express a desire to achieve a result. Now, I can push against the incentives of the system. But for one, most people will not do that at all; and for two, the tools we use inevitably shape us. I don't like the shape into which these tools are forming me - the shape of an incurious, dull, impotent person who can only ask for someone else to make something happen for me. Remember, The Medium Is The Message, and the Medium here is, Ask, and ye shall receive.

The fact that AI use leads to a reduction in Understanding is not only obvious, but also studies have shown the same. People who can't see this are refusing to acknowledge the obvious, in my opinion. They wouldn't disagree that having someone else do your homework for you would mean that you didn't learn anything. But somehow when an LLM tool enters the picture, it's different. They're a manager now instead of a lowly worker. The problem with this thinking is that, in your example, moving from say Assembly to C automates tedium to allow us to reason on a higher level. But LLMs are automating reasoning itself. There is no higher level to move to. The reasoning you do now while using AI is merely a temporary deficiency in the tool. It's not likely that you or I are the .01% of people who can create something truly novel that is not already sufficiently compressed into the model. So enjoy that bit of reasoning while you can, o thou Man of the Gaps.

They say that writing is God's way of showing you how sloppy your thinking is. AI tools discourage one from writing. They encourage us to prompt, read, and critique. But this does not result in the same Understanding as writing does. And so our thinking will be, become, and remain vapid, sloppy, inarticulate, invalid, impotent. Welcome to the future.
by bornfreddy | 2026-02-07 21:17:22+00:00
It might be "better unix" (whatever that means), but it sure as hell is not better. Locked down, buggy, and difficult / impossible to navigate by keyboard. And I need to install (and trust) a 3rd party app to get a multi value clipboard? Yeah right, better. I'd prefer Windows, and I'm not fan of the ad-OS either.
by thot_experiment | 2026-02-07 21:18:01+00:00
I cannot see myself installing Windows 11, it's sad, I've been primarily a windows guy for my home computer since W95 and I'll miss it. Windows 10 (LTSC) has been the best operating system experience of my life, once I disabled updates and all the nag screens it's been rock solid for me for many years. It's so important to be able to trust that your computer works the same way tomorrow as it does today.

I hope that there's enough people like me that the combined community will keep it alive for a few years longer, but I know eventually something will force me to upgrade to Linux.
by Melonai | 2026-02-07 21:18:06+00:00
At least with regards your second point, Google, DuckDuckGo, all other search engines. I always have to add "golang" because otherwise it just fucks up. I have to say that googling for "C", is a lot more dire, and because the LLVM people called their frontend "clang" I can't even use that, otherwise only clang stuff pops up. And even then, once I did manage to convince the search engine that I'm looking for the programming language, it still decides to just give me results for C++. It sucks.
by owenversteeg | 2026-02-07 21:18:07+00:00
There are a few interesting points in the comments here.

The pro case for getting rid of frameworks: they're bulky, complex, there are security holes, updates to keep up with, things keep changing. LLMs can write you something perfectly customized to what you're doing. You get some free security by obscurity.

The con case: LLMs are excellent at getting you up to speed with a framework and understanding issues. As avidiax says in this thread, "The author seems to mistake having to update Node.js for a security patch to be a curse rather than a blessing. You get the privilege of patching Node.js." Security by obscurity is generally a bad design. To me, the general architecture and maintainability is a huge issue when you have LLMs write everything from scratch. Not that a Node or React app is a paragon of maintainability or architecture, but it's certainly better than something made from scratch by an LLM. The code quality of a framework is also far higher.

I personally feel like the best path today is to use something lightweight, like Svelte. You get the best of both worlds. Light structure but nothing overbearing.
by rirze | 2026-02-07 21:18:26+00:00
Like others are saying, AI will accelerate the gap between competent devs and mediocre devs. It is a multiplier. AI cannot replace fundamentals, at least not a good helmsman with a good rational, detail-oriented mind. Having fundamentals (skill & knowledge) + using AI will be the cheat code in the next 10 years.

The only historical analogue of this is perhaps differentiating a good project manager from an excellent one. No matter how advanced, technology will not substitute for competence.
by pwg | 2026-02-07 21:18:26+00:00
> I take about 60 sec per crimp, and I don't have the exact tools in this guide

What tool(s) do you have?

> Buy better crimp tools

This is most likely your better path forward (as even if you go with pre-crimped, unless you can get all custom wires pre-crimped on both ends you'll likely still need to make some crimped ends). And not only "crimp" tools, but also better wire stripping tools (as you do have to strip the wire before you crimp it). The better tools significantly reduce the time needed, and for 15+ crimps per unit, may make a world of difference overall.
by SR2Z | 2026-02-07 21:18:44+00:00
The car will always get stuck every now and then.

This approach has two benefits: it can be unstuck without sending out a physical driver and while collecting training data, and it efficiently lets m humans control n cars with a wide range of acceptable m and n values.

It's intended for the ratio of m:n to smoothly shrink as the software gets better, but m will always be greater than zero.
by prmoustache | 2026-02-07 21:19:13+00:00
This doesn't make any sense as there is not a linux desktop but multiples and the major ones have been less buggy than windows for the most part of the last 20 years.

Hardware support is where Linux used to struggle. Nowadays things aren't perfect but much better. Basically it means you need to figure out which hardware to buy based on available support, before making the purchase.
by samiv | 2026-02-07 21:19:13+00:00
"creativity involved in deciding what to build, with the choice informed by engineering experience (the project/value will not be obvious to everyone) will allow differentiation."

How? Anyone upon seeing your digital product can just prompt the same thing in no time. If you can prompt it, I can prompt it and so can a million other people.

Nobody whether an individual or business holds any uniqueness or advantage to themselves. All careers and skill sets are leveled and worthless. Implementation skills are worthless. Creativity is worthless.

The only valuable thing is data.
by leoedin | 2026-02-07 21:19:32+00:00
What makes Linux not an option? Is there specific apps you need to use? Or IT policies? Or something else?

The company I work for got bought by a big conglomerate, and I managed to stubbornly hold out using Linux for a really long time. It turns out if your workplace has adopted “Bring your own device” type policies, that often means you can auth with enough services that working on Linux is feasible.
by not_a9 | 2026-02-07 21:20:04+00:00
Reminder the company had to spend time and money to get an EV cert and endured Microsoft’s nine circles of driver signing hell to ship this beauty.

Meanwhile they could have used EAC for free (with weaker protection than Rust/Apex/Fortnite, mind you, but still) which would both provide better game security and not be a vulnerable driver (until proven otherwise - and I’m not seeing a lot of proof despite any anticheat driver being reverse engineer targeted to hell and back)
by codexon | 2026-02-07 21:20:06+00:00
This paper creates a new benchmark comprised of real remote work tasks sourced from the remote working website Upwork. The best commercial LLMs like Opus, GPT, Gemini, and Grok were tested.

Models released a few days ago, Opus 4.6 and GPT 5.3, haven't been tested yet, but given the performance on other micro-benchmarks, they will probably not be much different on this benchmark.
by raw_anon_1111 | 2026-02-07 21:20:07+00:00
Yes I’m sure your anecdotal bubble is more statistically valid than telling a 22 year old if they have a choice between working at BigTech making $160K+ a year or work in government and make $70K, they are going to choose to work for the government.

Myself personally, I worked on the other side of the consulting - government divide. I saw a lot more people jump on the consulting side than the government side. I never heard one person say “I would love to take a 40% cut in pay and go into the office and deal with government shut downs. Sign me up!

But why in the heck would anyone want to work for a government that constantly insults them, forcing RTO and making people move to South (where I am from).
by slye514 | 2026-02-07 21:20:17+00:00
I built an inference-time method that reduces LLM hallucination by applying
toroidal geometric constraints to logit outputs. No retraining, no fine-tuning —

it works as a plug-in on existing models.

Results on Qwen 2.5-0.5B-Instruct:
• 40% error reduction on factual tasks
• +6.8% absolute improvement on TruthfulQA
• Random/non-toroidal baselines show no effect

The math comes from the Tonnetz — the same toroidal manifold that describes
harmonic relationships in music theory. Periodic boundary conditions on a 2D
torus create structured long-range coherence and a spectral gap that filters
noise from the logit distribution.

Try it: https://huggingface.co/spaces/paraxiom-research/topological-coherence
Paper: https://doi.org/10.5281/zenodo.18516477
Code: https://github.com/Paraxiom/topological-coherence

Rust crate: https://crates.io/crates/topological-coherence
Total compute cost to validate: $40.
by fluoridation | 2026-02-07 21:20:30+00:00
Re-read what I said.

>People starving en masse [...] despite there being plentiful food

Not "despite there being plentiful food production capacity". No, it has never happened that people starved in great numbers while the food stores were replete. That's a fantastical scenario. Famines only happen when there is no food, or no food nearby. Nature abhors a vacuum, so if you have hungry people on one side of a wall and food on the other, the wall will tend to become permeable until equilibrium is achieved. Money and violence (or aversion to it) are not factors in that equation.
by tombert | 2026-02-07 21:20:34+00:00
I've been writing a good chunk of C lately for some stuff that has some relatively high memory constraints (lower than I could squeeze out of GraalVM).

I know I could do C++, and you could argue that's better, but I find C++ to be exceptionally irritating to use. Every time I've used C++ I get people telling me I'm using it "wrong", sometimes in contradictory ways. Sometimes I should use a "friend" function, sometimes "friend functions are evil". Sometimes multiple inheritance is fine, sometimes it should be avoided like the plague. Sometimes you should "obviously" use operator overloading, sometimes you should avoid it because it's confusing because you don't know which functions are being called.

I'm sure someone here can "educate" me with the best practices for C++, and maybe there will be some reasoning for it, but ultimately I don't really care. I just found the language annoying and I don't enjoy using it. I know that I could "just write it mostly like C and use the C++ features when I need it", but I have just found that I have more fun thinking in pure C, and I've kind of grown to enjoy the lack of features.

Maybe it's just a little bit of masochism on my end, but I like the fact that C gives you so little. You kind of have to think about your problem at a very fundamental and low level; you have to be aware of how memory is allocated and deallocated, you don't get all these sexy helper functional-programming constructs, strings aren't these simple automatic dynamic things that you have in basically every other language. You have a dumb, simple language that will give you exactly what you need to write programs and very little else.

Most stuff I write uses a garbage collector, but the safety and easy of writing stuff with garbage collectors like Java makes it very easy to be lazy. I've grown to appreciate how much C makes you actually think about problems.
by pvtmert | 2026-02-07 21:20:58+00:00
With the current scale and speed, it is not yet viable to make N+1 calls to other models with specific prompts. (Or even calling multiple fine-tuned models)

However, even Google (and others) admit(s) that some sort of prompt-injection is always possible, hence out-of-scope for bug-bounty programs.

There are only 2 ways to fix this;

1. Either we ask multiple models with multiple system prompts to validate both inputs, processing, and outputs, then showing results to the user. Possibly making these kind of indirect attacks 2x-3x or Nx more difficult. (ie. Specialized checks and post-processing of the output of original model)

Note that this is linearly-scalable, looking like a *nix shell (bash) pipeline as such: `input-sanitizer-llm | translation-llm | output-sanitizer-llm | security-guard-llm`

2. I do not want to say "tiny LLMs" as the term itself is silly, but essentially finding a similar but different architecture to utilize transformers & language-relationship parts to create one-to-one models that are specialized for certain jobs.

Currently we use "General knowledge" LLMs and trying to "specialize" their output, this is inefficient overall as you have bunch of unnecessary things encoded in it, which are causing either hallucinations or these kinds of attacks. Meanwhile, an LLM with no information about some other unnecessary things besides the task it was trained for would be much better and safer. (WIthout requiring linear scaling of point#1)

I also believe that the tokenizer will require the most work to make point #2 possible. If point #2 becomes even a slight reality, capacity constraints will drop significantly yielding much higher efficiency for those agentic tasks.
by tuhgdetzhh | 2026-02-07 21:21:09+00:00
I think the productivity question hinges on what you count as the language versus the ecosystem. Very few nontrivial games are written in "just C". They are written in C plus a large pile of bespoke libraries, code generators, asset pipelines, and domain-specific conventions. At that point C is basically a portable assembly language with a decent macro system, and the abstraction lives outside the language. That can work if you have strong architectural discipline and are willing to pay the upfront cost. Most teams are not.

I agree on C++ being the worst of both worlds for many people. You get abstraction, but also an enormous semantic surface area and footguns everywhere. Java is interesting because the core language is indeed small and boring in a good way, much closer to C than people admit. The productivity gains mostly come from the standard library, GC, and tooling rather than clever language features. For games, the real disagreement is usually about who controls allocation, lifetime, and performance cliffs, not syntax.
by doublerabbit | 2026-02-07 21:21:16+00:00
What blew my mind was how most of the food industry is pretty much owned by about eight corporations.

https://s3.amazonaws.com/oxfam-us/www/static/media/files/Beh...

Chances are you're still buying Nestle. You can check here.

https://www.boycottbuddy.app