MurphyA/hacker-news huggingface dataset:
by theyregr8 | 2026-02-04 13:39:07+00:00
This only makes sense to YC, to try and prop up interest in digital assets they heavily inveterate in.

The majority of humans are losing interest in digital ephemera South Park-WoW guys are desperate sell them on, otherwise South Park-WoW guy might have to work to live not just shill hallucinations like a priest.
by sidewndr46 | 2026-02-04 13:39:20+00:00
This isn't really accurate. The Northern Alliance entered into an agreement with the US to secure the country. An insurgency sprang up and we fought it for 20 years before giving up. Since this is now after the fact, we can safely say the Taliban ran the insurgency the whole time.

The Taliban are a military and political group compromised of an ethnic minority in Afghanistan. It's not even that the US lost to "goat herders with guns". We failed to secure a small country against a well organized, armed minority.
Show HN: Diffnote – Browser-based document diff tool with no server uploads
by vivajayyy | 2026-02-04 13:39:31+00:00
I built a web-based document comparison tool where all file parsing and diffing happens entirely in the browser.
The idea came from watching non-technical coworkers struggle to compare document versions — manually reading two files side by side or fighting with Word's Track Changes.
Technical details:

PDF parsing via pdf.js, DOCX via mammoth.js — all client-side
Diff engine: Google's diff-match-patch
Line, word, and character-level comparison
Next.js 15 + TypeScript, deployed on Vercel

No files ever leave the browser. No signup required.
Site: https://diffnote.net
Product Hunt: https://www.producthunt.com/products/diffnote?launch=diffnot...
by TaupeRanger | 2026-02-04 13:39:32+00:00
If that's the case, then business results should get worse, and management should notice this. If business results don't get worse, then either 1) it's actually more than 60% as good, or 2) it doesn't matter to the business's bottom line that the result is only 60% as good instead of 80% as good, and management made the right decision.
by direwolf20 | 2026-02-04 13:40:01+00:00
That relies on a third party to maintain the value of the currency. Maybe I'd prefer to minimise my dependence on third parties. The crypto ecosystem makes it much easier to trade six cows for two tons of lumber and offload all of the exchange risk to speculators. It still can't enforce the physical exchange of goods, but it can atomically negotiate a swap from anything to anything through as many intermediaries as required. With a suitable transaction fee — which may come out of the transaction inputs.

A cryptocurrency system can negotiate that my six cow NFTs (which are not jpegs, I guarantee they are exchangeable for cows) for two Ethereum, of which 0.05 is taken as a fee and 1.95 flows on to Uniswap to buy Home Depot coin which buys two tonnes of lumber at a specific location and time. Except oh dear — Home Depot only trades on Polygon. Well then my 1.95 ether is bridged to Polygon where my 1.94 wrapped ether is traded for 9999999 POL and then for Home Depot coins. Or I buy wrapped Home Depot coins atomically on Ethereum and then unwrap them back to Polygon.

Crucially it all happens automatically.

That infra doesn't exist since cows and lumber aren't being traded on a blockchain, but it's the kind of thing that could be enabled.

Since I only hold ETH, WETH and POL during the transaction, their absolute value doesn't matter.
by longtermop | 2026-02-04 13:40:03+00:00
The meta-problem ("who watches the watcher?") is real, but I think the framing shapes the answer. If you're building a second AI to monitor the first, you've just doubled your attack surface.

The more tractable approach IMO is focusing on input validation. The primary attack vector for agentic AI isn't the model going rogue—it's prompt injection through tool outputs, RAG results, API responses, and external content. The model follows instructions; attackers craft instructions that look like legitimate data.

We're building something for this at Aeris (PromptShield)—lightweight guardrails that scan inputs before they reach the model. Think of it less as "watching the AI" and more like input sanitization in traditional security. You wouldn't let untrusted data hit your database without validation; same principle applies to LLM context windows.

Curious whether people think the "watcher" needs to be an AI at all, or if deterministic/rule-based scanning catches the majority of attack patterns?
by SPICLK2 | 2026-02-04 13:40:14+00:00
You need to state your premise to enable a reasonable discussion. I've been talking about energy or fuel efficency when it comes to public transport (I see you don't have any return for this, because the facts are indesputible).

However, your premise is that "people must use (I assume, electrified) HSR to stop burning oil". This is an entirely different discussion. In many ways, it is significantly less efficient when looking purely at an energy usage perspective, especially when considering new routes across sparsely-populated expanses with relatively low demand.
by notepad0x90 | 2026-02-04 13:40:17+00:00
Many times, the really hard problems that I ask AI to solve, it solves it not so well, and that just makes me more frustrated. If you're building that just need to barely work, that's one thing. if you need things to work securely, scale, and be really efficient, I don't see how AI changes things. To the contrary, it might spit out test-cases and sample code to test your hypothesis with, saving you time and frustration, letting you focus on the architecture and problem solving.

I think perhaps moving the goal posts to demand better quality and performance might force people who rely on AI to "think hard". Like your app works fine, now make it load in under a second on any platform.
by INTPenis | 2026-02-04 13:41:05+00:00
I don't. I miss being outside, in the sun, living my life. And if there's one thing AI has done it's save my time.

I'm not sure how you live and work in the US, but here in Sweden, in my experience, it's more focused on results than sitting at your desk 9-5.

So AI does enable me to take more free time, be outside more when the sun is out, because I finish my tasks faster.

I'm just afraid that managers will start demanding more, demand that we increase our output instead of our work life balance. But in that case I at least have the seniority to protest.
by delecti | 2026-02-04 13:42:14+00:00
I can't find the detailed breakdown for 2025, but in 2024, they took in $308bn in premiums and paid out $264bn in medical costs. So even ignoring all of the downstream and systemic problems caused by insurance existing as a for-profit entity, they're taking 14% off the top just to exist as a middle-man.

https://www.unitedhealthgroup.com/content/dam/UHG/PDF/invest...
by damnitbuilds | 2026-02-04 13:42:22+00:00
"
We assume, as we think Turing would have done, that humans have general intelligence. [...]

A common informal definition of general intelligence, and the starting point of our discussions, is a system that can do almost all cognitive tasks that a human can do.
"

So that's: "We assume humans have general intelligence, general intelligence is defined as what humans have."

How many experts did it take to produce this ?
by lee_ars | 2026-02-04 13:43:10+00:00
> Have you had to go back and fix any of your vibe coded projects yet?

Not yet, but you're absolutely right. Once a tool like this stops being front of mind, it'll fall right out of my head. It's a bit like driving somewhere versus being driven—I'm a lot more likely to remember how to get to a place if I have to actively navigate to it. If I'm in the passenger seat, all bets are off!
by itay-maman | 2026-02-04 13:43:12+00:00
This is appealing to me on several fronts—I like the focus on simplicity and local-first markdown files. Quick thought capture feels essential for staying productive these days.

But a screen recording would really help, since some of the descriptions are too vague to understand the actual workflow. For example, what does "You don't even have to open the file to jot down your notes" mean in practice?
by fix4fun | 2026-02-04 13:43:52+00:00
667 - “fax number of the beast” - that was funny ;)
The thing about mathematics is that it can tickle your brain - in a creative way.

It's becoming increasingly difficult these days, with so many things competing for your attention and "brain-deadening" you. It was a wonderful thing to be bored and play around with math. My favorite moments were the epiphany - that there is some hidden connection between math areas or something got new meaning.
by trashb | 2026-02-04 13:43:58+00:00
> isn't this fair?

We are talking about hear say anecdotal evidence from some influential people in the industry. The people mentioned in the comment I responded to have influence to organize certain research. Some measurements (even if not ideal) can point to 20x vs 0.1x speedup differences at least.

I indicated that there is at least some research pointing that developers (experienced or not) often overestimate the gains of using AI. There are a lot of other things that may prompt people to say things regarding emergent industries, for example investments into the AI industry.

I am interested if the claims are real or perhaps overstated. Therefore I asked what kind of information this is based on. This is how science works compared to marketing claims. Hypothesis lead to experiments that result in measurements that lead to a conclusion.

But as of now I still didn't even get a link to the statements supposedly made by these influential developers, this is the rhetoric with a lot of claims around AI especially. And therefore I am still skeptical about such claims until I see some concrete evidence.

So I would say yes it is fair to ask if they measured their results to back up their claims, especially if they are influential developers.
by derverstand | 2026-02-04 13:43:58+00:00
You’re fair to call out the wording. I agree some of it reads more buzzword-y than intended.

My point wasn’t that thinking fast is inherently good or that coding is “drag.” Quite the opposite: the friction of implementation used to be a form of thinking time for me. Typing forced pacing and reflection.

What I’m noticing now is that when iteration becomes extremely cheap, the bottleneck shifts from “can I build this?” to “should I build this?” That’s not about hyperactivity. It’s about decision quality.

The “dopamine” part wasn’t meant as a brag but as a caution. Fast feedback loops can encourage shallow iteration instead of deeper design if you’re not careful.

So if anything, I’m arguing for more deliberate thinking, not less.
by Nevermark | 2026-02-04 13:44:20+00:00
You can’t extract energy from heat by itself. Only from a heat delta.

Think of heat like flowing water or charge. Only an altitude or voltage delta creates the flow needed to harvest energy.

You get no useful energy from heat you are already trying to shed because you have no delta to work with. (The entire problem exists because there is no surrounding environment with high heat capacity and lower heat.)
by a13o | 2026-02-04 13:44:27+00:00
I’ve given these sorts of haystack search struggles completely over to the LLM. Whether it’s finding a bug in code or searching documentation for the answer, I view it as a near-obsolete skill. The past couple of decades it was important to know how to chase down documentation and zero in on the one line of config you were missing. Now it’s not.

I don’t view this as a hollowing out of my skill tree, I view it as freeing myself to focus on modern skills I need to develop. Such as learning how to steer LLM context windows towards maintainable solutions in large codebases.

I’m sure I’ll be thankful now and then that I know how to manually sift through stack traces for answers. But I expect those moments to be rarer and rarer. I basically never look at machine code, but I bet that used to be an important skill for programmers many decades ago.
by adrian_b | 2026-02-04 13:44:42+00:00
Keyboards with Hall effect switches have been frequently used many decades ago, before personal computers became dominant.

They were typically used in the more expensive models of video terminals that were used together with minicomputers or mainframes.

Personal computers used cheaper keyboards, to minimize the cost, so after everybody switched to using PCs the more expensive but better keyboards with Hall effect sensors have disappeared.

The keys with Hall effect sensors contain a special analog integrated circuit instead of metallic contacts. The IC is packaged similarly with a transistor, having 4 or sometimes only 3 pins that are soldered on the keyboard PCB.

So to make this kind of keyboard, you need a vendor for such an integrated circuit. Semiconductor IC vendors do not make such ICs, unless there is a market big enough for them.

During the seventies and the eighties, most IC vendors had such ICs in their catalog, but when the market for expensive keyboards disappeared, the production of such ICs has also stopped.

This has made more difficult for anyone to start making such keyboards, instead of other kinds of keyboards, because they must bet on selling enough of them, to be able to convince an IC vendor to make a batch of such ICs.

I have not seen any modern keyboard with Hall effect sensors, so I do not know whether they really use the kind of sensors made for keyboards that have been used originally. Perhaps they repurpose Hall sensors made for brushless DC motors, which are easily available anywhere, but they might need some additional external components in comparison with the special keyboard sensors.
Show HN: TinyFn – Your agent sucks at math
by tacoooooooo | 2026-02-04 13:44:59+00:00
I built TinyFn because I kept watching AI agents confidently get basic things wrong — math, string counting, unit conversions, validations. The classic "how many R's in strawberry" problem, but across hundreds of utility tasks.

TinyFn is a collection of 500+ deterministic utility endpoints (math, string ops, hashing, validation, conversions, etc.) that AI agents can call via MCP instead of guessing. (Also works as a plain REST API). Think of it as offloading the stuff you wouldn't ask a human to do in their head either.

I'd love feedback on which tool categories are most useful, and what's missing. Happy to answer any questions.
https://tinyfn.io
How do you manage context/memory across multiple AI tools?
by arapkuliev | 2026-02-04 13:45:12+00:00
I'm curious how others are handling this: I use Claude for some tasks, Cursor for coding, ChatGPT for research, and Perplexity for quick lookups.

The problem is none of them know what I've discussed with the others.

I find myself re-explaining the same context repeatedly, or copy-pasting from Notion docs.

For those of you heavily using AI tools:

- How are you managing shared context across tools?

- What's your current workflow for keeping AI "memory" consistent?

- Have you found any solutions that work well?

Especially interested in hearing from teams where multiple people need to access the same knowledge base across different AI sessions.
by exogen | 2026-02-04 13:45:13+00:00
It would be possible to have it decode the .dts and .dif formats on demand - that was my original plan - just much less efficient, as the .glb files are about 1/5 of the file size on average. (I also assume glTF loading/rendering has had a lot more optimization work put into it than what I'd be able to accomplish.) For these reasons it seemed more productive to have it work on the Blender addons as a starting point rather than JavaScript/TypeScript parsers for the original formats.

Some of the custom features you may be referring to I implemented as custom properties in the glTF output - like surface flags. "Outside Visible" is one example, it's a flag baked into each .dif surface that determines whether rays can reach it from the outside, so the engine knows whether to apply the map's directional sunlight, or just ambient and light map lighting. So, even though it technically could try to render with modern PBR, dynamic lighting/shadows and all that, it instead renders as close to the original as possible using the same (or similar) techniques. Comparing screenshots with actual Tribes 2 renders is often indistinguishable unless you really know what to look for!
by mtlynch | 2026-02-04 13:45:25+00:00
Congrats on launching your first 500 units!

I had a similar experience. I quit my job as a SWE at Google and built a hardware product on top of the Raspberry Pi.[0]

I don't really have anything helpful to add, but I relate a lot to all of the gotchas you encountered. Shipping a hardware product made me appreciate software so much more, especially SaaS products where you can ship a fix immediately.

With hardware, it's painfully easy to make a mistake and not realize it for 3-6 months. And by that point, you have this whole manufacturing pipeline you have to halt and unwind. And with overseas manufacturing, tariffs, and shipping costs, you can't even unwind some of this stuff, and you just end up with useless material that you paid 5-6 figures for.

We're definitely spoiled in the software world with the relative ease of fixing bugs.

[0] https://news.ycombinator.com/item?id=23927380
by DoctorOW | 2026-02-04 13:45:37+00:00
This is the problem to me with AI generated blog posts for AI code projects. Neither the AI that wrote this post, nor the human that copy/pasted it have necessarily read through the actual code to see what it does. One LLM got a paragraph and tried to write code, another tried to write a blog post. We cross our fingers and hope that the two match I guess.
by bosterhaus | 2026-02-04 13:45:52+00:00
Location: Dubai, UAE (USA National)
Remote: Yes
Willing to relocate: No
Technologies: Javascript/TypeScript, Node.js, React, Go, Java, CLI Tooling, Developer Experience
Résumé/CV: https://bryceosterhaus.com/cv.pdf
Email: bryceosterhaus@gmail.com

Software Engineer with over a decade of experience. Passionate about building developer tools and designing systems that make developers faster, reduce friction in workflows, and enable scalable, reliable product delivery.
by wongarsu | 2026-02-04 13:46:21+00:00
I have a hall-effect keyboard from Wooting, and they are indeed excellent. Very reliable, and setting the trigger point in software/firmware allows a number of interesting features like triggering different key codes depending on how far you've pressed the key down, enabling more rapid keypresses or using keys as analog input.

Their first keyboards actually used optical switches, and from everything I've heard were less reliable, and tracking precision was much worse than with the magnetic switches
by raw_anon_1111 | 2026-02-04 13:46:21+00:00
Yep, just these past the weeks. I tried to reuse an implementation I had used for another project, it took me a day to modify it (with Codex), I tried it out and it worked fine with a few hundred documents.

Then I tried to push through 50000 documents, it crashed and burned like I suspected. It took one day to go from my second more complicated but more scalable spec where I didn’t depend on an AWS managed service to working scalable code.

It would have taken me at least a week to do it myself
Show HN: Tearoff – tear-off flyers for the internet
by marcomezzavilla | 2026-02-04 13:46:26+00:00
Hey HN,

I'm a solo dev and I built this mostly because I thought it would be fun to make.

Tearoff brings the classic paper flyer with tear-off tabs to the internet. Create a digital flyer, add tabs with discount codes, hidden messages, access links, or contact info, and share it as a single link. When someone grabs a tab, it's gone for everyone.

I built it because I always liked the physicality of those "guitar lessons" flyers you see on city walls, and I wanted to see if that scarcity mechanic could work digitally.

I'd love feedback, especially if you can think of use cases I haven't considered. What would you put on a digital tear-off flyer?

Demo: https://tearoff.app/f/01kgme131hneq659tcc38gcz7j
by Gud | 2026-02-04 13:46:35+00:00
Yeah, typically people don’t understand the point of Marx at all.

He saw capitalism as a natural and necessary step before developing communism.

Hence why most criticism of soviet and Chinese communism is fundamentally flawed, since they tried to develop communism in feudal societies.

FWIW I am libertarian leaning, but it is obvious to me capitalism has obvious defects that must be either compensated for, or be done away with entirely.
by skywhopper | 2026-02-04 13:46:54+00:00
All of those “huge overheads” you cite are nothing compared to the huge overhead of building and fueling rockets to launch the vibration- and radiation-hardened versions of the solar panels and GPUs and cooling equipment that you could use much cheaper versions of on Earth. How many permitted, regulated launches would it take to get around the one-time permitting and predictable regulation of a ground-based datacenter?

Are Earth-based datacenters actually bound by some bottleneck that space-based datacenters would not be? Grid connections or on-site power plants take time to build, yes. How long does it take to build the rocket fleet required to launch a space “datacenter” in a reasonable time window?

This is not a problem that needs to be solved. Certainly not worth investing billions in, and definitely not when run by the biggest scam artist of the 21st century.
by Cthulhu_ | 2026-02-04 13:47:32+00:00
I really think the standards for review have lowered, or, they're more spot check or based on whoever reviews them these days, with different layers of seniority in reviewers.

For example, we had an app that was fine for years, but one day it was rejected because it didn't have an offline-available privacy policy readable without logging in (or something to that effect). Another time it was suddenly rejected because we released an update to two whitelabel apps (mostly same app, different brands) simultaneously; we had to find higher-ups to vouch that they were in fact different brands and that it was OK and not some kind of copycat.
by csummers | 2026-02-04 13:47:38+00:00
I definitely identify with the "Thinker" described in this post, but I am routinely mulling over ideas and problems (multiple hours, days, and weeks) with the help of LLMs now.

One of the benefits of LLM usage is to figure out the boundaries of your own knowledge and that of humanity's existing knowledge--at least for the LLM's training data.

Enumerating through existing options and existing solutions to problems gets you to the knowledge boundary sooner--where the real work begins! While faster with LLMs, I don't see this process as much different than bouncing ideas off of colleagues (and critiquing your own thoughts).

However, the difference is likely human's unpredictable ability to apply creativity throughout the process...such that a new solution may arise at any point and leap-frog existing solutions/explanations. (Think Einstein taking known data from Lorentz, Michelson, Morley plus Maxwell's equations on light and coming up with special relativity.)
Show HN: Lazyactions – Terminal UI for GitHub Actions
by tokkyokky | 2026-02-04 13:47:48+00:00
Hi HN,

I built this because I got tired of the browser round‑trip every time I pushed code.

Push → open browser → Actions tab → wait → find workflow → check status. Repeat dozens of times a day.

Lazyactions is a lazygit‑style TUI for GitHub Actions so you can stay in the terminal. Browse workflows, watch logs as they update, and trigger/cancel/rerun jobs. Vim keybindings and mouse support.

Built with Go and Bubble Tea. Uses your existing gh auth (or GITHUB_TOKEN).

brew install nnnkkk7/tap/lazyactions

Repo: https://github.com/nnnkkk7/lazyactions

It’s a bit rough but usable. Feedback welcome—especially on what’s annoying or missing.