MurphyA/hacker-news huggingface dataset:
by rlpb | 2026-02-05 19:46:08+00:00
> It needs to be fast-updating for shared multi-user docs, like Google Docs/Sheets or Word/Excel 365.

In my experience, Google Docs has this, but realtime collaboration with Wors is unusable. Which is interesting, because that means a huge number of existing Office 365 users have yet to experience it.

I wonder if there's an opportunity there.
by bityard | 2026-02-05 19:46:23+00:00
If it works anything like the memories on Copilot (which have been around for quite a while), you need to be pretty explicit about it being a permanent preference for it to be stored as a memory. For example, "Don't use emoji in your response" would only be relevant for the current chat session, whereas this is more sticky: "I never want to see emojis from you, you sub-par excuse for a roided-out spreadsheet"
by toomuchtodo | 2026-02-05 19:46:31+00:00
I'm in several Slack teams for non profits and professional orgs, Teams for a client or two, IRC and Matrix servers for digital archiving ops, Signal/WhatsApp/GroupMe/Telegram groups, etc. I have been in tech for 25+ years, I am familiar with the extremes. You are right, things can be bad, that is the point of systems engineering: to drive directionally towards continual improvement. Success is never assured, but throwing our hands up and giving up is not reasonable. Make a plan, work the plan. Default to action. Work is hard.

I recommend "Thinking in Systems" by Donella H. Meadows (ISBN13 9781603580557) on this topic [1]. It's ~$10 on Amazon as of this comment, and the PDF is easy to find with a quick web search.

[1] https://openlibrary.org/works/OL3737036W/Thinking_in_systems
by axus | 2026-02-05 19:46:38+00:00
Whenever there's a mystery, apply the scientific method to investigate it. Form a hypothesis, an experiment or test , then record the results and check if they support.

Hypothesis: CIA is hacking reporters to determine their government sources.

If we start seeing more government sources exposed, we haven't proven it but it supports the hypothesis.

Hypothesis: State election systems are being compromised for federal monitoring and control.

If we start seeing more improbably results, that is support for the hypothesis.
by cxr | 2026-02-05 19:46:39+00:00
> the charter of projects like LibreOffice are fundamentally broken—they're aiming to replace Microsoft Office by cloning it, but Microsoft Office itself is part of a busted paradigm

<https://news.ycombinator.com/item?id=24759573>

> The LibreOffice project's imprimatur should be to stop existing[…] The editing paradigm perpetuated by the legacy of MS Office is a dead end.

<https://news.ycombinator.com/item?id=23795918>

I'll amend my previous position and say that the charter should be to (a) as much as possible change the menu and dialog structure to match whatever the last "good" version of the Microsoft Office UI was, but still ultimately focus on (b) doing everything I said in those other comments.
by StephenHerlihyy | 2026-02-05 19:47:08+00:00
I don’t use OpenAI too much, but I follow a similar work flow. Use Opus for design/architecture work. Move it to Sonnet for implementation and build out. Then finally over to Gemini for review, QC and standards check. There is an absolute gain in using different models. Each has their own style and way of solving the problem just like a human team. It’s kind of awesome and crazy and a bit scary all at once.
by NitpickLawyer | 2026-02-05 19:47:12+00:00
> Prove this statement wrong.

If all it takes is "trained on the Internet" and "decompress stored knowledge", then surely gpt3, 3.5, 4, 4.1, 4o, o1, o3, o4, 5, 5.1, 5.x should have been able to do it, right? Claude 2, 3, 4, 4.1, 4.5? Surely.
by falcor84 | 2026-02-05 19:48:10+00:00
To the best of my knowledge, there's no Rust-based compiler that comes anywhere close to 99% on the GCC torture test suite, or able to compile Doom. So even if it saw the internals of GCC and a lot of other compilers, the ability to recreate this step-by-step in Rust is extremely impressive to me.
by AnthonyMouse | 2026-02-05 19:48:39+00:00
In those days they did this by having physical public spaces for interaction, which we've since priced people out of through artificial scarcity of real estate via zoning laws. And even if people were willing to solve that one, it would take time to actually build new buildings, and doing that would have to be done first.

It's also assuming that we're willing to abandon a technological capacity (not having to personally travel to someone's location to communicate with them) that humans have had since before Moses came down from the mountain, which seems like a fairly ridiculous constraint to impose when there are obviously better alternatives available.
by romperstomper | 2026-02-05 19:48:43+00:00
Oh, I was very wrong, my apologies!

I was sure this one was for Python from 3.7 up to 3.10. But it is still here..
But as for 2026 it will not stay forever as it was supposed to - there are 2 PEPs which are suppose to fix it in Python 3.14 - https://peps.python.org/pep-0649/ and https://peps.python.org/pep-0749/
by Philpax | 2026-02-05 19:48:44+00:00
Great. Did your compiler support three different architectures (four, if you include x86 in addition to x86-64) and compile and pass the test suite for all of this software?

> Projects that compile and pass their test suites include PostgreSQL (all 237 regression tests), SQLite, QuickJS, zlib, Lua, libsodium, libpng, jq, libjpeg-turbo, mbedTLS, libuv, Redis, libffi, musl, TCC, and DOOM — all using the fully standalone assembler and linker with no external toolchain. Over 150 additional projects have also been built successfully, including FFmpeg (all 7331 FATE checkasm tests on x86-64 and AArch64), GNU coreutils, Busybox, CPython, QEMU, and LuaJIT.

Writing a C compiler is not that difficult, I agree. Writing a C compiler that can compile a significant amount of real software across multiple architectures? That's significantly more non-trivial.
by nhecker | 2026-02-05 19:49:12+00:00
I'm genuinely ignorant of how those red teaming attempts are incorporated into training, but I'd guess that this kind of dialogue is fed in something like normal training data? Which is interesting to think about: they might not even be red-team dialogue from the model under training, but still useful as an example or counter-example of what abusive attempts look like and how to handle them.
by fragmede | 2026-02-05 19:49:18+00:00
The people that work at Anthropic are aware of simonw and his test, and people aren't unthinking data-driven machines. How valid his test is or isn't, a better score on it is convincing. If it gets, say, 1,000 people to use Claude Code over Codex, how much would that be worth to Anthropic?

$200 * 1,000 = $200k/month.

I'm not saying they are, but to say that they aren't with such certainty, when money is on the line; unless you have some insider knowledge you'd like to share with the rest of the class, it seems like an questionable conclusion.
by mrandish | 2026-02-05 19:49:31+00:00
> Do we still think we'll have soft take off?

There's still no evidence we'll have any take off. At least in the "Foom!" sense of LLMs independently improving themselves iteratively to substantial new levels being reliably sustained over many generations.

To be clear, I think LLMs are valuable and will continue to significantly improve. But self-sustaining runaway positive feedback loops delivering exponential improvements resulting in leaps of tangible, real-world utility is a substantially different hypothesis. All the impressive and rapid achievements in LLMs to date can still be true while major elements required for Foom-ish exponential take-off are still missing.
by bgirard | 2026-02-05 19:49:40+00:00
> Using the develop web game skill and preselected, generic follow-up prompts like "fix the bug" or "improve the game", GPT‑5.3-Codex iterated on the games autonomously over millions of tokens.

I wish they would share the full conversation, token counts and more. I'd like to have a better sense of how they normalize these comparisons across version. Is this a 3-prompt 10m token game? a 30-prompt 100m token game? Are both models using similar prompts/token counts?

I vibe coded a small factorio web clone [1] that got pretty far using the models from last summer. I'd love to compare against this.

[1] https://factory-gpt.vercel.app/
by StephenHerlihyy | 2026-02-05 19:50:36+00:00
What amazes me the most is the speed at which things are advancing. Go back a year or even a year before that and all these incremental improvements have compounded. Things that used to require real effort to consistently solve, either with RAGs, context/prompt engineering, have become… trivial. I totally agree with your point that each step along the way doesn’t necessarily change that much. But in the aggregate it’s sort of insane how fast everything is moving.
by _se | 2026-02-05 19:50:40+00:00
This entire site is full of idiots confidently spouting nonsense. Probably time to move on. "Don't use Excel for accounting" has to be the dumbest thing I've read in a year, even with all of the LLM bullshit going on.

And that's including the people this morning who are apparently excited for LLMs to file their taxes.
by masfuerte | 2026-02-05 19:50:41+00:00
Right? Each legitimate stream, including the pirate's, includes a unique ID. The content protection company subscribes to the pirate stream, gets the ID, and shuts down the pirate. This works today.

The problem that Sky has is that most premium sports content is available in other countries with less effective copy protection, so that's where the pirate streams originate, and Sky can't do anything about them.

You're right that none of this affects the end-users.
by nananana9 | 2026-02-05 19:50:44+00:00
I've been listening to the insane 100x productivity gains you all are getting with AI and "this new crazy model is a real game changer" for a few years now, I think it's about time I asked:

Can you guys point me ton a single useful, majority LLM-written, preferably reliable, program that solves a non-trivial problem that hasn't been solved before a bunch of times in publicly available code?
by lunar_mycroft | 2026-02-05 19:50:50+00:00
LLMs can regurgitate almost all of the Harry Potter books, among others [0]. Clearly, these models can actually regurgitate large amounts of their training data, and reconstructing any gaps would be a lot less impressive than implementing the project truly from scratch.

(I'm not claiming this is what actually happened here, just pointing out that memorization is a lot more plausible/significant than you say)

[0] https://www.theregister.com/2026/01/09/boffins_probe_commerc...
by pixl97 | 2026-02-05 19:51:16+00:00
>And you're saying that this shouldn't happen because

You have a strange reversal of causality here.

I'm not saying what should or shouldn't happen.

I am describing what has or has not happened.

I am saying that 'insecure' operating systems dominate the market and can be found everywhere.

I need you to explain to me why secure operating systems are somehow going to get users to move from what they are on to your magical platform?

There is no security police that is writing this secure operating system you're talking about, no one to point guns at them and make people use it. No long line of volunteers open sourcing code to make this secure operating system either.

You're describing an OUGHT, I'm describing an IS.
by light_hue_1 | 2026-02-05 19:51:22+00:00
> This was a clean-room implementation (Claude did not have internet access at any point during its development);

This is absolutely false and I wish the people doing these demonstrations were more honest.

It had access to GCC! Not only that, using GCC as an oracle was critical and had to be built in by hand.

Like the web browser project this shows how far you can get when you have a reference implementation, good benchmarks, and clear metrics. But that's not the real world for 99% of people, this is the easiest scenario for any ML setting.
by Revolution1120 | 2026-02-05 19:51:24+00:00
Playing a musical instrument is far more athletic than sports, requires more scientific practice, and is more "competitive." The only difference is the scoring method. Music doesn't test "who can finish playing in the shortest time," but during practice, speeds faster or slower than the original tempo have already been practiced. Sports are about "who can push their limits"; in musical instrument playing, the very act of "practicing a complete, challenging piece" is already a limit. The difference is that it doesn't require pushing further limits.
by pronik | 2026-02-05 19:51:27+00:00
> Right now I can't write spec (or meta-spec) files quick enough to saturate the agent loops, and I can't QA their output well enough... mostly a me thing, i guess?

Same for me, however, the velocity of the whole field is astonishing and things change as we get used to them. We are not talking that much about hallucinating anymore, just 4-5 months ago you couldn't trust coding agents with extracting functionality to a separate file without typos, now splitting Git commits works almost without a hinch. The more we get used to agents getting certain things right 100% of the time, the more we'll trust them. There are many many things that I know I won't get right, but I'm absolutely sure my agent will. As soon as we start trusting e.g. a QA agent to do his job, our "project management" velocity will increase too.

Interestingly enough, the infamous "bowling score card" text on how XP works, has demonstrated inherently agentic behaviour in more way than one (they just didn't know what "extreme" was back then). You were supposed to implement a failing test and then implement just enough functionality for this test to not fail anymore, even if the intended functionality was broader -- which is exactly what agents reliably do in a loop. Also, you were supposed to be pair-driving a single machine, which has been incomprehensible to me for almost decades -- after all, every person has their own shortcuts, hardware, IDEs, window managers and what not. Turns out, all you need is a centralized server running a "team manager agent" and multiple developers talking to him to craft software fast (see tmux requirement in Gas Town).
by georgemcbay | 2026-02-05 19:51:47+00:00
> It gives me hope that Trump will replace the top generals and a few layers down with yes-men who will spend the military budget on coke and then the US will be less of a threat to the rest of the world.

The US will continue to be the most powerful military in history for a very long time even with a highly incompetent top-layer. It will just have less people with the wisdom and power to push back on the president's worst impulses.

Unfortunately(?) there's not enough coke in the world to put much of a dent in the 1.5 trillion dollars they are hoping to spend on the military in 2027.

Also, there is likely to be a rapid burst of nuclear proliferation across the globe as everyone else adjusts to this new reality sans the traditional post-WW II world order.

On the current Trump path the world is going to get far more dangerous and chaotic, not less.
by kimixa | 2026-02-05 19:51:50+00:00
I mean the systems I work on have enough weird custom APIs and internal interfaces just getting them working seems to take a good chunk of the context. I've spent a long time trying to minimize every input document where I can, compact and terse references, and still keep hitting similar issues.

At this point I just think the "success" of many AI coding agents is extremely sector dependent.

Going forward I'd love to experiment with seeing if that's actually the problem, or just an easy explanation of failure. I'd like to play with more controls on context management than "slightly better models" - like being able to select/minimize/compact sections of context I feel would be relevant for the immediate task, to what "depth" of needed details, and those that aren't likely to be relevant so can be removed from consideration. Perhaps each chunk can be cached to save processing power. Who knows.
by segmondy | 2026-02-05 19:51:57+00:00
This is nothing new, folks have been doing this for since 2023. Lots of paper on arxiv and lots of code in github with implementation of multiagents.

... the "limit" were agents were not as smart then, context window was much smaller and RLVR wasn't a thing so agents were trained for just function calling, but not agent calling/coordination.

we have been doing it since then, the difference really is that the models have gotten really smart and good to handle it.
by LorenPechtel | 2026-02-05 19:52:12+00:00
Yeah, the alternatives aren't as good. They're safer, though.

Teflon and it's relatives--so long as you don't expose them to enough heat to mess with the C-F bonds, they're probably safe. But Teflon only exists as a solid, it will decompose before melting, thus the problem becomes how to form it? You need a solvent--a solvent that dissolves that which is famous for being impervious. To date only one such solvent has ever been found: it's pretty close chemically but one bond doesn't have a F stuck on it so it will play nice with both Teflon (which is what most of the molecule looks like) and other things (the piece that isn't like Teflon.) Can you hope to recover all of the solvent from the finished product? No way. And that solvent will react in the body, it's not inert like the Teflon. Toxic down to the detection threshold.

They have played games, producing "different" solvents but they're all the same thing, the same reactive part connected to a chain of a different length that is fully fluorinated. The length of the inert chain doesn't change anything, the toxicity comes from the one reactive part.
by strobe | 2026-02-05 19:52:49+00:00
>With AWS the knowledge is at least transferable

unfortunately it lot of things in AWS that also could be messed up so it might be really hard to research what is going on. For example, you could have hundreds of Lambdas running without any idea where original sources and how they connected to each-other, or complex VPCs network routing where some rules and security groups shared randomly between services so if you do small change it could lead to completely difference service to degrade (like you were hired to help with service X but after you changes some service Y went down and you even not aware that it existed)
by bunderbunder | 2026-02-05 19:53:04+00:00
I think their point might have been more that there just wasn’t as much need for jets that big in the first place. The jumbo jets are meant for a business model that pushes consumers into making extra compromises on their plans (like more and longer layovers) to accommodate the operator’s need to fill bigger planes with more people to make things economical. It turns out that many consumers are happy to spend a bit more on a direct flight instead of a 3 leg journey with one long flight on an widebody sandwiched between two “last mile” hops on a CRJ700.

The rocketry analogy would be choosing between (possibly - we can’t know numbers until Starship is commercially operational) paying a bit more but waiting less time for a Falcon 9 launch that puts you right into the orbit you want, or waiting for a bus ride on a Starship launch that only gets everyone to a compromise orbit in the general area of where they want to be and requires them to pack an extra motor and fuel for transferring the spacecraft to its final destination.
Show HN: VectorGuard-Nano – Free secure messaging for AI agents
by supere989 | 2026-02-05 19:53:36+00:00
I built VectorGuard-Nano, a lightweight secure messaging plugin for AI agents.

With MCP and agent frameworks exploding, agents need a way to communicate securely. This is MIT-licensed, HMAC-based obfuscation for casual agent messaging (Moltbook, Slack, IPFS, etc).

Features:
- Deterministic encode/decode with shared secrets
- Built-in timestamp handling
- Zero dependencies (just Node crypto)
- OpenClaw integration ready
- Round-trip guaranteed

This is the "nano" version to show the concept. I'm also developing full VectorGuard with model-bound cryptography that solves the recently published Whisper Leak vulnerability.

GitHub: https://github.com/Active-IQ/VectorGuard-Nano
More info: https://www.active-iq.com

Happy to answer questions!
by sgarland | 2026-02-05 19:53:52+00:00
That’s going to be enormously expensive. If you need guaranteed tenant isolation, put them in separate schemas, with specific user grants. That scales up much better than you’d think.

Or use Citus Postgres, and get sharding by schema for free, so you have both isolation and more or less infinite growth.

I’m not sure why if you think it would take 5 employees to manage self-hosted DBs, that it won’t take close to that to manage cloud-hosted ones. The only real difference you’re going to have once both are set up is dealing with any possible hardware issues. The initial setup for backups, streaming replication, etc. is a one-time thing, and then it just works. Hire a contractor for that, optionally keeping them on retainer for emergencies if you want.

You still have to deal with DB issues with a managed service: things like schema management, table design, index maintenance, parameter tuning, query optimization are all your responsibility, not the cloud provider’s.
by Legend2440 | 2026-02-05 19:53:57+00:00
You’re right, he does: https://daniel.haxx.se/blog/2025/10/10/a-new-breed-of-analyz...

Curl fully supports the use of AI tools by legitimate security researchers to catch bugs, and they have fixed dozens caught in this way. It’s just idiots submitting bugs they don’t understand that’s a problem.
by ianbutler | 2026-02-05 19:54:02+00:00
> Don't lump me in that "we". I did no such thing. I know exactly how it could be abused and have spent 12 years intentionally not working for companies that perpetuate it.

I don't think you know how to read because I certainly didn't do that. But also go fuck yourself.

This is why no one cares about your causes btw because weird angry little dudes isn't a good look.
by mahirsaid | 2026-02-05 19:54:29+00:00
Indeed, I've been paying attention to the market share of the biggest companies in advertisement, its clear that Google and Meta are the largest share by a large margin. Almost not even comparable to other players other than Reddit recently. which it's exposure is dependent on Search engines like Google and Bing for that matter. users within the platform are a different story. I personally think the internet is not being utilized wisely when it comes to current context. There is still so much to be done and innovated and there are gate keepers keeping this from happening.
by regenschutz | 2026-02-05 19:54:32+00:00
Looks awesome! Would have been very useful a few years ago when I was doing all kinds of things in Dart/Flutter.

I'm assuming this is only works for the web, and not for mobile apps?

What's the support for Material 3 like?

I'll definitely try it out later when I am on desktop!

Btw, the Hero Description (the text that among others says "Perfect SEO") overflows on my phone. Might want to get that fixed. Oh, and the "View on GitHub" button doesn't actually seem clickable?
by vkazanov | 2026-02-05 19:54:32+00:00
It took me about 15 years (out of 20 in the industry) to arrive at similar ideas. Interestingly, I heard all the arguments many times before but somewhat obscured by the way function programming speaks of things.

For the purpose of this game spliting things into core/shell makes certain things super easy: saving and restoring state, undo, debugging, testing, etc.

And one more bit, relevant to this new reality we find outselves in. Having a bunch of pure functions merged into a very focused DSL makes it easy to extend the systems through LLMs: a description of well-understood inputs and outputs fits into limited context windows.

By the way.

It is true that dedicated languages never arrived but FCIS is not a language feature, it's more like a architectural paradigm.

So who cares?