MurphyA/hacker-news huggingface dataset:
by aspenmartin | 2026-01-17 15:52:38+00:00
I'm definitely in the camp that this browser implementation is shit, but just a reminder: agent training does involve human coding data in early stages of training to bootstrap it but in its reinforcement learning phase it does not -- it learns closer to the way AlphaGo did, self play and verifiable rewards. This is why people are very bullish on agents, there is no limit technically to how well they can learn (unlike LLMs) and we know we will reach superhuman skill, and the crucial crucial reason for this is: verifiable rewards. You have this for coding, you do not have this for e.g. creative tasks etc.

So agents will actually be able to build a {browser, library, etc} that won't be an absolute slopfest, but the real crucial question is when. You need better and more efficient RL training, further scaling (Amodei thinks really scaling is the only thing you technically need here and we have about 3-4 orders of magnitude of headroom left before we hit insurmountable limits), bigger context windows (that models actually handle well) and possibly continual learning paradigms, but solutions to these problems are quite tangible now.
by starryex | 2026-01-17 15:53:02+00:00
I think one think we can do as engineers is refuse to build these propaganda machines. All the tools used to infect people with the propaganda are built by us. Refuse to work for the biggest offenders - Google, Meta, Twitter, etc. Engineers lust after these jobs and then complain about the fall of democracy. This is the biggest thing we can do. Refuse to build the tools of misinformation.
by gus_massa | 2026-01-17 15:53:28+00:00
Here in Argentina, we have a proportional system inside each province. At the national level we have an indefinite number of parties, but as a simplification, we have

* the 2 extremes: far-right, far-left

* the 2 biggest one: Milei and Cristina

* Like 3 small/medium in the middle

So you can select something in between. They work as informal alliances, so the parties in the middle most of the time align with one of the big ones, but they may switch in particular cases.

It makes it harder for the big parties to do very stupid things, but they can manage to do stupid things anyway ¯\_(ツ)_/¯
by dboon | 2026-01-17 15:54:08+00:00
Fantastic article! I wrote an ASCII renderer to show a 3D Claude for my Claude Wrapped[^1], and instead of supersampling I just decided to raymarch the whole thing. SDFs give you a smoother result than even super sampling, but of course your scene has to be represented with distance functions and combinations thereof whereas your method is generally applicable.

Taking into account the shape of different ASCII characters is brilliant, though!

[1]: https://spader.zone/wrapped/
by ryanlol | 2026-01-17 15:54:14+00:00
>I'd bet good money that this dude has some sort of antisocial personality disorder, and really can't be "cured", so to speak.

I'm happy to take you up on this, but I feel like the stakes will need to be pretty high to justify all the effort involved.

>Something tells me he'll try to sneak out of Finland (which is easy due to Schengen), purchase a new passport, and leave Europe.

Why would I do that? I hold a valid Finnish passport, haven't had any trouble entering or exciting Schengen zone lately.
by kankerlijer | 2026-01-17 15:55:41+00:00
Outside of SV the thought of More Tech being the answer to ever greater things is met with great skepticism these days. It's not that people hate engineers, and most people are content to hold their nose while the mag7 make 401k go up, but people are sick of Big Tech. Like it or not, the Musks, Karps, Thiels, Bezos's have a lot to do with that.
by littlestymaar | 2026-01-17 15:55:51+00:00
> It's all very 1984-esque; I'm seeing shades of "We were never/always at war with Oceania/Eurasia".

This is an hilarious take.

There's little things less 1984-esque than a small self-structured collective organization enforcing the preference of an individual on how they should be named.

It's the opposite of “a dictatorship imposing its views on individuals through propaganda”, it's a collective of people helping an individual, dead for not being as society wanted them to be, have their personal wish fulfilled even after death. People who want to dead name the victim, are the one who want to erase the individual to make it fit the mold of society, they are the totalitarian hivemind, they are the Tom Parsons of our reality.

Orwell being a lifelong anarchist socialist, there's very little doubt on which side he'd be in that debate.
by adventured | 2026-01-17 15:55:57+00:00
Europe is so backwards when it comes to annual heat deaths that they manage to have more heat deaths per year than the US has gun deaths + heat deaths combined. You won't hear about that from Europeans though, it'd make them seem barbaric. 175,000 heat deaths per year in Europe according to the WHO. It's a staggering genocide of technological primitiveness. Imagine having millions of people die because you can't be bothered to adopt 1950s technology (and of course I'm aware of the things the US is backwards on).
by Aurornis | 2026-01-17 15:56:10+00:00
I kind of doubt a single surprise bill that happened to arrive in the winter is a TOU plan change.

If someone changes to a TOU plan and their bill shoots up, they’re smart enough to blame the plan change and cite that

Most surprise winter time bills are just excess electric heater usage, such as after the purchase of a couple space heaters without thinking about the overall cost.

> This is why there's pushback in some areas that have had deregulated energy markets

What areas have deregulated residential electricity?
by analog8374 | 2026-01-17 15:56:54+00:00
I think everybody, with few exceptions, is in the system involuntarily. And also you can't say that that you don't want to be in the system. You have to fake it very hard if you want to "win". You have to demonstrate "passion" and such.

My boss refused to allow people to call him boss, for example. He really hated the system.
Show HN: OpenAI to show ads in ChatGPT for logged-in U.S. adults
by SRMohitkr | 2026-01-17 15:57:21+00:00
It appears OpenAI is testing or planning to introduce ads inside ChatGPT for logged-in users in the U.S.
From what I can tell, ads would appear in limited placements and not affect free access immediately, but this raises questions about product direction, user experience, privacy, and long-term incentives.

Curious how others here feel about ads inside AI tools:

1.Would this change how you use ChatGPT?

2.Are ads inevitable for consumer AI products?

3.What would be an acceptable implementation?
by stranded22 | 2026-01-17 15:58:11+00:00
Pardon?

This comment literally shows why you do not understand ADHD.

Reckon people haven’t TRIED?

And how dare you call someone lazy if they have ADHD?!?

I’m the hardest working person I know - but because of meds, I have been able to focus better. My long term planning is 0, and my executive function is low. But sure, I’ll just try a bit more.

Smh.
by galsapir | 2026-01-17 15:58:20+00:00
i've been working with healthcare/biobank data and keep thinking about what "data moats" mean now that llms can ingest anything. some a16z piece from 2019 said moats were eroding — now the question seems to be whether you can actually make your data useful to these systems, not just have it. there's some recent work (tables2traces, ehr-r1) showing you can convert structured medical data into reasoning traces that improve llm performance, but the approaches are still rough and synthetic traces don't fully hold up to scrutiny (writing this to think through it, not because i have answers)
by cbmuser | 2026-01-17 15:58:22+00:00
»US electricity demand jumped by 135 terawatt-hours (TWh) in 2025, a 3.1% increase, the fourth‑largest annual rise of the past decade. Over that same period, solar generation grew by a record 83 TWh – a 27% increase from 2024 and the biggest absolute gain of any power source. That single jump in solar output covered 61% of all new electricity demand nationwide.«

This article equates generation with consumption which is a fallacy.

Lots of solar and wind generation is actually produced without meeting demand meaning that the generated electricity often has to be wasted.
by anthk | 2026-01-17 15:58:23+00:00
That's a KVM role. The idea in the 21th century it's to spawn a personal VM per user. Network boundaries would be defined in hypervisor devel, (VLANs, network share accesses and so on), you would need nearly no GPO's but different WMI setups with options prebaked.

The old NT based ACL's/GPO's and such are obsolete as I said when a cheap Linux KVM server can do tons of stuff by itself and firewalls (even professional ones) are dirt cheap. The old world died long ago.
by nomagicbullet | 2026-01-17 15:58:25+00:00
I don't find open spaces noisier than cubicles but I am able to easily block out distracting sounds.

I am interrupted, and when I am is generally somebody giving me a useful quick update or an informal greeting from an office buddy when they notice I make welcoming eye contact.

I don't think I ever felt a lack of privacy in the office or expected it in any way? I wonder what kind of privacy I would need that the restroom doesn't cover, I'm sure there are some instances since it's been called out.
by abdibrokhim | 2026-01-17 15:58:58+00:00
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by CodingJeebus | 2026-01-17 16:00:02+00:00
> Which brings us to the question: why does this pattern repeat?

The pattern repeats because the market incentivizes it. AI has been pushed as an omnipotent, all-powerful job-killer by these companies because shareholder value depends on enough people believing in it, not whether the tooling is actually capable. It's telling that folks like Jensen Huang talk about people's negativity towards AI being one of the biggest barriers to advancement, as if they should be immune from scrutiny.

They'd rather try to discredit the naysayers than actually work towards making these products function the way they're being marketed, and once the market wakes up to this reality, it's gonna get really ugly.
by andsoitis | 2026-01-17 16:00:11+00:00
> Are we reaching a point where it's easier to just build what you need rather than learning a new app/tool?

Applications and tools have always been about solving a particular problem.
Some software are more general out of the box than others and so can be applied to wide range of specific tasks. Famously, spreadsheets are great for this.

I'd argue that ChatGPT is even more general than spreadsheets on enough dimensions that it can be used for a much wider range of problems, including workflows.
Show HN: Long-horizon LLM coherence benchmark (500 cycles)
by teugent | 2026-01-17 16:00:20+00:00
We ran a 500-cycle benchmark to test long-horizon coherence, reasoning stability, and identity persistence in large language models.

The experiment used the Sigma Runtime, a model-agnostic control layer that adds long-term memory, structural coherence tracking, and adaptive equilibrium regulation to standard LLMs. It enables stable reasoning and personality continuity across hundreds of interactions without context resets.

Protocol overview
- 500 reasoning cycles divided into 10 blocks of 50 questions.
- Every 50th response (“Rib Point”) compresses and validates reasoning from the previous 49 cycles.
- Each block builds on prior synthesis, forming a cumulative reasoning chain up to cycle 500.
- The final cycle (C500) performs full closure, verifying long-range consistency.

Two independent tests
- OpenAI GPT-5.2 — phase-stable regime: early micro-fractures during lattice formation self-corrected by C50; zero structural drift afterward.
- Google Gemini-3-Flash — forced-equilibrium regime: proportional feedback absorbed API truncations and prevented over-stabilization.

Results
- Both runs maintained full coherence and stable identity across 500 cycles.
- Rib Points confirmed successful recursive compression: reasoning remained referentially consistent.
- Structural drift and semantic degradation ≈ 0 across both architectures.

Architecture components
- SRIP-09: Long-Term Memory + Structural Coherence Layer
- SRIP-09c: Nucleus Integration Protocol (semantic anchoring)

Full report (DOI): https://doi.org/10.5281/zenodo.18271591
Appendix & data: https://github.com/sigmastratum/documentation/blob/a57bae59b...
by jonjacky | 2026-01-17 16:00:33+00:00
See also Rogaway's Moral Character of Cryptographic Work[0], which is a more technical talk for an audience of cryptography researchers. It's been noted
several times on HN, most recently in 2023 with 56 comments [1] and in 2015 with 93 comments [2].

0. https://web.cs.ucdavis.edu/~rogaway/papers/moral.html

1. https://news.ycombinator.com/item?id=36901885

2. https://news.ycombinator.com/item?id=10673055
by Sevii | 2026-01-17 16:00:34+00:00
I don't buy the idea of immutable contracts becoming more common with AI assisted coding. One of the areas AI shines is coding against a spec. One of the big problems in old systems is that the cost of upgrading consumers to a new API version gets too expensive. Using AI agents you can just do it for them. Refactoring getting cheaper isn't going to make API contracts immutable its going to make them more mutable.
Show HN: LaReview, Plan-first AI code review, runs locally, bring your own agent
by deofoo | 2026-01-17 16:00:37+00:00
Hi HN, I built LaReview because AI review bots spam PRs with 50+ nitpicky comments that authors just batch-dismiss.

I also didn't want to pay $15-30/month for another AI subscription when I already have an amazing coding agent (Claude Code, OpenCode, Gemini, etc.) that's way better than what these review bots use.

LaReview works differently: you paste a PR link, it groups the changes by logical area (auth changes, API endpoints, migrations, UI updates) ordered by risk, then uses your coding agent to draft review comments that you edit before posting. Nothing posts automatically.

Example: a 40-file PR touching auth, API, and frontend becomes 3 reviewable chunks. You start with auth (highest risk), draft 2-3 focused comments, then move to the next chunk. No 40-comment dump.

How it works:
1. Paste a GitHub/GitLab PR link or unified diff
2. AI analyzes the changes and proposes a review plan grouped by area and risk
3. You open each task and see only the relevant code hunks
4. AI drafts potential feedback for that specific task
5. You edit, approve, or delete each suggestion before posting to GitHub/GitLab (or export as Markdown)

Install:
macOS: brew install --cask puemos/tap/lareview
Linux: brew install puemos/tap/lareview
Windows: not yet (let me know if you need it)Repo: https://github.com/puemos/lareview
Releases: https://github.com/puemos/lareview/releases

You need your own API key for Claude, OpenAI, Gemini, or similar. LaReview runs locally and fetches PR data directly from GitHub/GitLab - no LaReview server involved.

Why it's different from Copilot/CodeRabbit/PR-Agent:
1. They mostly comment file-by-file, LaReview groups changes by logical area first
2. They auto-post or make you filter spam, LaReview drafts suggestions you review
3. They often need cloud integrations, LaReview is local-first

License: MIT + Apache-2.0
by fwipsy | 2026-01-17 16:01:16+00:00
I did something similar back in college: https://github.com/Andrew-Maxwell/Ascii-Platformer/blob/mast...

I only had to run against static images and I was using a fixed 8x8px bitmap font. I converted each character in the font and each 8x8 tile from the image into a 64-bit integer and just used popcnt to find the one which was the closest match. I wonder if this produces meaningfully different results from your approach? Unfortunately I don't have any example results on hand...
by jurschreuder | 2026-01-17 16:02:34+00:00
The problem is the software has already been made in the past. It has built up over time. Just like songs. There are so many already there.

When smartphones just came out I was already not making websites anymore. But every single app I made got at least 10k downloads in one week and around 1/5 got in the top 10 of a category like "social" even though I've only ever spent maybe a month max on developing any single app.

But now there are soooo many already there. Good luck getting into the top 10 social now with one weekend of coding.
by Nextgrid | 2026-01-17 16:04:29+00:00
Because there being a stable desktop OS brings indirect profits and enables efforts like AI to work. AI isn't going to help you if you no longer have a computer to run it on.

This is my general concern with the decline of tech quality. It’s one thing if it’s just consumer products, but it’s now affecting actual tools people including us use to do their jobs.
by reorder9695 | 2026-01-17 16:04:47+00:00
I personally prefer not having other people decide for me which facts are and aren't relevant, I think that is unhelpful and potentially dangerous (some people think what happened in Tienanmen Square isn't relevant to the general population, do you agree?).

For a transgender person, I may have known them before they transitioned for example and may not necessarily be familiar with their new name, that's a reason off the top of my head that it would be relevant to me but not necessarily you.
by __MatrixMan__ | 2026-01-17 16:05:12+00:00
You're just describing a recipe for agents opening fire into a crowd. The opposition is doing it right: demonstrate to ICE that they're nonviolent, well coordinated, and much more numerous.

If violence is warranted, the time and place for it is not when they're all together, armed to the teeth, and looking for a fight. It's when they're off duty, alone, and not expecting a confrontation.
by vunderba | 2026-01-17 16:05:18+00:00
Thanks for the feedback.

> The bigger models are way more capable than you make them out to be.

No test suite is ever going to be perfect. GenAI Showdown was started with the goal of focusing on a very narrow spectrum of testing (prompt adherence) because as a creator that's the one of the most interest to me.

> Pure t2i is not a good benchmark anymore

Just FYI Image Editing is already a separate benchmark (see the navbar at the top).

> Your testing suite is the perfect example that structured data implies false confidence

Again - the headline is "Specific prompts and challenges with a strong emphasis placed on adherence". If I tried to capture every possible aspect of GenAI models (multimodal, texture maps, periodic motion, tiling, etc) - I'd be at it until the heat death of the universe.

Incidentally - which model (specifically) do you think is ranked unfairly? While Flux.2 [dev] did only score a single point above ZiT, it's weighted score is much higher (1442 points vs 911 points).
by lkjdsklf | 2026-01-17 16:05:27+00:00
XFCE is actually a great example of the problem with Linux

It's wayland support is utterly broken right now and getting very little attention. The major distros are about to put X11 in the grave and then XFCE will die (or more likely it'll live on in some weird offshoot distro).

That's not really an acceptable situation for a consumer product.

now obviously xfce is not one of the main DEs pushed by the distros, but it's plight is a symptom of a couple of problems that plague linux

Compatibility is important. MSFT, for all their faults, puts a shitload of effort into making sure that even old ass software keeps working. They're not perfect (especially in the last few years) but they're miles ahead of linux here. As a user, I shouldn't ever have to know or care about wayland or pipewire or whatever other nonsense, but that's not the case. I have to know just so I can find software that works with my system.
by acron0 | 2026-01-17 16:06:29+00:00
I appreciate your response, and I will confess to a certain bias as at some point I think I made the leap of acceptance of AI, in the sense of "this is how it's going to be from now on so I better get on board with it".

Spot on. These are the exact tools I was referring to. They seem a little un-magical but the real value is the boilerplate they provide for context management. Essentially allowing coding agents to perform at their beat. For what it's worth, Taches is my tool of choice.
by ventegus | 2026-01-17 16:06:40+00:00
Actually, I'm not entirely sure on how archive.org achieves its resiliency.

It's a rather interesting question for archive.org, if one were to interview them, that is.

Unlike archive.today, they don't appear to have any issues with e.g. child pornography content, despite certainly hosting a hundred times more material.

They have some strong magic which makes the cheap tricks needless.
by simonw | 2026-01-17 16:07:48+00:00
I'd love to see answers of those questions too, especially the team ones.

Personally the skills that I have found most useful that I've written myself are these:

- uv-tdd - run a TDD loop on a Python project via uv: https://github.com/simonw/skills/blob/main/uv-tdd/SKILL.md

- setup-to-pyproject - migrate a setup.py Python project to pyproject.toml in the way I prefer https://github.com/simonw/skills/blob/main/setup-to-pyprojec...

- datasette-plugins: everything an LLM needs to write a new Datasette plugin https://github.com/datasette/skill/blob/main/SKILL.md
by fwipsy | 2026-01-17 16:08:35+00:00
Aha! The 8x8 bitmap approach is the one I used back in college. I was using a fixed font, so I just converted each character to a 64-bit integer and then used popcnt to compare with an 8x8 tile from the image. I wonder whether this approach results in meaningfully different image results from the original post? e.g. focusing on directionality rather than bitmap match might result in more legible large shapes, but fine noise may not be reproduced as faithfully.
by Rafert | 2026-01-17 16:08:45+00:00
I'm surprised it's not mentioned yet, but this seems to compliment last year's acquisition of observability tool HyperDX[1] (part of ClickStack[2]) quite well. I'm in the market for a new o11y platform and it seems all vendors are working to add LLM observability one way or the other, if they haven't added it already.

1: https://news.ycombinator.com/item?id=44194082
2: https://clickhouse.com/use-cases/observability
by mikepurvis | 2026-01-17 16:08:57+00:00
Maybe, but I think it could have made a small team very wealthy and successful much more than it did a large company.

It was obviously pitched as an ecosystem/platform play, like "the next vmware" or something, but there was never anything close to a real moat there. Running a registry involved a lot of storage and transfer costs plus spam/abuse management, and private registry was always going to be a better fit for being integrated with CI platforms and the like more than a standalone service with its own auth and billing concerns.
by johng | 2026-01-17 16:09:01+00:00
This article does pretty much talk about the past when they did control the government. It's also been well known that the left has spent more money in all of the elections for a long time. Kamala spent over $1B on her campaign which was much more than Trump.

I'd like to find out if the dollar figures in the article are correct -- that tells the real story.