MurphyA/hacker-news huggingface dataset:
by z-dev | 2025-12-18 21:26:24+00:00
I don't much about casey, but jblow seems to have gotten popular partly because of the timing with live streaming becoming mainstream and also because people find his brash "tell-it-like-it-is" opinions refreshing. It's the same reason why people tend to gravitate towards guys like linus or stallman. Having opinions and not being a fence-sitter makes you interesting.
by whou | 2025-12-18 21:26:53+00:00
Oh man. Everything about this guy looks entirely AI made. Am I being paranoid or does even his GitHub profile picture[0] is AI? Taking an even slightly closer look, it just looks like this is an entirely fake developer, what the actual hell is this profile. Literally millions of lines of code submitted so recently and in huge proportions at a time as well. Again, am I really being that much paranoid about all of this?

[0]: https://github.com/kolkov
by maxglute | 2025-12-18 21:27:24+00:00
Most of that entire network is easy to replicate, as in it's not technically hard, the hard part is validation, no one in PRC wants to use unproven PRC inputs if risk is 100m wafer run goes to trash. Hence PRC now basically insuring domestic fabs on risk runs using domestic inputs, which are being validated on full scale production, instead of taking 5 years to verify, it'll take 2. Export controls help this, i.e. domestic resist basically required now after JP export controls.

The hard part, i.e. optics, light source. Zeiss had like 3k engineerings, Cymer 1k, ASML 13k during EUV commercialization process. PRC can (and is) just throwing bodies at problem, lots of parallel execution with clear second mover road map. That and as this article suggest, they're literally poaching people with the tacit knowledge which will help speed run. I'd wadger they get there sooner than later.
by Someone | 2025-12-18 21:27:38+00:00
> So there I was, implementing a one element ring buffer. Which, I'm sure you'll agree, is a perfectly reasonable data structure.

It is, but, IMO, shouldn’t use the code for “a n-element ring buffer, with n set to 1”, similarly to how an array of booleans in many languages shouldn’t be implemented as “an arrayof Foos, with Foo set to bool”.

C++ has std::bitset and std::vector and Java similarly has BitSet and Array because using the generic code for arrays of bits is too wasteful.

Similarly, a one-element ring buffer is either full or it is empty. Why use two indexes to encode a single boolean?
by chaosharmonic | 2025-12-18 21:27:42+00:00
> Honor obliges me to admit this is not literally true. bettermotherfuckingwebsite.com is a fucking pedagogical masterpiece and reshaped how I built my own site. But let's not spoil the bit...

> Inspired by (and in joyful dialogue with) motherfuckingwebsite.com, justfuckingusehtml.com, bettermotherfuckingwebsite.com, and justfuckingusereact.com. Extremism in defense of developer experience is no vice! This site made by me. Does this all sound a bit like shallow slop? Yup, please help make it better.

I agree with you, and wrote a similar one for Markdown that you might enjoy. Same overall naming scheme. (Note: open the comments before you judge the use of a Web Component for rendering purposes.)
by nodja | 2025-12-18 21:28:13+00:00
It's an alternate architecture of LLMs, they actually predate modern LLMs. An encoder-decoder model was actually the model used in the "Attention if all you need" paper that introduced the transformer and essentially gave birth to modern LLMs.

A encoder-decoder model splits input and output. This makes sense for translation tasks, summarization, etc. They're good when there's a clear separation of "understand the task" and "complete the task", but you can use it for anything really. A example would be send "Translate to english: Le chat est noir." to the encoder, the encoder processes everything in a single step, that is understand the task as a whole, then the output of the encoder is fed to the decoder and then the decoder runs one token at a time.

GPT ditches the encoder altogether and just runs the decoder with some slight changes, this makes it more parameter efficient but tends to hallucinate more due to past tokens containing information that might be wrong. You can see it as the encoder running on each token as they are read/generated.

Edit: On re-read I noticed it might not be clear what I mean by past tokens containing wrong information. I mean that for each token the model generates a hidden state, those states don't change, so for example an input of 100 tokens will have 100 hidden states, the states are generated at once on the encoder model, and one token at a time on the decoder models. Since the decoder doesn't have the full information yet, the hidden state will contain extra information that might not having anything to do with the task, or even confuse it.

For example if you give the model the task "Please translate this to chinese: Thanks for the cat, he's cute. I'm trying to send it to my friend in hong kong.". For a enc-dec model it would read the whole thing at once and understand that you mean cantonese. But a decoder only model would "read" it one token a time it could trip in several places, 1. assume chinese means mandarin chinese not cantonese, 2. assume that the text after "cute." it's something to also translate and not a clarification. This would have several token worth of extra information that would confuse the model. Models are trained with this in mind so they're used to tokens having lots of different meanings embeded in them, then having later tokens narrow down the meanings, but it might cause models to ignore certain tokens, or hallucinate.
by rekabis | 2025-12-18 21:28:23+00:00
Someone up here in Canada ought to get Carney to duplicate the lab, and just straight-on poach anyone on the American lab with full moving expenses paid.

Stephen Harper’s wanton destruction of the Experimental Lakes Area - which had _hundreds of millions_ of man-hours of research across three centuries - really needs to be atoned for, and poaching the entire lab and all staff would be a great start to re-establishing Canada’s prominence in climate science.
by mrinterweb | 2025-12-18 21:28:46+00:00
I would much rather buy a dumb TV. I feel that the smart TV experience is an opportunity it eventually make TVs feel dated and slow. I would rather buy a standalone streamer that I can plug in. Buying a new $100 dollar streamer every couple years is cheaper and produces less e-waste than buying a new giant TV.

I isolate smart TVs and other IOT devices to a separate network/subnet, and usually block their network access unless they need an update.
by ewoodrich | 2025-12-18 21:28:49+00:00
Yeah, I've been using Claude and Codex to create bespoke systemd services for my random tools and automation stuff and have been really impressed by how easy it is and how rock solid they are once setup. It's really nice not living in constant terror that a reboot, network connectivity loss or gentle breeze will cause my duct taped scripts to collapse under their own weight.
by jjk166 | 2025-12-18 21:28:52+00:00
The idea that tumors develop their own tumors, suppressing cancer is known as the Hypertumor Hypothesis and, while it works in computer models, there isn't actually any evidence backing it up.

The hypothesis doesn't really resolve Peto's paradox, the observation that cancer rates don't scale directly with the number of cells in an organism. Not only do large organisms like whales get fewer cancers per cell division, small animals like mice get more cancers per cell division, which can not really be explained by a threshold beyond which hypertumors suppress tumors. The actual evidence suggests organisms just evolve whatever level of cancer resistance they need to have low odds of dying of cancer before something else kills them.

That being said, the main observation underpinning Peto's paradox was actually just due to lack of good data. Over the years much more data has been collected from animal autopsies and it turns out that big animals do get cancer and cancer rates actually do scale with body size, just different species have varying levels of cancer protection, with the levels of protection being similar in closely related species of different sizes.
by kuylar | 2025-12-18 21:29:45+00:00
> As for AI scrapers impersonating googlebot I feel like yes they'd definitely start doing that, unless the risk of getting sued by google is too high?

Google releases the Googlebot IP ranges[0], so you can makes sure that it's the real Googlebot and not just someone else pretending to be one.

[0] https://developers.google.com/crawling/docs/crawlers-fetcher...
by segmondy | 2025-12-18 21:30:00+00:00
scale down or not, we will see consumer GPU from China in the future. might be a copy or rip of existing GPUs, but it will happen. 3 of my GPU rigs are chinese MB built for the chinese market, ripoff of dual x99. They work, they are cheap, I got them for under $100 a piece. So maybe 5 years from now, we get cheap GPUs, and maybe they will be equivalent to 5090s, but who cares if the price is right?
by mrcode007 | 2025-12-18 21:30:02+00:00
There is one more way that is truly lock free. Most lock free implementations relying on atomic compare and swap instructions are not lock free afaik; they have a lock on the cache line in the CPU (in a way you go away from global lock to many distributed locks).

There is one more mechanism that allows implementing ring buffers without having to compare head and tail buffers at all (and doesn’t rely on counters or empty/full flags etc) that piggybacks on the cache consistency protocol
by theshrike79 | 2025-12-18 21:30:39+00:00
IMO LLMs are forcing us in the other way.

To get the maximum ROI from LLM-assisted programming it needs proper unit tests, integration tests, correctly configured linters, accessible documentation and well-managed git history (Claude actually checks git history nowadays to see when a feature was added if it has a bug)

Worst case we'll still have proper tests and documentation if the AI bubble suddenly bursts. Best case we can skip the boring bits because the LLM is "smart" enough to handle the low hanging fruit reliably because of the robust test suite.
by dfxm12 | 2025-12-18 21:31:00+00:00
If there were any significant number of people who would pay for a dumb high end TV, the market would sell them one.

I don't think they would. There are some TV manufacturers that are better about not nagging you (which is one of the reasons why I bought a Sony last year), but as time moves forward, companies have been less likely to leave money on the table. This is just the logical result of capitalism. Regulation will be the only way to protect consumer privacy.

Similarly, air travel gets worse as consumer protection regulations gets rolled back
by thunderfork | 2025-12-18 21:31:02+00:00
I travel to work, and engaging with the outdoors, traffic, etc. involves sacrificing safety that I wouldn't have if I stayed at home.

So, how much would my employer need to pay me? Not much, I guess? I definitely get paid less than the average cop in my city.

There are plenty of jobs that involve sacrificing safety, but very few of them give you the opportunity to kill people because you "didn't want to give up your own safety".
by 9rx | 2025-12-18 21:31:24+00:00
The scare quotes are significant. Obviously nobody can ever see it all as taken in its most literal sense. But one can start to see enough that they can recognize the patterns.

If your job is dependent on the weather, one year might be rainy, one year might be drought, one year might be a flood, etc. You need to see them to understand them. But eventually you don't have to need to see the year where it is exceptionally rainy, but not to the point of flood, to be able to make good decisions around it. You can take what you learned in the earlier not-quite-so rainy year and what you learned during the flood year and extrapolate from that what the exceptionally rainy year entails. That is what levels up someone.

Much the same is true in software. For example, once you write a (well-written) automated test in Javascript and perhaps create something in Typescript, you also have a pretty good understanding of what Rocq is trying to do well enough to determine when it would be appropriate for you to use. It would no doubt take much, much longer to understand all of its minutia, but it is not knowledge of intimate details that "senior", "principle", etc. is looking for. It is about being able to draw on past experience to make well-reasoned choices going forward.
by m463 | 2025-12-18 21:31:34+00:00
I think government is the only way to regulate below pain threshold nonsense that weighs down society.

but I think small issues in society might translate to small issues for government action, and regulatory capture has a super-high roi overturning "minor" stuff.

I suspect only showing real harm for something is the only way to get these things high-enough priority for action.

I kind of wonder if the pager attacks, or the phone nonsense in ukraine/russia might make privacy a priority?
by xg15 | 2025-12-18 21:31:59+00:00
When reading about articles relating to consciousness, I'm always amazed how far the "state of knowledge" of the general public seems to have diverged from the (neuro)scientific one.

On the "public" side, you can read neverending discussions about the "true nature" of consciousness, asking whether it's biological or a fundamental physical force or exists on a different metaphysical plane altogether, with the debate circling back and forth between psychology, quantum physics, cosmology, philosophy, religion, etc etc. and always framing this as a mystical, eternally unanswerable question.

Meanwhile neuroscience is just like "yup, it's biological. That's it. We know for decades which brain regions are responsible for different aspects of consciousness, such as memory, emotion and cognition and are at a point where we can start researching the evolutionary history of consciousness, because the knowledge is solid enough."
by n1xis10t | 2025-12-18 21:32:14+00:00
That’s so many scrapers. There must be a ton of companies with very large document collections at this point, and it really sucks that they don’t at least do us the courtesy of indexing them and making them available for keyword search, but instead only do AI.

It’s kind of crazy how much scraping goes on and how little search engine development goes on. I guess search engines aren’t fashionable. Reminds me of this article about search engines disappearing mysteriously: https://archive.org/details/search-timeline

I try to share that article as much as possible, it’s interesting.
by golly_ned | 2025-12-18 21:32:22+00:00
I wonder how much their revenue really ends up contributes towards covering their costs.

In my mind, they're hardly making any money compared to how much they're spending, and are relying on future modeling and efficiency gains to be able to reduce their costs but are pursuing user growth and engagement almost fully -- the more queries they get, the more data they get, the bigger a data moat they can build.
by baditaflorin | 2025-12-18 21:32:52+00:00
Built this to solve the problem of categorizing domains at scale. Pre-processing the top 10M domains through GPU-intensive AI analysis - now returns instant categorization via API: industry, business model, target market, audience profile. The interesting part is visualizing the "long tail" of communities that don't show up in typical web rankings. Happy to answer technical questions.
by johnea | 2025-12-18 21:34:11+00:00
Hope does spring eternal, doesn't it 8-/

If no one manufactures such a product, how does the "market" express this desire?

Buying one toaster, that would last your lifetime, is easily manufactured today, and yet no company makes such a thing. This is true across hundreds of products.

The fact is, manufacturing something that isn't shit, is less profitable, so what we're gonna get is shit. It doesn't really matter what people "want".

This is true for toasters and TVs...
by dietr1ch | 2025-12-18 21:34:20+00:00
The team (AND Marketing) should focus on saying it's a fast core browser with the extensions you want to make it yours.

Have recommended extension sets ([uBlock, Sponsorblock], [Containerise, Sideberry, Decentraleyes], [AI translation + Dictionary/Thesaurus]).

Make me want to use your AI features, don't just slap them on my face wishing I'll do more than get mad and try to get rid of them.
by sundarurfriend | 2025-12-18 21:34:24+00:00
> A lot of these are the underpinnings of modern computer science optimizations.

Note that older articles have already been open access for a while now:

> April 7, 2022

> ACM has opened the articles published during the first 50 years of its publishing program. These articles, published between 1951 and the end of 2000, are now open and freely available to view and download via the ACM Digital Library.

- https://www.acm.org/articles/bulletins/2022/april/50-years-b...
by limagnolia | 2025-12-18 21:34:37+00:00
But SNAP doesn't have a hard cutoff. There are welfare programs that do, but SNAP doesn't.

School lunch programs have two phases, free, and reduced. Medicaid varies a bit by state, but transitions to Obamacare subsidies. Hitting the cutoff for medicaid can really hurt, though, if your employer doesn't provide healthcare benefits.
by jijijijij | 2025-12-18 21:34:45+00:00
That's a limited view. The damage this could cause should be accounted for. People don't have to sell shit, they could fuck things up just for the fun of it. That's something to consider, especially with a bunch of teenagers. Now, these big corpos didn't take the chance to sponsor and encourage these kids early careers and make this fuck-up good PR, at least.
by kordlessagain | 2025-12-18 21:35:49+00:00
I’ve been using Codex CLI heavily after moving off Claude Code and built a containerized starter to run Codex in different modes: timers/file triggers, API calls, or interactive/single-run CLI. A few others are already using it for agentic workflows. If you want to run Codex securely (or not) in a container to test the model or build workflows, check out https://github.com/DeepBlueDynamics/codex-container.

It ships with 300+ MCP tools (crawl, Google search, Gmail/GCal/GDrive, Slack, scheduling, web indexing, embeddings, transcription, and more). Many came from tools I originally built for Claude Desktop—OpenAI’s MCP has been stable across 20+ versions so I prefer it.

I will note I usually run this in Danger mode but because it runs in a container, it doesn't have access to ENVs I don't want it messing with, and have it in a directory I'm OK with it changing or poking about in.

Headless browser setup for the crawl tools: https://github.com/DeepBlueDynamics/gnosis-crawl.

My email is in my profile if anyone needs help.
by dmoy | 2025-12-18 21:35:52+00:00
I just hellban every app from sending any notifications, except for a select few. Apps get like a one strike policy on notification spam. If they send a single notification I didn't want, I disable their ability to send notifications at all.

Also all notifications/etc are silent, except for alarms, pages, phone calls, and specific named people's texts.

Everything else... no. YouTube was the worst offender before for me.
by lbreakjai | 2025-12-18 21:36:00+00:00
Splitting application API and generic data API is orthogonal to HTMX. You still have issues compared to plain JSON, don't you?

Imagine you need firstName/email in once place, firstName/email in another, and firstName/D.O.B in another.

In a plain JSON world, I'd craft a single "user" endpoint, returning those three datapoints, and I would let the frontend handle it. My understanding is with HTMX, I'd have to craft (and maintain/test) three different endpoints, one per component.

I feel like you would quickly end up in a combinatorial explosion for anything but the simplest page. I really don't get the appeal at all. Of course everything can be very simple and lightweight if you hide the complexity under the bed!
by golly_ned | 2025-12-18 21:36:06+00:00
I don't think this quite captures the problem: even if the code is functional and proven to work, it can still be bad in many other ways.

The submitter should understand how it works and be able to 'own' and review modifications to it. That's cognitive work submitters ipso facto don't do by offloading the understanding to an LLM. That's the actual hard work reviewers and future programmers have to do instead.
by rsync | 2025-12-18 21:36:08+00:00
For the sake of completeness I will mention that one US bank that I use, Wells Fargo, issues the classic RSA keychain tokens:

https://www.wellsfargo.com/biz/online-banking/securid/

... which is quite simple and cheap ... and can be used in place of SMS 2FA.

The fact that these tokens exist and are so simple to deploy and use really deflates any claim (by banks) that banking and/or auth apps are required. It causes one to consider what the real motivation is behind the bank desperately pushing customers away from the simple and adequate web service towards the apps.
by darkwater | 2025-12-18 21:36:23+00:00
I don't think I have been rude at all, and also seniority does not give any special authority over opinions.

My point was that the "creating the personal brand" part - which can seem something intentional - is just a byproduct of posting, writing and contributing. And he contributes because he has knowledge, opinions and things to say.

It's like writing your own blog with good content and getting organic traffic from search engines vs writing SEO content to get traffic and get noted.

Maybe I initially expressed myself not the way I really wanted.
by vernrVingingIt | 2025-12-18 21:36:25+00:00
Sure. The hang up here is SWEs belief those abstractions must be stored as some syntax they know; C, Python, RoR, Linux, Elixir... whatever.

There is zero obligation to capture the concept of memory safety in traditional software notation. If it was possible to look inside the hardware at runtime no one is going to see Rust syntax.

At runtime it's more appropriate to think of it as geometric functions redrawing electrical state geometrically to avoid collisions. And that's where future chip and system state management are headed.

Away from arbitrary syntax constructs with computational expensive parsing rules of the past towards a more efficient geometric functions abstraction embedded in the machine.
by maxglute | 2025-12-18 21:36:30+00:00
Yeah PRC probably going to dump 1T into indigenize semi efforts by end of decade, but IMO good chance they're going to treat strategic semi as commodity utility business than make NASDAQ lines go up model. When western semi has 1st tier suppliers taking 30% margin, asml taking 50%, tsmc taking 50%, nvidia taking lol 70%, there's alot of fat on the pyramid to trim. PRC doing cost plus 10-20% will basically be able to brrrt chips stupid cheap if they have mature domestic tool scaling, enough to wipe litho+yield inefficiencies.

Western semi still "safe" since west+co aren't going to source from PRC leading edge due to national security, but pretty soon they're either going to need to compress margins to compete which means cutting costs, which means cutting R&D because shareholder going to get theirs or western semi business model going to run on permenant subsidies. Which is what will probably happen considering their performance is why stonk lines go up right now. That 1T PRC spend and choose to simply discount for utility chips is going to wipe multipel trillion of western semi market cap and all the economic implications that entails so it might not even be bad idea.