skysight-inc/HackerNews huggingface dataset:
> It's not a complex language

You cannot claim this when even codebases with veteran C developers will be virtually guaranteed to have memory safety issues at some point.
I have just read one section of this, "The AI scientist'. It was fantastic. They don't fall into the trap of unfalsifiable arguments about parrots. Instead they have pointed out positive uses of AI in science, examples which are obviously harmful, and examples which are simply a waste of time. Refreshingly objective and more than I expected from what I saw as an inflammatory title.
Great minds think alike - we built wiktok.lovable.app a few months ago in Lovable as a fun experiment
Also, and it's striking to me that there never was a crackdown on this, but in a lot of countries, you cannot call yourself an engineer unless you have an engineering degree from a vetted higher-ed institution and are part of your provincial/state engineers' association.

For example, in N.S., your job title cannot contain the word engineer unless you're registered as an engineer with Engineers Nova Scotia, the provincial regulatory body. And to get the EIT status (engineer in training, the provisional period before becoming a professional engineer), you must hold a CEAB-accredited undergraduate degree. So, software engineers rarely exist and it's mostly software developers in N.S.
It's clearly true that the LLMS are 'stochastic parrots', but for all we know that might be the key to intelligence. It is in itself not a deep observation any more than calling your fellow humans 'microbial meatbags'.

Saying that LLMs are stochastic machines does not establish an upper bound for success.
Their agents too: https://www.youtube.com/watch?v=KX7f1PwXEWg
> At what point will we have to assume that any systems touched by doge are compromised/backdoored?

You assume it is compromised the moment they gain access.

See "A US Treasury Threat Intelligence Analysis Designates DOGE Staff as ‘Insider Threat’":

* https://www.wired.com/story/treasury-bfs-doge-insider-threat...

And "Treasury was warned DOGE access to payments marked an ‘insider threat’":

* https://www.washingtonpost.com/national-security/2025/02/07/...

* https://archive.is/https://www.washingtonpost.com/national-s...
This feels like banning plastic straws. It's an action that will create disproportional anger compared to the benefit.
Fitness functions are retrospective, so there is no "We should have done this differently."

The definition of fitness is literally whatever persists by reproduction.

Features and species that persist for a while and then collapse/disappear are a normal part of the process.
> In fact there isn't a single widely used language besides Java that feature checked exceptions.

Not in Java's form, but I'd argue Rust's Result type basically achieves the same effect but with less syntax. A function call can return an error variant, and the caller must handle the case (even if that's just propagating it up with `?`), as opposed to letting it silently flow up the call stack (which is more like a Rust panic).

And I'd argue that Rust's error handling is excellent. The programmer is always forced to acknowledge function calls which may produce an error, yet is also able to say "I don't care" without much syntactic overhead.
I wish it would! Although regarding graphics in Windows, I would ask Raymond Chen a different question: what is DT_DISPFILE anyway?

https://stackoverflow.com/questions/79399744/what-is-display...
> straight to social media drama.

It was a move of frustration due to having exhausted all other avenues. It wasn't his first action.
I followed the link, that's what he means by 'cool stuff that's missing':

> In short:

> The key to Noether’s theorem is the requirement that we can freely reinterpret observables as symmetry generators, and vice versa — in a way that’s consistent with the action of symmetry generators on both observables and symmetry generators.

> In classical mechanics this is achieved by a hybrid structure: a Poisson algebra, whose elements are both observables and symmetry generators.

> In an algebraic approach to quantum theory, this requirement singles out complex quantum mechanics. i =√−1 turns observables into symmetry generators, and vice versa.

How would one explain this to the audience of Quanta Magazine?
I feel like that’s the curse of most programming languages that end up mainstream and survive for a decade or two - some amount of legacy cruft or bad decisions that end up more or less set in stone is inevitable.
Interview with Donald Knuth, with his opinions on multicore CPUs
> they can’t give anyone orders and impose consequences for not following them

well, they also demonstrably did this?

but I'm pretty done with this "conversation"
> And now you've just got lots of different complications, like that seawater is very corrosive.

Is it as corrosive as lightning? All space elevators will encounter that problem pretty regularly.

We've been running cables under the ocean for over a century now, there's ways to address seawater corrosion and intrusion.
Don't "optimize" conditional moves in shaders with mix()+step()
I think I've made the case above that it's not merely about "being neurotypical", it's also about being steeped in a very specific culture. That peculiar use of "why did you apply" might as well be described as an idiomatic expression, a play on words that happens to be common in that well-defined context. If you aren't familiar with that usage because you are from a different cultural context (or even something as simple as a different "low-class" socio-economic stratum in the same society), you might misunderstand the question in the exact same way - or perhaps you'll grok it but you'll still be bothered by the implied "dishonesty" in it and be inclined to subvert expectations by starting with a straight and to the point answer, and then getting into the actual topic of why you think you were right to apply.
You slightly moved the goalpost here: I said women find hair attractive. That is not the same as saying women will not enter a relationship. I know this is a hot take and unpopular, but women historically have most of the time (and still do it today - albeit probably not to the same amount) entered relationships with men they don't find attractive.
Deep Dive into Yann LeCun's JEPA
Most novice programmers reject the complexity created by others in favor of their own.
Statistical truths based on observation of reality is the basis for science. Statistical truth based on the text on the internet is the basis for something else, and I would personally not like to call whatever that is science, or any truths established this way "ground truths".
> Given that government lawyers are unable to answer questions about who has access and what they're doing with it, I'd say that point has come and gone.

Which is the most basic question that any audit(or) will ask and that needs to be answerable for any security certification. If you don't know who has access to your system, or how it has been (potentially) changed, how can you be sure it's still your system?
But is it though? Because it's has been claimed for many many years that the west if falling (at least from 2008 on-wards) and yet - more people speak English than ever before, American culture (at least anecdotally) is more ever present and American tech corporations are 8 out of 10 most valuable companies in the world.

I guess that people always feel that the end is nigh.
Show HN: Neovim Plugin for iOS and macOS Development
Over two years ago, I began exploring whether it was possible to shift my iOS development to Neovim. It took me over six months to resolve all issues and figure out how to connect everything, creating an environment with all the features required for development.

After that, I decided to develop my own plugin to enable others to do the same. Since then, I have been developing apps for iOS and macOS using Neovim, for both my professional work and personal projects with no issues.

This change has significantly boosted my productivity, and I no longer have to deal with Xcode's flaws. I can accomplish 95% of my work without needing to open Xcode.

Before that, it seemed impossible to develop for Apple platforms outside of Xcode. I'm proud that I was stubborn enough to make it work after all those failures along the way.

Neovim is an amazing project <3.
the main reason why I el-you-vee love this is that it's what my first sketches in processing ( minus the obligatory "random" color generation on every mouse click ( somehow those colors where never really random ) ) plus some algo for extra splotches around curves, it looks like. a very simple starting point elevated to a super cool thing.
> Bob Nystrom worked on Dart at Google and wrote the amazing Crafting Interpreters book. Rob Pike referenced this article in his 2023 talk, Go: What We Got Right, What We Got Wrong, while discussing the trade-offs between CSP and coroutine-driven concurrency.

I know, which is the exact reason the reply states "uncharacteristically". And yet, it fails to acknowledge existing terminology and tradeoffs and just states at the end in a couple paragraphs how Goroutines shall deliver us all from evil (which could not be demonstrably further from the truth). Surely we need to expect better from one of the Dart's authors than forgetting to mention all the caveats virtual threading via stackful coroutines comes with?

And this completely ignores that Go applications end up having to reimplement .NET's task system system anyway and that Goroutines are poorly suited for "fine-grained" concurrency. Even the UX of Goroutines is bad. Want to return a value when one exits? Be sure to not screw up synchronizing and passing the data by hand. One must imagine Gophers writing all that boilerplate happy. I suppose, it's a preferred pastime to learning the internals and ceasing to post the same tired shibboleths.
Tailscale or pure WireGuard is cool.
Similar discussion (2024): https://news.ycombinator.com/item?id=42557098
Yes, in the article it says many structural engineers over the years have deemed it “unlikely” to have major issues.
> that accurately reflects their model of reality.

you are also seemingly anthropomorphising the technology by assigning to it some concept of having a “model of reality”.

LLM systems output an inference of the next most likely token, given: the input prompt, the model weights and the previously output token [0].

that is all. no models of reality involved. “it” doesn’t “know” or “model” anything about “reality”. the systems are just a fancy probability maths pipelines.

probably generally best to avoid using the word “they” in these discussions. the english language sucks sometimes. :shrug:

[0]: yes i know it is a bit more complicated than that.
Smart Connections[0] plug-in for Obsidian is worth checking out.

It does a really good job of indexing (with local or OpenAI embeddings) and RAG allowing you to chat with various models about your notes. The chunking and context algorithms it uses seem to be well designed and find most/all relevant details for most things I try to discuss.

It's well implemented and provides useful and interesting discussions with my journal/notes.

0 - https://github.com/brianpetro/obsidian-smart-connections
someone, once, attached different paint brushes to the branches of a tree, that could touch a canvas placed below.
The completely random, but compelling results, resemble nothing so much as a pollock
one of the few mad artists that I admire there work.
Also have lived with paintings done in his studio by an X's relative, who was attempting the same style, but in no way achiving what pollock himself did.
I do have a few random unknown artist works, that come close, and have a partial back story on two, and they were also, mad!
Mad but precious, and in this time there is little physical and financial room for people and the subculters they create to thrive, and so we are impoverished.
The app is cute, but it trivialises what was a huge reach into the unknown.
Nice to see that some companies still know what "Open" means.
The PKM space for neovim plugins is a surprisingly deep rabbithole but it can take quite a while to find what you need.

For completions and tagging https://github.com/Feel-ix-343/markdown-oxide works well for me and does pretty much everything I need.

There are also a glut of all-in-one solutions like https://github.com/nvim-neorg/neorg (org-mode for neovim) and https://github.com/epwalsh/obsidian.nvim.

Graphing is a bit harder because it doesn't intuitively match up with nvim's interface, but I'm pretty sure I saw something on Reddit the other day.
Ask HN: Are you considering learning Mandarin?
With China getting more and more influence, do think it will be useful or even necessary in your area?
More than just a plain fume event, if people in charge of aircraft had difficulty interpreting ATC directions and had no recollection of landing and taxiing that is a clear near miss. One more thing going wrong could have turned it into a disaster.

I am additionally surprised that captain’s death did not make it mandatory to report.
We are not stochastic parrots. Old components of our brain help “ground” our thoughts and allow things like doubt or a gut feeling to develop which means we can question ourselves in ways an LLM cannot.
Most of these examples/walkthroughs look like they have been generated by LLMs. They might be useful for teaching purposes, but I believe they significantly underestimate the amount of domain knowledge that often goes into data extraction, data cleaning and data wrangling.
Show HN: Ocal – AI Calendar That Schedules Assignments for You
We built Ocal, an AI-powered calendar that automatically schedules assignments as soon as they’re assigned.

We realized that most students don’t struggle with time management because they’re lazy—they struggle because time planning itself is an overhead. The mental effort of estimating task durations, figuring out when to work, and actually doing the work is non-trivial. So we decided to eliminate that friction.

How It Works:
1 LMS Integration (Canvas for now) – Ocal scans your assignments, extracts deadlines, and understands task complexity.
2 AI-Scheduled Work Blocks – Based on your habits (night owl vs. early bird), Ocal schedules the work comfortably ahead of deadlines—no more cramming.
3 Subtle Weekly Adjustments – Each week, Ocal subtly tweaks your schedule, nudging you toward your ideal workflow without a disruptive overhaul.
4 Social Scheduling (Coming Soon) – Friend people, see when they’re free/busy (privacy-first), and let AI find optimal times for study groups, workouts, or board game nights.

Why This Matters:
Most productivity tools still rely on manual scheduling—we don’t. Ocal makes time blocking effortless, helping students get work done early and reclaim time. No decision fatigue. No planning paralysis. Just execution.

What’s Next?
We’ve been building for a week. Ocal is not fully built for institutions yet, but it’s developed enough for people to start testing. If you’re a student or productivity geek, we’d love for you to poke around and tell us what works, what sucks, and what features you'd love to see.

Check it out & let us know what you think!
This is completely wrong, if anything an increase in the usage of LLMs to generate small pipelines will lead to increased demand for professional pipelines to be built. Because if any small thing breaks the dashboards/features break which is immediately noticeable. I think you'll see a big increase in the number of models a data scientist can create, but making those python notebooks production ready can't be done by an LLM. That's to say as analysts create more potential use cases, there will be more demand to get those implemented.

There's so much that goes into ensuring the reliability, scalability and monitoring of production ready data pipelines. Not to mention the integration work for each use case. An LLM will give you short term wins at the cost of long term reliability - which is exactly why we already have DE teams to support DA and DS roles.
I'm honestly not quite sure what you mean here (which I guess is fitting given the topic of conversation!). In case what I was talking about might have unclear, when I talk about feeling like the majority of people are different than me, I'm saying the idea of social norms being communicated implicitly, or at least being something most people seem to be able to infer from previous examples. To use the example of the interview given above, someone might be able to explain to me that when I'm asked that question, I shouldn't treat it as literal and instead given an answer that fits the expectation they'll actually have, but if the interview instead asks a slightly different question like "what's one thing you would change about your current job?", someone like me might not realize that this is _also_ not a question where it's good to give an answer like "I wish I got paid more for doing less work". For me, it's impossible to take all of the norms and expectations that I've learned over the years and apply them to an entirely new situation that I'm not familiar with, and that's not something that most people seem to struggle with as much as me.
I've Configure OpenBSD and FreeBSD for an IPv6 WiFi
The cost of inference seems like a major barrier in making these things work commercially. If you put one in the user facing flow you'll need an extraordinary amount of compute that scales extremely poorly in number of users, given that each query takes O(nm^2) where m is the number of model weights (many) and n is the number of tokens in the query. So it seems clear if each user session implies multiple LLM queries, those user sessions had better be exceptionally valuable. This seems like a completely different business with very different constraints and margins.

The problem is it doesn't seem like the value added is all that great. So how do you justify the ruinous cost? I would like to know more about how people actually intend on using these things profitably than to hear about how they're going to wake up and become "intelligent". Does anyone have any success stories actually using this thing? It's hard to find any discussion of this amidst all the bullshit hype, and it's really the only question--can you make money with this or not? And I don't mean raising billions in venture capital, I mean can you integrate these things profitably and sustainably into a website?
Ente[0] has this feature (locally run on mobile/desktop). It marks recognized faces in your gallery and then you can search for any combination of faces.

[0]: https://ente.io/
Have you never taken public transit before? You're one of today's lucky 10000: https://xkcd.com/1053/

Pre-smartphone, or if you don't have a signal, you check the posted timetable. In any decent good transit system, every stop, even the tiny bus stops in the middle of nowhere, has an up-to-date timetable on display. In a complicated area with several lines, they may also have a map showing all the different lines.

Or - ask a human! A bus is driven by a driver, and they aren't omniscient, but they do know stuff because they have to drive buses every day. Worst case, they could point you to the right place to find routes and timetables. If they've got an hour to kill before they drive the next bus back, they know that.

Post-smartphone, you get out your smartphone and check the transit operator's website or app. Transit apps are pretty useful: input where you want to go, and it tells you the fastest route to get there, including where you need to change to a different vehicle. I normally use the app from my local transit company (BVG), or the nationwide one (Deutsche Bahn) for long-distance trips; aggregators like Google don't always have the latest information. In Germany there is some kind of data-sharing program run by the government so that any transit company can give you accurate information for any other company's services and plan a route involving multiple companies. This might not be the case where you live.
Fully agree, in recent weeks I've also started to consider LLMs in a wider context, which is to destroy all trust in the web.

The enshittification of search engines, making social media verification meaningless, locking down APIs that used to be public, destroying public datasets, spreading lies about legacy media, the easiness of deploying bots that can sound human in short bursts of text... it's all leading towards making it impossible to verify anything you read online.

The fearmongering around deepfakes from a few years back is coming true, but the scale is even bigger. Turns out, there won't be Web 3.0.
this is absolutely well, very well done!
This would require massively more compute than regular pipelines...
> > > Good design is innovative

> > Why?

> a "good design" is indeed innovative in some way

Proof by repetition, I guess? You haven't answered the question in any meaningful way, just repeated the original assertion. It's still as unsupported as it ever was.
This is the original meaning of open in 1980's computing,

https://www.opengroup.org/

https://en.m.wikipedia.org/wiki/OpenVMS
There is "Sand Mafia" in India also. A lot of people have sadly lost their lives and the corruption / rot runs deep. https://en.wikipedia.org/wiki/Sand_theft
I'll agree on interesting, however I found it very difficult to follow.

Reading the landing page, I expected a link to get started. Took me some time to really register the links at the very bottom.

After finding my way into the lectures I got distracted by all the scrolling. Fortunately Reader Mode fixed that. However a few lectures in and I notice there's several videos I've missed...

However since I'm starting to approach the get-off-my-lawn age, I guess I'm not the target audience.
I know very little about cheese and such a stat seems just incredibly obviously untrue. I wonder how it made it past the dozens or more people who worked on the ad.
Gen Z unlikely savior of Japan's economy through 'oshikatsu'
I would be interested in hearing the reasons for why this bureau should be shut down, hopefully before this gets flagged.
The Investor Betting on People in Their 50s and 60s–Because Older Is Better
I generally take issue when "FOMO" is used. Could go with:

FOBBWIIBM - Fear of being blindsided when it, inevitably, becomes mainstream.

Or drop the "fear" altogether:

JOENT - Joy of exploring new territory.
There's a difference between software developers who glue together libraries to build cat picture voting sites and software developers who write real-time avionics firmware. The second type of developer can reasonably claim to be "software engineers" -- blueprints for a garden shed and for a skyscraper are distinguished by content, not medium.

Between those two limits the line must be drawn somewhere, and honest people will disagree about exactly where, but it seems reasonable to claim that people working in most software development positions of interest to Hacker News are closer to the latter than the former.

If you want to claim that junior developers are apprentices (journeymen? are apprentices interns?) and senior/staff/principal/whatever are engineers then that's fine (if idiosyncratic), but that's not what other people mean when they say or hear "software developers aren't engineers".
You are right! This is here to be used when your resources do not allow you to build full-blow solutions. Yes, I used LLMs to help create examples from my existing code, but they are based on things I have put in production when the client's resources were limited and wanted to move from point 0 to test out the potential of LLMs on their data.
I think that we are at a "generational inflection point".

I did the whole "it's cool to wear t-shirts to work" startup thing, and now that I'm a little older and the stakes are a bit higher in the office, It does feel a bit disrespectful to look "unserious".

So it's probably a perennial moment: ppl getting older. Maybe I'm boring now.

(Also, died at loss in your footer, and the MD timeline of discovery is cool -- submit it here!)