Is that really the problem, though, or has the audience simply changed? It seems to me that the thoughtful deep dives of years past are still being produced, but they're buried under a much larger volume of lighter content. More importantly, many of the people working at the forefront of technology and product development appear to have moved to private communities such as Discord, Slack, and similar groups, perhaps in part because of NDAs.
Wonderful work by Mr. XKCD (Randall Munroe).
This was published in 2011 when there was "some" misinformation in the U.S. press about the Fukushima nuclear accident.
Based on this chart some proposed to use "bananas" as unit of radition (equivalent to 0.1 uSv).
So (from this chart) one flight from New York to LA exposes you to 400 bananas worth of radiation.
Right.... but it is also an industry that provides an insane amount of (often well paying) jobs to a large amount of people to do "make work", admin tasks.
Reliable details are hard to come by, but some estimations are that more people in the industry are doing admin tasks than instead of providing care, admin tasks that will be reduced drastically once the industry is streamlined.
Once we get affordable care there will be less people who can... afford.
Feels like their job is mostly to enrich the corporations profiteering from these inefficiencies, they're doing admin fighting the sick and dying who also gained the job of admin of fighting them (a job thrown at them to - in a lot of cases - literally save their lives, financially and physically).
> Once we get affordable care there will be less people who can... afford.
This just plainly isn't true. The US is unique in the way it doesn't have affordable public healthcare, but the rest of the western world doesn't have an affordability problem because of less bean counters scamming patients.
That sounds really cool, can you expand a bit on the workflow you used: what format were the 360 pictures in and how did you convert that into data that this Python library uses ?
It appears to me that this is the same pattern you often see when junior employees are given one or more resources intended to help them succeed. Despite having access to those resources, there is frequently no shortage of complaints about how incompetent people are, that they "should know" esoteric home-built sowtware patterns or business knowledge without being told or that they failed to perform a task in the one specific way that someone considers the "correct" approach.
Let my karma burn for saying this:
Maybe it is time to let this go man. These comments are really the new incarnation of "grammar policing". (1)
They don't add anything of value, did the author use an LLM to fix his prose but no useless slop was added in the process: who cares ? Is the article useless slop: fine, downvote it to oblivion.
(1) For those not old enough to remember that wonderful practice please use your nearest LLM to find out or, you know, visit a library and do your own research.
Thank you!
Text is not the main part of this repo. The main part is the technology and the list of experiments (and some useful knowledge I got from this project, haha). I have always been bad at writing or editing text (in both my native language and English), but without text it is impossible to share this project online.
Text was the last and most difficult part for me. It is not perfect (and this project is not perfect as well), but I believe it does the job of communicating my ideas
100% agree. We're on Hacker News. We should be open to people who aren't native English speakers using LLMs to help them communicate their ideas and more importantly, cool projects without getting dragged for AI speak in the text.
I don't know what the author's native language is, but I assume it's something I'd need machine translation for anyway. Having it in good (if not Nobel prize level great) English is much easier - and will probably be easier to find again via search.
Because it's a strong signal of AI slop. Why put in more work than the "author" did?
If the author generated text that required no effort, and has no understanding of the contents of the material generated, and no self-awareness of their behavior and how the audience will receive it, it definitely doesn't warrant wasting a single second reading it.
Now, granted, maybe they did review it, maybe they did understand it, maybe they did know how it would be received and merely made a mistake, but how are we to know? It quacks like a duck.
That's like inhaling a virus to see if it's contagious. Reading text generated by a model tuned with RLHF is a dangerous pastime. It's all too easy to reach past a human's critical thinking and push the pleasure buttons. Uncanny valley is uncanny for a reason. As social monkeys we instinctively screech danger warnings at each other; AI slop gets the same treatment as an alligator pretending to be a log.
Saying that something is thought terminating is thought terminating, it's the laziest "I win" bullshit approach ever. A more nuanced approach: don't produce slop and people won't dismiss it as lazy bullshit either.
No, that's not true at all. Thought-terminating cliches cause you to stop thinking; they give a quick shortcut that let's you be dismissive. That's what "AI slop" is, when someone bestows the moniker on a piece of prose that has "It's not this, it's that" in it.
Look, there's is a wide variety of work being produced with AI, all the way from exceptional professional work to total trash done by amateurs. Painting all over those efforts with the same brush of "AI slop" attempts to avoid the thought necessary to process the nuance in each individual situation. In fact, folks that use "AI slop" enjoy being able to dismiss AI output as quickly as possible; they seem to be quite happy to forgo whatever insights might be present in such work. But let's not for a moment pretend it's not a crappy heuristic.
Through this lens, dunking on a piece of prose because it has some trace of LLM processing seems both useless and uninsightful, which is why I'm rallying against it as thought-terminating. Do the thinking to determine whether what you're reading is valid. Saying that it has tells that an LLM might have contributed is not sufficient evidence to do that, and it's also something anyone can do, it requires no skill or insight, and makes for boring discussion. Zero curiousity, 100% dismissive.
Yes, it’s dismissive, intentionally and abrasively so. Because the author is being disrespectful to the reader, expecting them to put more effort into it than they did. I will happily be uncurious about a text the author couldn't even bother to proofread and clean up. Life is finite, LLMs could generate more text than I could ever possibly read, there has to be a quality filter we all apply and I’ve drawn my line in the sand.
You’re arguing in favor of what I view as pollution. I’m not lacking thought, it didn’t terminate, you just value slop for reasons I don’t.
It's not low effort. The author had to write in English, not their native, and then used LLM to polish it. The sentence itself conveyed a real point. They cared how their article came across. That's much more effort than the boring "Claude was here" comment that took a second to write but costs real energy to appear, and once again spurred a worthless debate.
> Is the article useless slop: fine, downvote it to oblivion.
You can’t downvote submissions on HN, only flag them. Identifying when text was written by LLMs is a useful signal. Maybe you don’t like these repeated comments, but I’d bet the people making them hate even more that they feel they wasted their time reading it.
This attitude will just cause people to write the same thing with AI and then ask it to strip out all the tells. I found it works just fine, but then you push usage underground, making it harder to detect, which isn't in your best interest, assuming you want to be able to detect and avoid low-effort writing.
I think the point was that Python, as a language and ecosystem, has experienced a number of breaking changes over the years. In practice, that means code written only a few years ago may no longer run without specific versions of Python and a collection of dependencies, many of which have since been replaced by newer, incompatible implementations.
What I appreciate about the traditional shell languages is their remarkable stability. Shell scripts written in 2000, or even earlier, are often still able to run today with little or no modification. By contrast, Python applications frequently require recreating a historical runtime environment, including older language versions and dependencies, many of which have accumulated significant security vulnerabilities over time.
Interestingly, apart from the various shell languages, Perl is probably one of the strongest alternatives in this regard. The Perl community has placed a high value on backward compatibility, allowing older code to continue functioning while the language itself remains actively maintained and up to date.
I basically agree with these tradeoffs (you should never be pulling in dependencies outside the builtins), but let's look back to GP:
> Comparing the shell to C, Go, Rust, Python, or JavaScript is crazypants. It has a different job than those, so of course it will look and feel different!
The point was just a small one, that Python is not like the others. C, Go, and Rust do not come with REPLs. Node is plausible to use as an OS shell but I've never heard of anyone doing that. Python is the only one of those I've used as a shell or have heard of others using as a shell.
Again, I'm not advocating for Python as a good general-purpose shell. I'm only making the small claim that C, Go, Rust, and (to a smaller extent) JavaScript cannot be be used like bash. Python could be used as a shell.
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