MurphyA/hacker-news huggingface dataset:
by ThomPete | 2025-05-16 20:46:14+00:00
My way out of this was to start thinking about what can't the LLMs of the world do and my realization was actually quite simple and quite satisfying.

What LLMs can't replace is network effects. One LLM is good but 10 LLMs/agents working together creating shared history is not replaceable by any LLM no matter how smart it becomes.

So it's simple. Build something that benefit from network effects and you will quickly find new ideas, at least it worked for me.

So now I am exploring ex. synthetic predictions markets via https://www.getantelope.com or

Rethinking myspace but for agents instead like: https://www.firstprinciple.co/misc/AlmostFamous.mp4

AI want's to be social :)
by xivzgrev | 2025-05-16 20:46:21+00:00
in life and with people I think about a car, knowing when to go and when to stop

some people are all go and no stop. we call them impulsive.

some people may LOOK all go but have wisdom (or luck) behind the scenes putting the brakes on. Example: Tom Cruise does his own stunts, and must have a good sense for how to make it safe enough

What this author touches on is a chief concern with AI. In the name of removing life friction, it removes your brakes. Anything you want to do, just ask AI!

But should you?

I was out the other day, pondering what the word "respect" really means. It's more elusive than simply liking someone. Several times I was tempted to just google it or ask AI, but then how would I develop my own point of view? This kind of thing feels important to have your own point of view on. And it's that we're losing - the things we should think about in this life, we'll be tempted to not anymore. And come out worse for it.

All go, no brakes
by NoFunPedant | 2025-05-16 20:47:15+00:00
Yes, the Canon Cat had a built-in manual, and I checked the manual quite thoroughly. I learned to use the Cat after a fashion, but even when I understood the Cat a little bit, it still didn't make any sense to me. It especially didn't make sense that there were no separate files and no clear cut way to save your work. By design, the Cat had a single, infinite scrolling text workspace. Documents were separated by a special return code. The user never needed to save a file, because all actions were automatically saved. I now know that the Raskin's theory was that users shouldn't be bothered with thinking about saving or file structure, but at the time it was hugely confusing to me. Most of what the Cat did was invisible to the user. Raskin thought that saved users mental overhead, but all it did was give the user no feedback on what the computer was doing.

The Macintosh, by contrast, was quite transparent to the naive user. It was very easy to understand that if you saved a file, the file was represented by a little picture that you could move to a folder icon or a disk icon. No naive user of the 1980s had any experience with an infinitely long scroll, but the desktop metaphor of file and folder icons was easily understood.

The no-separate-document interface of the Cat was, I think, a huge mistake. That might have been the way Raskin thought people should use computers, but it was a greater conceptual leap than users could easily understand. Non-computer people who were used to typewriters were used to working on separate documents; they thought in terms of writing letters, memos, reports, and manuscripts, and they expected all these documents to stay separate objects.

In the section of The Humane Interface you quote, I think Raskin exaggerates the non-intuitiveness of the mouse. People in the 1980s were familiar with the concept of a pointing device through playing Pong and Centipede. Even before I'd seen a Macintosh in real life, I'd seen the Mac ads and knew what the mouse was supposed to do. As Raskin says, no one needs more than 10 seconds to understand a mouse. It takes a lot more than 10 seconds to understand the Canon Cat.
by asim | 2025-05-16 20:47:18+00:00
True. Now compare that to the creation of the universe and feel your insignificance of never being able to match it's creation in any form. Try to create the code that creates blades of grass. Good luck creating life. AI for all it's worth is a toy. One that shows us our own limitations but replace the word AI with God and understand that we spend a lot of time ruminating over things that don't matter. It's an opinion, don't kill me over it. But Dustin has reached an interesting point. What's the value of our time and effort and where should we place it? If the tools we create can do the things we used to do for "work" and "fun" then we need to get back to doing what only humans were made for. Being human.
by lo_zamoyski | 2025-05-16 20:47:41+00:00
The primary motivation should be wisdom. No one can become wise for you. You don't become any wiser yourself that way. And a machine isn't even capable of being wise.

So while AI might remove the need for human beings to engage in certain practical activities, it cannot eliminate the theoretical, because by definition, theory is done for its own sake, to benefit the person theorizing by leading them to understanding something about the world. AI can perhaps find a beneficial place here in the way books or teachers do, as guides. But in all these cases, you absolutely need to engage with the subject matter yourself to profit from it.
by Enginerrrd | 2025-05-16 20:47:57+00:00
Quanta magazine is one of my absolute favorite read-for-pleasure publications.

Scientific American filled a similar niche but used significantly less rigor. Physorg overly sensationalizes every single article and thus has zero credibility. Physics Magazine is an absolute gem but is limited in scope to physics and thus omits computer science, biology, and mathematics.

So quanta fills a niche for people interested in news from other fields without grossly overstaying results and is willing to go into just a bit more detail than usual. It's a wonderful niche for the curious and the source publications are usually just a click away.

Instead of rhetorically dismissing people that like it, can you explain what you do NOT like about it?
by w10-1 | 2025-05-16 20:47:59+00:00
Java is a great success story. Though, to be fair, James Gosling was the spark but has not been the steward.

Even as early as Java 1.1 and 1.2 he was not particularly involved in making runtime, library, or even language decisions, and later he wasn't the key to generics, etc.

Mark Reinhold has been the hand's-on lead since 1.1, first integrating early JIT's, HotSpot, the 1.2 10X class explosion, and has been running the team all the way through Oracle's purchase, making the JVM suitable for dynamic language like Kotlin and Clojure, open-sourcing, moving to a faster release cadence, pushing JVM method and field handles that form the basis for modern language features, migrating between GC's, and on and on.

As far as I can tell, everything that makes Java great has come down to Mark Reinhold pushing and guiding.
by inetknght | 2025-05-16 20:48:51+00:00
> Gunfire is insanely loud. Even a little .22 is louder than the apparent volume of heavier rounds in most film and TV. It's one of those things people can have entirely the wrong idea about if their only exposure to it is media.

Part of that is because the sound volume is just so drastically different compared to normally talking; microphones have trouble with it, audio amplifiers end up clipping [0], and most speakers would blow out if the amp didn't clip (especially for the larger guns). And, assuming none of that happened then, just as you would have on a gun deck, your listeners' ears would be damaged. So the sound of gunfire in media is quieted.

Most people simply aren't around guns in the first place, let alone firing guns (eg, going to a gun range with friends/family/etc even if you don't own a gun), to understand just how much media misrepresents it.

[0]: https://en.wikipedia.org/wiki/Clipping_(audio)
by entrepy123 | 2025-05-16 20:49:00+00:00
Are these significantly faster/better on 64GB or 128GB Apple silicon (over 36GB or 48GB)?

I've been reading that large contexts and large models are just painfully slow, even on the fastest and largest Apple silicon that money can buy.

So I wonder if this helps make more use of greater memory, or if really smallish models are still where it's at for Apple silicon, practically speaking.
by lubujackson | 2025-05-16 20:49:12+00:00
I went through this exact trajectory last year. Mid-40s with added weight of having a family as a sole earner, and feeling burnout for the first time in my life.

Things to do before you leave your current job: - make LinkedIn connections with all your co-workers. Generally co-workers accept those, even if they don't think you're great. The reason for this is to increase your number of "1st/2nd/3rd connections" on LinkedIn. Which likely doesn't matter, but hey why not. - Depending on where you live, you may be able to get unemployment if you quit or fired but not the other way around. So figure that out, as well as what health care looks like for you and plan accordingly. - Update your resume with your current projects etc. if you haven't done that lately.

Now once you are free of your current job, don't do any coding for a few months. No interview prep, no learning AI, none of it. Exercise and eat right, as others have said. Have a routine and maybe explore those 2 non-tech things.

But give yourself a calendar and come back to things after you've let the burnout fade a bit. Don't rush back after a month because you start to get anxious - your body physically needs to recover.

At this point, like it our not, I'd spend time getting comfortable with Cursor and vibe coding tools. Build a thing, see how it works, play around. You won't be able to avoid AI so see how it can help you with what you already know how to do and where it can't help.

If you suck at interviews and leet coding, don't worry about it. Take some interviews, bomb them. The goal is to develop a thicker skin, which is the first step. Also, if a company's hiring culture is steeped in crap you hate, you will probably hate the job anyway. If they as you to do a weekend project, prefer to do that. That is likely where you will shine. Plus, it is a good way to practice when unemployed.

Lastly, lean into your strengths - generalists and graybeards tend to be great at startups because they can pump things out and understand the big picture. Look for roles on sites like WellFound rather than LinkedIn. If you use LinkedIn, really only jobs through recruiters bear fruit nowadays.
by curl-up | 2025-05-16 20:49:13+00:00
I am in no way disputing that some people would feel that way because of AI, just as some performing classical musicians felt that way in the advent of the audio recorder.

What I am saying is that (1) I regard this as an unhealthy relationship to creativity (and I accept that this is subjective), and (2) that most people do not feel that way, as can be confirmed by the fact that chess, go, and live music performances are all still very much practiced.
by thewebguyd | 2025-05-16 20:49:49+00:00
I'm with you there.

People complain about how crap UX is now, and how computer illiterate the general populace has become but I firmly place the blame on forcing the web into an application delivery platform, abandoning all operating system HIG and conventions so that every app is now it's own unique snowflake that breaks conventions.

IMO people would struggle less if it was all native apps that followed the OS. You learn your operating system's conventions and shortcuts, and those translate into every app you run - but then marketing people got their hands in things, and suddenly everything had to be branded and unique, and we are worse off for it.
by gary17the | 2025-05-16 20:50:48+00:00
> I haven’t interviewed in years and get extremely anxious in interviews.

If you are a programmer, the hiring process these days is an unbelievable screw-up with no shred of professionalism whatsoever in many, if not most, cases. Either make a conscious effort not to let it get under your skin or start only with job offers that specifically outline the hiring process as one with a take-home coding assignment, as opposed to all the pair-programming or white-boarding nonsense. Otherwise, it will hurt and you will get discouraged. Also, consider starting to build up reputation on Upwork, etc. as a freelancer. As you gain more clients down the line, you can always just drop the ones you do not enjoy working for.
by therein | 2025-05-16 20:51:07+00:00
Yeah, their metrics for it being good sounds so out of touch that their pride seems cringe-worthy.

If you take rebelliousness as "this doesn't follow the conventions we are used to", subculture as "this is weird in its own way" and modernity as "this reminds me of new modern design stuff I see", it makes it clear they aren't necessarily praises.
by lucb1e | 2025-05-16 20:51:19+00:00
> Everyone likes their mother tongue better

Speak for your own mother (tongue)! I think there are (many) better languages than my mother tongue but I haven't been able to convince the natives of this yet. The oscillate between catching on and regaining national pride (we're currently in a nationalism phase, where they're pushing to teach more in dutch again rather than a language everybody understands and needs for research and business anyway, source: https://www.universiteitenvannederland.nl/actueel/nieuws/uni...)

> But like many delicacies, it is an acquired taste

Why say lot word when two word do trick? Stockholm syndrome!
by _7acn | 2025-05-16 20:51:19+00:00
My experience is that sending out CVs and searching for job postings didn't yield any results in my case. All the recruitment processes I've been through came from someone finding my LinkedIn profile and reaching out with a job offer. So, if you have general skills but lack specialized ones, I think the best approach is to tailor your profile to specific job offers and wait for someone to contact you.

I've never done more than 1 profile myself because I have just one strong skill —good knowledge of SQL Server — and my profile is built around that. If I had more skills, I wouldn't list them all, instead, I'd precisely target specific job postings.

Besides SQL Server, I obviously know the basics of other things and have decent general IT knowledge, but I don't mention those skills on my CV or LinkedIn at all.

Simply treat your profile and CV like you're optimizing a website for SEO, targeting specific keywords. That's my advice.

Imagine an average recruiter from a foreign country looking for candidates for a specific position. Make your profile in a way that, first, it appears in their suggestions (through the algorithm/keywords), and second, when they visit it, even without deep IT knowledge, they can easily see that you're a fitting candidate for the role they're trying to fill.
by EvanAnderson | 2025-05-16 20:51:29+00:00
> Our civilization desperately needs a way to modify modern microelectronics at home or at least in a well-equipped repair shop.

I'll take consumer protection regulation, at least in the short term.

I wish manufacturers were required to clearly inform consumers which products are sold versus rented, self-hostable versus tied to hosted services, or crippled from running Free software by firmware locks. That would allow a market for freedom-respecting products to actually develop to a reasonable size, and not just to be a fringe thing.
by kmacdough | 2025-05-16 20:51:50+00:00
> Will it just allow me to run let’s say a model with a 2048 token context window with a 4-6k context window

It reduces the memory footprint of a particular model. You can do what you like with that. Extending the context window post-training isn't trivial, so unless you know what you're doing, you'd be better off finding a model trained on a larger context window.

Many uses for local models like working offline or privacy/security. Most folks, though, are using it to experiment with tweaking models.
by brailsafe | 2025-05-16 20:52:57+00:00
I've heard similar accounts, and anecdotally holds up, although my experience travelling for work specifically is limited. Incidentally, as a Canadian, I've been searched many more times, if not 100% of the time, coming back from the states than going in. Security theater in both directions though for sure, just looking for a slip up. Going in to the states, I once had a slightly vague answer about where I was staying because I'd planned to camp on a long road trip. They pulled me into the lineup and then asked me again, I tried explaining but they just wanted an address and hinted as such, so I just google searched a hotel in front of them and gave them that. They've got boxes to check.
by carlosjobim | 2025-05-16 20:53:04+00:00
There's people who count days instead of months and dates, so called "ordinal dates". Military and flight are some examples.

There's people who count weeks instead of months and dates. "We're visiting my parents when we have our vacations in week 28". Incredibly annoying.

I think our modern calendar is a result of when sun cults and moon cults mixed in the Mediterranean. The farther North you go, the more important are the yearly seasons (sun). They determine everything and are deeply embedded within the soul of people. Spring - summer - autumn - winter. Those are the important phases.

Then the farther South you go, the less important are the yearly seasons and the better way to track time is the moon. Especially as women's fertility is tied to the moon phases. So months become the standard of measure and are then conveniently divided into four weeks (28 can only be divided by two or four).
by matheist | 2025-05-16 20:53:46+00:00
Looks interesting! Is there any intuition for why this should be the case? Did you discover it via that intuition, or just random experimentation?

A note, your install script appears to still have a placeholder at the "apply patch" step. A suggestion, might be more user-friendly to fork llama.cpp and then include that as a git submodule rather than make it a "git clone and apply patch" step.

A further note, everyone and their dog has a different local python set-up, might be nice to let people separate the llama.cpp stuff from the python stuff rather than bake in a dependence on homebrew python.
by montebicyclelo | 2025-05-16 20:53:46+00:00
My thoughts are that it's key that humans know they will still get credit for their contributions.

E.g. imagine it was the case that you could write a blog post, with some insight, in some niche field – but you know that traffic isn't going to get directed to your site. Instead, an LLM will ingest it, and use the material when people ask about the topic, without giving credit. If you know that will happen, it's not a good incentive to write the post in the first place. You might think, "what's the point".

Related to this topic - computers have been superhuman at chess for 2 decades; yet good chess humans still get credit, recognition, and I would guess, satisfaction, from achieving the level they get to. Although, obviously the LLM situation is on a whole other level.

I guess the main (valid) concern is that LLMs get so good at thought that humans just don't come up with ideas as good as them... And can't execute their ideas as well as them... And then what... (Although that doesn't seem to be the case currently.)
by yongjik | 2025-05-16 20:54:22+00:00
That's just past with its rose-tinted glasses. It was easy for someone to master the machine when that someone was a university researcher or a lone gamer, the most precious resource stored in the machine was saved term projects, and either it was not connected to anything else, or connected to fellow university researchers.

The stake was low, because nobody could use your computer to drain your bank account. And someone who would "prank" your computer beyond the social norm would get a stern talking to.

Computers these days have to support your grandma making hotel reservations online without her entire financial information being sent to hackers in Eastern Europe. They're doing jobs that 70s OS designers never thought about. It's a different world.
by kragen | 2025-05-16 20:55:20+00:00
To be concrete about this, http://canonical.org/~kragen/sw/dev3/forkovh.c took 670μs to fork, exit, and wait on the first laptop I tried it on, but only 130μs compiled with dietlibc instead of glibc, and with glibc on a 2.3 GHz E5-2697 Xeon, it took 130μs compiled with glibc.

httpdito http://canonical.org/~kragen/sw/dev3/server.s (which launches a process per request) seems to take only about 50μs because it's not linked with any C library and therefore only maps 5 pages. Also, that doesn't include the time for exit() because it runs multiple concurrent child processes.

On this laptop, a Ryzen 5 3500U running at 2.9GHz, forkovh takes about 330μs built with glibc and about 130–140μs built with dietlibc, and `time python3 -c True` takes about 30000–50000μs. I wrote a Python version of forkovh http://canonical.org/~kragen/sw/dev3/forkovh.py and it takes about 1200μs to fork(), _exit(), and wait().

If anyone else wants to clone that repo and test their own machines, I'm interested to hear the results, especially if they aren't in Linux. `make forkovh` will compile the C version.

1200μs is pretty expensive in some contexts but not others. Certainly it's cheaper than spawning a new Python interpreter by more than an order of magnitude.
by thewebguyd | 2025-05-16 20:55:36+00:00
> And after all that, your company gets hacked through a misconfigured router.

Or a more likely scenario - some dev with admin on their machine grabs a malicious NPM package, EDR doesn't grab it because they successfully lobbied to have certain directories exempt for performance reasons (like DevDrive on Windows, or WSL). SSH keys get stolen, and despite all the fancy security products, the environment is still a mess (which is why there's so many products to cover up that fact) so the dev actually has keys to prod, then you're hosed.

I've seen my fair share of orgs with a plethora of security "solutions" and yet fail to understand some basic principles like least privilege or separation of concerns and think all their security software is going to save them.
by codedokode | 2025-05-16 20:55:38+00:00
The react's algorithm of detecting changes is based on rebuilding a Virtual DOM tree (i.e. recalculating all components) and comparing that tree to the previous one. It is done, as I understand, every time someone calls update() or similar method on a component.

So React won't cause performance issues only if you have few model variables or manually optimize the code by using immutable data structures (which have their own performance issues) and pure components.

For comparison, Vue detects changing by wrapping all model variables with proxies and linking them to UI components that use them. This has an advantage of not having to recalculate everything and disadvantage of having an overhead for using proxies and creating a dependency graph. Also, having to deal with proxies adds more pain for the programmer.