MurphyA/hacker-news huggingface dataset:
by mrnotcrazy | 2025-04-28 00:24:44+00:00
I'm working on an escape room! Initially I was working on a software/hardware bundle that I was planning to market to other escape rooms but I think that is the wrong approach. So I am going to build a bunch of modular stuff in my garage and eventually start my own, its been an awesome project so far! I want a more dynamic and action oriented experience so it might not really be an escape room anymore but I don't know what to call it yet.

Escape rooms are honestly... almost always a let down but the concept has a lot of potential and there are some really neat ones that standout like this local one where you pilot an airship https://www.portlandescaperooms.com/steampunk-airship

Once I build the best escape room on the planet, I can consider selling the tools.
by senordevnyc | 2025-04-28 00:24:50+00:00
This seems like a great example of someone reasoning from first principles that X is impossible, while someone else doing some simple experiments with an open mind can easily see that X is both possible and easily demonstrated to be so.

Y'all think that AI is "thinking" because it's right sometimes, but it ain't thinking.

I know the principles of how LLMs work, I know the difference between anthropomorphizing them and not. It's not complicated. And yet I still find them wildly useful.

YMMV, but it's just lazy to declare that anyone who sees it differently than you just doesn't understand how LLMs work.

Anyway, I could care less if others avoid coding with LLMs, I'll just keep getting shit done.
by AnthonyMouse | 2025-04-28 00:25:09+00:00
That's what happens if you sell the car. What happens if the thing thinks the speed limit on a 65 MPH highway is 30 MPH? Or you have some emergency situation where a higher travel speed is a matter of life and death?

Machines should never enforce laws because they don't have the ability to know when doing so would be unreasonable.
by thelaxiankey | 2025-04-28 00:27:24+00:00
i'm well aware of how medications are developed. i'm talking about biology, not medicine. there is a world of difference. pharma companies combine tech that gets developed in academic labs in clever ways to treat diseases. but make no mistake, most of these techniques come out of academia.

if you think CRISPR or P1 transduction were discovered outside academia, you are wrong. and this isn't even discussing stuff with no immediate clinical applications that is nonetheless important (jumbo phages, asgard archaea are hot rn)
by hansvm | 2025-04-28 00:28:06+00:00
Figuring out which of two things is bigger is hard. The article lightly touches on the two main reasons:

- Sometimes the definition is complicated. E.g., I'd accept a computer 10x slower at most tasks if a particular small subset were sped up even 2x. No symmetric mean (geometric, arithmetic, harmonic, or otherwise) will appropriately capture that.

- Nobody agrees on the definition. Even for very regular workloads, parsing protobufs is very different from old-school ML is very different from reversing the endianness of an unaligned data fragment. Venturing into even more diverse workloads muddies the waters further.

The article basically gives up and says that the geometric mean is the least bad option because it has some nice properties (ones I don't think anyone cares about for this purpose...) and because it's what everyone expects.

That latter argument is at least based in something sound, but I think the real point here is that attempting to come up with a single definitive "speed" is foolhardy in the first place. The only point is to compare two architectures, but without a particular context in mind no such linear ordering exists, and that's before we get to the difficulties in defining it appropriately even when given a context.
by addaon | 2025-04-28 00:29:42+00:00
A memory safe language is one for which (a) there is a subset of programs which can be statically proven to not perform unsafe memory operations at runtime and (b) no programs outside of this subset will be accepted. The set of operations that are considered to be unsafe can vary, but always includes writes to unowned memory, and often includes reads from unowned and/or uninitialized memory.
by yellowapple | 2025-04-28 00:30:11+00:00
> the relay storage volume scales only with the backfill window for consumers that drop briefly […] bluesky's feed gen post-dropping is about internal operation of their appview and not anything to do with network sync semantics

Gotcha; thanks for the clarifications/corrections. Good to know that the firehose bandwidth is a lot less than I thought (though 20Mbps can certainly add up to some hefty pricetags depending on how you're billed for traffic).

> if you're running an AppView for the bsky data you are likely keeping a copy of all bsky posts in a database, since fetching from PDSes on-the-fly is network intensive over a relatively small pipe, which is what i mean by write volume requirements.

Right, but how much of that actually needs to hit the disk? I'd imagine most appviews can readily get away with just keeping posts in RAM, and even if disk storage is desired (e.g. to avoid needing to pull everything from the PDSes if an appview server reboots), it ain't like the writes need to be synchronous or low-latency. A full-blown ACID-compliant DBMS is probably overkill.

It'd also be overkill to cache all posts, rather than subsets (e.g. each users' "Discover" and "Following" feeds), so I reckon that'd also reduce the in-appview caching needs further.
by madeofpalk | 2025-04-28 00:30:45+00:00
> Which means even if it is a mindless bot, by virtue of human psychology, the user will become more trusting and reliant on the LLM, even if they have doubts about the things the LLM is offering.

I'm sceptical of this claim. At least for me, when humans do this I find it shallow and inauthentic.

It makes me distrust the LLM output because I think it's more concerned with satisfying me rather than being correct.
by overfeed | 2025-04-28 00:31:05+00:00
To expand on what you said - you can post some grotesque things here as long as you don't provoke flagging or offending the ~90th percentile into down-voting your comment in the first 24 hours, and language plays a big part in this, such as hiding bigotry behind big words and playing into confirmation bias. Low-level down-voting can be countered if you can get <1% of HNers, who may be fellow-travelers in the fringe ideology to vociferously agree & up-vote your comment.

I think this is a side-effect of HNs voting rules, what counts as "adding to the conversation", and the limited window for voting down comments and unlimited time to vote up.
by RevEng | 2025-04-28 00:31:09+00:00
The article rightly points out that people don't enjoy just being reviewers: we like to take an active role in playing, learning, and creating. They point out the need to find a solution to this, but then never follow up on that idea.

This is perhaps the most fundamental problem. In the past, tools took care of the laborious and tedious work so we could focus on creativity. Now we are letting AI do the creative work and asking humans to become managers and code reviewers. Maybe that's great for some people, but it's not what most problem solvers want to be doing. The same people who know how to judge such things are the same people who have years of experience doing this things. Without that experience you can't have good judgement.

Let the AI make it faster and easier for me to create; don't make it replace what I do best and leave me as a manager and code reviewer.

The parallels with grocery checkouts are worth considering. Humans are great at recognizing things, handling unexpected situations, and being friendly and personable. People working checkouts are experts at these things.

Now replace that with self serve checkouts. Random customers are forced to do this all themselves. They are not experts at this. The checkouts are less efficient because they have to accommodate these non-experts. People have to pack their own bags. And they do all of this while punching buttons on a soulless machine instead of getting some social interaction in.

But worse off is the employee who manages these checkouts. Now instead of being social, they are security guards and tech support. They are constantly having to shoot the computer issues and teach disinterested and frustrated beginners how to do something that should be so simple. The employee spends most of their time as a manager and watchdog, looking at a screen that shows the status of all the checkouts, looking for issues, like a prison security guard. This work is inactive and unengaging, requiring constant attention - something humans aren't good at. When little they do interact with others, it is in situations where that are upset.

We didn't automate anything here, we just changed who does what. We made customers into the people doing checkouts and we made more level staff into managers of them, plus being tech support.

This is what companies are trying to do with AI. They want to have fewer employees whose job it is to manage the AIs, directing them to produce. The human is left assigning tasks and checking the results - managers of thankless and soulless machines. The credit for the creation goes to the machines while the employees are seen as low skilled and replaceable.

And we end up back at the start: trying to find high skilled people to perform low skilled work based on experience that they only would have had if they had being doing high skilled work to begin with. When everyone is just managing an AI, no one will know what it is supposed to do.
by linsomniac | 2025-04-28 00:32:08+00:00
>But AI doesn't think -- it predicts patterns in language.

We've moved well beyond that. The above sentence tells me you haven't used the tools recently. That's a useful way to picture what's happening, to remove the magic so you can temper your expectations.

The new tooling will "predict patterns" at a higher level, a planning level, then start "predicting patterns" in the form of strategy, etc... This all, when you start reading the output of "thinking" phases. They sound a lot likea conversation I'd have with a colleague about the problem, actually.
by kev009 | 2025-04-28 00:32:29+00:00
I'm not sure if you missed the point. HDL design work is done by simulation for countless iterations before ever making it to a physical prototype. ASIC prototypes come very late in the cycle and are usually a low digit number of revs. So the point is simulation carries you through most of the design feedback cycle, and a significant economic and technical effort went into industry automatic place and route, DRC/LVS, etc. I am also ignoring the human heavy side of layout especially around analog and RF which is more like PCB design still.

A PCB can be reworked by hand on site. And those revs can be incorporated cheaply as you say. So the need to do all this programmatically is lowered below the economic threshold to make it all plausible in most cases. This presupposes that modern PCB tooling is itself semi-automated and includes simulation capabilities, but an expert operator is doing a lot of the decision making.
by dymk | 2025-04-28 00:32:33+00:00
Last startup I worked at, the CEO would tell the team to go do X, Y, Z because he asked ChatGPT and it said so. Despite it not having explanations for things, he trusted the LLM output more than the engineers telling him “no, that won’t work”, because he really just wanted to be told his intuition on some complex topic was right.

I didn’t last very long there.
by Xylakant | 2025-04-28 00:34:33+00:00
Speeding is widely accepted, because it seems such a low level offense. 50km/h instead of 30, it’s only 20 more. But the physics are against you - the energy of the vehicle grows quadratic with the speed. At 30, you need about 18 meters to come to a stop. So you can prevent an accident if a person appears about 20 meters from your hood. At 50, you’ll run them over with a remaining speed of more than 30km/h. Speeding kills.
by senordevnyc | 2025-04-28 00:35:44+00:00
One of the frustrating things about talking about this is that the discussion often sounds like we're all talking about the same thing when we talk about "AI".

We're not.

Not only does it matter what language you code in, but the model you use and the context you give it also matter tremendously.

I'm a huge fan of AI-assisted coding, it's probably writing 80-90% of my code at this point, but I've had all the same experiences that you have, and still do sometimes. There's a steep learning curve to leveraging AIs effectively, and I think a lot of programmers stop before they get far enough along on that curve to see the magic.

For example, right now I'm coding with Cursor and I'm alternating between Claude 3.7 max, Gemini 2.5 pro max, and o3. They all have their strengths and weaknesses, and all cost for usage above the monthly subscription. I'm spending like $10 per day on these models at the moment. I could just use the models included with the subscription, but they tend to hallucinate more, or take odd steps around debugging, etc.

I've also got a bunch of documents and rules setup for Cursor to guide it in terms of what kinds of context to include for the model. And on top of that, there are things I'm learning about what works best in terms of how to phrase my requests, what to emphasize or tell the model NOT to do, etc.

Currently I usually start by laying out as much detail about the problem as I can, pointing to relevant files or little snippets of other code, linking to docs, etc, and asking it to devise a plan for accomplishing the task, but not to write any code. We'll go back and forth on the plan, then I'll have it implement test coverage if it makes sense, then run the tests and iterate on the implementation until they're green.

It's not perfect, I have to stop it and backup often, sometimes I have to dig into docs and get more details that I can hand off to shape the implementation better, etc. I've cursed in frustration at whatever model I'm using more than once.

But overall, it helps me write better code, faster. I never could have built what I've built over the last year without AI. Never.
by mobilejdral | 2025-04-28 00:35:57+00:00
And then this ties to estrogen, HRT is known to reduce the risk of dementia/AD (https://pmc.ncbi.nlm.nih.gov/articles/PMC10480684/).

PEMT (phosphatidylethanolamine N-methyltransferase) is what makes choline in the body, but it depends on estrogen.(https://pmc.ncbi.nlm.nih.gov/articles/PMC3020773/)
by taneq | 2025-04-28 00:36:17+00:00
“Bricking” isn’t a rigorously defined term, it’s more like “realtime” in the sense that it comes with an implicit “(for this particular user in this particular scenario)”. For most users a device is bricked if it doesn’t turn on and work when you press the power button. For most readers here, using dev tools to re-flash a bootloader would be fairly easy but if USB stops working it might be game over. I’m sure there are a few around who could de-cap an ASIC and circuit bend it back to life.
by moralestapia | 2025-04-28 00:37:42+00:00
>have this conversation [...] as early as possible

Yes, it could be one of the things you bring up on the very first talk you get around this, and it's much easier to do it early than anytime later.

"Hey, this thing you're telling me about, do you want my opinion or are you telling me because you want me to be a part of it?"

(if: want to be part of it) "Nice, have you thought about how much each one of us will get? I always prefer to do equal splits."

If equal splits or very close to that I might do it. If not, the deal would have to be exceptionally good from the start, e.g. "we'll give you 10% of a post Series A company that is already valued at XX million".
by SamBam | 2025-04-28 00:37:45+00:00
I was thinking this too.

They do talk about using FileZilla or Nextcloud to upload files, and mention using CMSes like WordPress, so maybe it's quite possible, just not a big focus.

I agree that making it easy for teachers, students, and anyone in the community making their own discoverable webpages would be a great aspect to this.
by mustache_kimono | 2025-04-28 00:39:31+00:00
> And for the thin-provisioned snapshotted subvolume usecase, btrfs is currently eating ZFS's lunch due to far better Linux integration.

Is this a technical argument? Or is this just more licensing nonsense?

> Think snapshots at every update, and having a/b boot to get back to a known-working config after an update.

I use ZFS and I have snapshots on every update? I have snapshots hourly, daily, weekly and monthly. I have triggered snapshots too, and ad hoc dynamic snapshots too. I wrote about it here: https://kimono-koans.github.io/opinionated-guide/
by pridkett | 2025-04-28 00:39:38+00:00
The State of Charge YouTube video that covered the announcement and visited a site in McKinney, TX indicated it did need the Walmart app[0].

Sigh. Plug and pay charging is so much better. It’s not like this is a Tesla only feature. Ford has thousands of chargers beyond SuperChargers that just work for plug and pay.

[0]: https://youtu.be/_UIVp8Upvj8?si=eX9EMWKi6sho4DnT
by -__---____-ZXyw | 2025-04-28 00:40:19+00:00
Just like they listen to the music they want, watch the movies they want, buy the products they want, and go to the websites they want..?

I don't think it's true for porn or for any of the above things that people "do what they want" in any serious sense of the term.

It might be true in some sort of world without advertising, where media is presented neutrally, and barriers to creating and sharing (porn, music, plays, books, etc) are low, and we all explore and pick what we liked from these media sources in a deliberate, thoughtful way.

But that is so very, very far from the world we're in, surely?

Or a different way to make the point, just compare a pre-internet and post-internet kid. What did pre-internet kids know of sex when they were 14 or 15? And post-internet? This is a quick and easy example, but surely it's a major shift?
by dtnewman | 2025-04-28 00:40:33+00:00
AWS lambda + API gateway. I use serverless to deploy to these.

If traffic is high, this could get pricy. For example, i have a site up getting about 20,000k visitors a day, hitting it many times each and it's probably costing me $400/month whereas a $50 server would probably do the trick (it's a temporary thing that i'm migrating away soon). But I have a bunch of smaller projects with a few visitors a day and the cost rounds to $0.

The nice thing is that it'll basically scale infinitely when you need it to.
by ForOldHack | 2025-04-28 00:41:16+00:00
Aquire a new tech, shart the sales team, say everyone should get one, shart the development staff and only have a single maintenance engineer, who is moonlighting, suck up all the profits, and then with the stroke of a pen from the brain addled director, killyhe product completely. Let them eat cake.

https://hackaday.com/2019/02/27/hack-my-house-raspberry-pi-a...
by mastazi | 2025-04-28 00:41:47+00:00
I'm the same, I started coding as a kid on an Amiga 500. But I never thought it would become my job. I studied a degree in communication and worked as a journalist first, then as a press agent. Later I decided to move to a different country where I could not work in PR or journalism due to language barriers so I went back to programming. Eventually I even went back to Uni and got a degree in IT because I felt that I had some knowledge gaps due to being self-taught. Going back to uni in my mid 30s was actually a cool experience (despite the fact that I had to study & work at the same time).
by alistairSH | 2025-04-28 00:41:55+00:00
Ha! I cut my teeth on Spec RX-7. I drove it to the track for a season and it was a terrible idea. The car was nominally legal (catalyst in place, full exhaust). But it was loud AF, the rollcage was dangerous on the street, and getting 4 race wheels in the back with a jack, tools, tent, etc was an endeavor.
by 999900000999 | 2025-04-28 00:42:35+00:00
I like programming for my friends. The moment money gets involved it goes to shit. Idea guys want you to program for free , and offer you something like 1% vested over 5 years.

They have you sign NDAs before you start working. The ideas are all really really stupid.

I do have my ideas, but I’m also humble enough to just accept I’ll probably never make any real money. I self taught my way straight to 6 figures ( back in 2016 when that still meant something). That’s enough really…
by ChrisMarshallNY | 2025-04-28 00:43:28+00:00
Speaking only for myself, I never wanted to be rich. It would have been nice to have the money, but I never wanted to make the sacrifices necessary.

I also didn't want to be used by some predator, to make them rich. I found a [less-than-perfect, but OK] company to work for, that had values I liked, and stayed there, for a long time. I got to hang with the really cool kids. I mean the ones that were so cool, no one knew who they were, because they didn't care about being cool. They just liked doing what they were doing, and they were the best at it.

I was the dumbest kid in the room, and I'm smarter than the average bear. I also got to play with some very cool toys.

But I was a manager, for most of that time, and I didn't want to give up coding. I didn't have a "shower clause" in my employment contract, so I spent a great deal of my extracurricular time, doing open-source stuff. I had an organization that could use my skills, so I worked with them.

Eventually, the cool ride was over (after almost 27 years), and I found myself ready to roll up my sleeves, and help make someone else rich.

But no one wanted me, so I was forced to retire, and I've never been happier.

I was just talking about this, yesterday, to a friend of mine, who sold his company, and is getting set to become a Man of Leisure. He's like me. He needs something to do, and I suspect that he'll do something cool.

I mentioned how upset I was, when I figured out that no one wanted me, but, after a year or so of following my own muse, I realized that I had been working at a state of chronic, low-grade misery, for over 30 years. I probably work harder now, than I ever did, drawing a salary, and I absolutely love it. This is what I've been working on, for the last month or so[0]. Still have a ways to go, but it's coming along great, and I've been learning a lot.

Here's a post that I wrote, some time ago, about how I like to approach things[1].

[0] https://github.com/RiftValleySoftware/ambiamara/tree/master/...

[1] https://littlegreenviper.com/miscellany/thats-not-what-ships...
by willmeyers | 2025-04-28 00:43:28+00:00
I updated the catalogue of movies and added some internal tools to my movies released on YouTube website: We Love Free Movies (https://welovefreemovies.com/). It's hard to share it because it gets flagged because of the name... But yeah, planning to add search, design touch ups, more movies, etc. this year.

Also working out the logistics of offering a microgrant to award people who want to make movies like this!
by platevoltage | 2025-04-28 00:43:46+00:00
I wouldn't say that it's making games worse. It's just that I can count the number of open-world games that I have enjoyed on one hand. I'm fine with just a new GTA game every decade or so. Zelda did it well, although, what do you even do after that besides reuse the map for a sequel, which they've already done? Or in GTA's case, pump out online content continuously, and print money. I preferred GTA 4, where they created 2 new narratives to play through on the same map, but I'm sure that was less lucrative. Then you have whatever Bethesda craps out any given year.

Personally, I enjoy a good sandbox game like Mario 64, or Hitman 1/2/3, or a game like Hollow Knight, while not technically an open world game, scratches the same itches.

They just cost too much time and money to do well.