MurphyA/hacker-news huggingface dataset:
by xtrememarketers | 2025-07-05 05:37:53+00:00
For a 2025 self-hosted photo library with local AI, a great stack is PhotoPrism or Immich running on Docker with local storage (NAS or server). Both offer built-in face/object detection without cloud reliance, using local TensorFlow or custom models. Add a reverse proxy like Nginx for HTTPS, and use a GPU for faster tagging. Deployment is easy with Docker Compose on Raspberry Pi or x86 servers. For managing costs on gear or upgrades, try this handy Percent Off Calculator (https://www.calculate-percent.com/) to figure out your savings quickly.
by macinjosh | 2025-07-05 05:38:47+00:00
It is hilarious to me to be reading about city folk being amazed at a few coyotes and an owl. In Nebraska coyotes are vermin and you shoot them on sight if they are on your farm for all the trouble and danger they can cause. We used to go out on the property and call them for target practice.

edit: lol at the downvotes, welcome to the real world?
by aspenmayer | 2025-07-05 05:40:02+00:00
Related:

Ishkur's Guide to Electronic Music

https://music.ishkur.com/

Previously:

https://news.ycombinator.com/item?id=44470331

https://news.ycombinator.com/item?id=37919241

https://news.ycombinator.com/item?id=25083516
by troupo | 2025-07-05 05:40:49+00:00
> That's not my point. How many of those lists are correct? (ignoring the fact prompting a LLM for lists is a bad idea, let alone local ones)

> Yes. That's missing the forest for the trees, though.

So, what is your point and forest?

That there exists some non-deterministic accurate LLM with a 100% correct training set which will always produce the same answer if you ask it 2x2 (where asking is somehow different from prompting)?

- Does it exist?

- Where? (considering that the world at large uses chatgpt/claude/gemini)

- what's its usefulness beyond 2x2?
by Ashoka_rkt | 2025-07-05 05:41:05+00:00
AI companies are spending millions to get the laws they want.

They're not trying to cure cancer, or save America.

These companies want to make $100 billion overnight, and they're willing to sponsor dangerous laws to make it happen. -----

More Perfect Union is an Emmy-winning, nonprofit newsroom whose mission is to build power for working people. Here’s what that means: We report on the real struggles and challenges of the working class from a working-class perspective. We attempt to connect those problems to potential solutions. We report on the abuses and wrongdoing of corporate power. And we seek to hold accountable the ultra-rich who have too much power over America’s political and economic systems.
by benreesman | 2025-07-05 05:42:13+00:00
Bare metal is priced like it always was but is mad convenient now. latitude.sh is my favorite, but there are a bunch of providers that are maybe a little less polished.

It's also way faster to deploy and easier to operate now. And mad global, I've needed to do it all over the world (a lot of places the shit works flawlessly and you can get Ryzen SKUs for nothing).

Protip: burn a partition of Ubuntu 24.04 LTS which is the default on everything and use that as "premium IPMI", even if you run Ubuntu. you can always boot into a known perfect thing with all the tools to tweak whatever. If I have to even restart on I just image it, faster than launching a VM on EC2.
by udev4096 | 2025-07-05 05:42:16+00:00
What? Satoshi's last publicly known email was on April, 2011 to Gavin [0], stating the following:

"I wish you wouldn’t keep talking about me as a mysterious shadowy figure, the press just turns that into a pirate currency angle. Maybe instead make it about the open source project and give more credit to your dev contributors; it helps motivate them."

Also, let's not forget, it took BTC ~1.5 years to gain any amount of traction at all. Nakamoto was in for a long run and his sudden disappearance is always going to be mysterious

[0] - https://www.bitcoin.com/satoshi-archive/emails/gavin-andrese...
by kristopolous | 2025-07-05 05:43:00+00:00
You're looking at it wrong. There doesn't need to be a generalizable, embarrassingly parallel, computationally lower class, key reduction.

Just this specific implementation with these specific wallets maybe using a version of the btc code with a small recently discovered bug that existed say for 3 months in 2011

You can have something extremely localized and get this result. And this is exactly the behavior people have long game theoried would happen under such a scenario.

You're implicitly making the claim that just because you can't find something widely discussed in literature than any optimization of any kind is impossible and nobody would ever dare to keep an advantage in stealing bitcoin wallets secret.

Stuxnet is way less plausible than this yet that happened.

People have been trying to do this for a decade and have in aggregate thrown probably north of $100 million into it through separate efforts. The idea of someone finally succeeding is kind of expected.

Again the only claim I'm making here is that this is not only a non-zero chance, but, in my mind, an over 90%.
by arendtio | 2025-07-05 05:43:11+00:00
For me, it is a different experience. Yes, it takes time to provide the LLM with the necessary context, but overall it can save me 3-4 times the time I would have invested. Maybe I am just slower at software development myself ;-)

However, the work you do is indeed more that of a product owner than that of a developer. To avoid hallucinations, providing extensive documentation and allowing the LLM to perform test-driven development can be a game-changer.

When you do that, generation time is highly correlated (negatively) with code quality. So when the AI solves the tasks quickly and easily, you have a good chance of it generating good code. As soon as the AI has to try and try again to build something working, you should be very skeptical of the result.

Over the past months and years, I have used this method, and because it is somewhat reproducible, you can see the progress that LLMs are making. Sessions where the model does stupid things are becoming fewer, and sessions where the model finds a good solution become more frequent.
by xtrememarketers | 2025-07-05 05:43:37+00:00
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by dworks | 2025-07-05 05:43:52+00:00
LLMs must be handheld by humans and cannot function autonomously. There are two main forms of handholding or human supervision:

Synchronously, where we prompt a CLI or chatbot interface and verify or manipulate its return before putting it to use.

Asynchronously, in the form of code that implements RAG guardrails, examples in prompts, evals, a workflow that uses a second model to correct the output of the first, etc.

In fact, you can infer a principle that I have had in mind for some time now from this need for human supervision:

Output generated by language models through automated workflows must never be exposed directly to the end-user. [1]

These organizations have obviously missed the human QA step and went with an autonomous workflow publishing the generated text directly to the website. They should have had humans synchronously in the loop, validating and editing every string after its generated.

Obviously what caused this is the overselling of LLMs as "intelligent".

--- [1] When you prompt a chatbot while working on a new marketing strategy, you are not the end user of its output. Your organization is. You wouldn’t dream of copying the raw output from ChatGPT and present it as your new strategy.
by armada651 | 2025-07-05 05:44:10+00:00
> If I don't type it into the editor myself, I'm not putting my name on it. It is not my code and I'm not claiming either credit nor responsibility for it

This of course isn't just a moral concern, it's a legal one. I want ownership of my code, I don't want to find out later the AI just copied another project and now I've violated a license by not giving attribution.

Very few open-source projects are in the public domain and even the most permissive license requires attribution.
by kouteiheika | 2025-07-05 05:47:38+00:00
It' $4.2k on Newegg; I wouldn't necessarily call it reasonably priced, even compared to NVidia.

If we're looking at the ultra high end, you can pay double that and get an RTX 6000 Pro with double the VRAM (96GB vs 48GB), double the memory bandwidth (1792 GB/s vs 864 GB/s) and much much better software support. Or you could get an RTX 5000 Pro with the same VRAM, better memory bandwidth (1344 GB/s vs 864 GB/s) at similar ~$4.5k USD from what I can see (only a little more expensive than AMD).

Why the hell would I ever buy AMD in this situation? They don't really give you anything extra over NVidia, while having similar prices (usually only marginally cheaper) and much, much worse software support. Their strategy was always "slightly worse experience than NVidia, but $50 cheaper and with much worse software support"; it's no wonder they only have less than 10% GPU market share.
by jnfno | 2025-07-05 05:49:16+00:00
I’ve been coding 5+ a day since the late 80s

And I agree. Because ultimately we don’t need that much code in the first place. We need robust data sets.

AI models will enable the data driven machine state dream. Chips that self improve models will boot strap from them and rely on humans to iteratively improve updates.

Coding like it’s 1970 in the 2020s and beyond is not that high tech.
by bepitulaz | 2025-07-05 05:51:14+00:00
Open the app and open Logic Pro. Create a MIDI track on Logic, try waving to the app it should automatically receive MIDI message from all channels and all MIDI devices.

Then if you want to filter the track to receive specific MIDI channel from specific device, for example AirBending channel 2, then find it in the dropdown in the MIDI inspector section in the same MIDI track.
by PoshBreeze | 2025-07-05 05:53:46+00:00
Nvidia is the high end, AMD is the mid segment and Intel is the low end. In reality I am playing 4K on HellDivers with 50-60FPS on a 6800XT.

Traditionally the NVIDIA drivers have been more stable on Windows than the AMD drivers. I choose an AMD card because I wanted a hassle free experience on Linux (well as much as you can).
by orbital-decay | 2025-07-05 05:55:17+00:00
>So, what is your point and forest? That there exists some non-deterministic accurate LLM with a 100% correct training set which will always produce the same answer if you ask it 2x2 (where asking is somehow different from prompting)?

As I already said: modern LLMs mainly map a single input idea to a single output idea. They might express it in slightly different ways, but it's either correct or incorrect, you can't easily turn an incorrect result into a correct one by rerolling. If you spend any time with Gemini/o3/Claude, you understand this from the first-hand experience. If you know what current RL algorithms do, you understand why this happens.

An ideal LLM would learn one-to-many correspondence, generalizing better, and that still won't be any problem as long as the answer is correct. Because correctness and determinism are orthogonal to each other.
by palmotea | 2025-07-05 05:57:04+00:00
> I think I'm satisfied with the very simple reason that raising kids is hard work. Most people feel like 1 kid already gets their hands full. That's really it IMO. Whenever it was that joint families split up into disparate nuclear families, obviously the load of raising say 5 kids that was being shared among 20 people, suddenly fell on just 2 people.

I think you're falsely assuming that, over history, it has taken a constant amount of effort to raise a child. I recently read an aside in some recent article about birthrates that current-day American working mothers spend as much time on their kids as 1970s-era stay-at-home mothers. For that to be true, parents/society must be making child-rearing much more work than it was 50 years ago.

So I agree with the GP, it's a modernity problem (or rather, a modern culture problem).
by LargoLasskhyfv | 2025-07-05 05:58:05+00:00
Why?

"The spread of Islam presents a profound challenge to open societies. While we cherish tolerance as a foundational value, tolerance of intolerance eventually becomes self-destructive.2 As we struggle to defend secular, liberal values without lapsing into bigotry or xenophobia, the distinction between criticizing ideas and dehumanizing people is essential. But so is honesty: And the truth is that open societies cannot tolerate the spread of Islamic fanaticism indefinitely." seems perfectly reasonable to me.
by proc0 | 2025-07-05 05:59:03+00:00
I've always played a few games for many hours as opposed to many games for one playthrough. Subscription just does not make sense for me, and I suspect that's a big part of the market. Add to this the fact that you have no control over it and then top it off with potential ads and I will quit gaming before switching to subs only. Luckily there is still GoG and Steam doesn't seem like it will change but who knows.
by bmacho | 2025-07-05 05:59:06+00:00
Threads being over is a good thing, isn't it? Truth's been discovered, all parties agree, no more time spent on going in circles, can move on to do other, meaningful things, etc. Unless you are facebook, and you optimize on endless churn, stealing time and showing ads.

I haven't seen the original comment, but the wiki article is moronic. None of the listed example seems even bad to me, claiming that they are the devil is ridiculous. Maybe even a false flag.

The only one that actually has anything to do with "terminating cliche" is "Let's agree to disagree.". But that's just the common phrase you say after you've decided to opt out of an argument. It is not (and can't be) the cause of it, it is the consequence of it.* And it is by no means any bad, or should one avoid it.

* : something something people being able to easily leave an argument makes them do it more. But it would need a lot of stretch to argue that the possibility to go away from arguments is a net negative for humanity

edit: can we agree that the random shit you linked is 100% unrelated to the argument at hand, therefore/and definitely should not be used?

edit2: yeah, it assumes the truthness of some ridiculously nonsensical concepts, and uses them in a meta meta way, that is 2-3 steps away from the topic at hand. Much-much more annoying than anything listed. "This is the hill you want to die on, huh? Naah.. How about.." *points downwards* "..there is this hill there 14000 miles away (actually there is only ocean), how about we move this fight there?" Yeah no thx.
by zeta0134 | 2025-07-05 05:59:56+00:00
You seem to be missing that the translation part isn't the expensive part, it's the validation and review.

Separately, maybe this is just me, but having data actually flow through my hands is necessary for full comprehension. Just skimming an automated result, my brain doesn't actually process like half of that data. Making the process more efficient in this way can make my actual review performance *much worse.* The "inefficient" process forcing me to slow down and think can be a feature.
by troupo | 2025-07-05 06:00:06+00:00
I still fail to see your point.

Here's what you started with: "The point about non-determinism is moot if you understand how it works."

When challenged you're now quite literally saying "oh yeah, they are all non-deterministic, will produce varying results, it's impossible to control the outcome, and there's some ideal non-existent LLM that will not have these issues"

So what's your point and forest again?
by sandreas | 2025-07-05 06:01:08+00:00
A 80Bronze 300W can still be more efficient than a 750W 80Platinum on mainly low loads. Additionally, some of the devices are way more efficient than they are certified for. A well known example is the Corsair RM550x (2021).

If your peak power draw is <200W, I would recommend an efficient <450W power supply.

Another aspect: Buying a 120 bucks power supply that is 1.2% more efficient than a 60 bucks one is just a waste of money.
by hecanjog | 2025-07-05 06:01:27+00:00
> my college is a kind of a kind of a center of the most tradicional, western avant-gard electronic music, so certainly I agree that it leaves a lot of outside

Let's list some of the outside.

Maryanne Amacher, Pauline Oliveros, Éliane Radigue, Clarence Barlow, Bebe and Louis Barron... I'm brain-farting so many, keep going!
by theshackleford | 2025-07-05 06:01:50+00:00
> Reflecting a bit, I really see not plausible justification why say one account should be let to be logged in for more than 3 hours/day

Because I am the master of my time. If I wish to not play for three months, and then I decide I want to spend an entire Saturday playing, that is my choice, not yours.

> I don't think it's adding to your wellbeing.

I'm not interested in what you think is/is not good for my well being. That is a decision for me to make.

> I think those people can find other activities and other media to fill their time and chat.

Please see the above.
by anovikov | 2025-07-05 06:04:01+00:00
So it means that indirectly, developers' salaries are not a taxable income in Canada if they are working on R&D? Meaning, they do pay taxes on their income, but their employer gets those taxes back, so if tax is 60%, the employer could pay 250% of what they'd pay otherwise, get 150% back, then the developer pays 150% of taxes, and gets 100%, so in effect the salary is tax-free. Is that what you meant to say?

If so, it sounds almost too good to be true. Why aren't all startups in Canada?
by edg5000 | 2025-07-05 06:04:05+00:00
Treating it like a thinking partner is good. When programming, I don't treat it like a person, but rather a very high programming language. Imagine exactly how you want the code to be. Then find a way to express that unambiguously in natural language; the idea is that you'll still have a bit of work to do writing things out, but it will be a lot quicker than typing out all code by hand. Combined with iterations of feedback as well as having the AI build and run your program (at least as a sanity check); and asking the AI to check the program behaviour in the same way you would, gets you quite far.

A limitation is the lack of memory. If you steer it from style A to B using multiple points of feedback, if this is not written down, the next AI session you'll have to reexplain this all over.

Deepseek is about 1TB in weights; maybe that is why LLMs don't remember things across sessions yet. I think everybody can have their personal AI (hosted remote unless you own lots of compute); it should remember what happened yesterday; in particular the feedback it was given when developing. As an AI layman I do think this is the next step.
by zeras | 2025-07-05 06:04:15+00:00
I remember playing Ultima Online and really enjoying that game when I heard about a new first-person MMORPG in development called EverQuest.

I ran a couple of popular game sites back then and had industry connections so I got early beta test access to try out EverQuest.

Unfortunately, I made a bad choice when I chose to make a Human character, which was night-blind. On top of that, it seemed like every time I logged in it was night time and the game was nearly unplayable away from lights, fires and torches for that character.

To make matters worse, I started in Freeport which had several invisible zone walls so on top of not being able to see, I constantly kept zoning which constantly interrupted the game.

As you can imagine, I lost interest rather quickly and went back to UO. I gave my beta account to a gamer friend of mine, who had a much better experience than I had during beta.

When EverQuest eventually launched, several friends of mine bought it so I decided to buy it as well. By then I had learned to make elven characters because they had infravision/ultravision that allowed them to see at night.

It was fun for a little while, but then bad game design concepts led to another problem. They arbitrarily decided to assign some of the classes with experience penalties, including the one I played which had a 40% experience reduction, which was ridiculous.

The problem was that at that time, that information was not well known so I all I noticed was all of my friends were outleveling me because none of their classes had penalties.

Eventually by around level 12 (which took a while back then), I was too low to group with them, despite playing the same amount of time they did, and I could no longer gain experience in their groups.

Since EverQuest was heavily group-focused, I decided to go back to Ultimate Online.

A few months later, I decided to give it another try and made a bard. Suddenly, everyone was inviting me to group and that made the game a lot more fun and led to a lot of great memories.

A few years ago I tried to go back and play it but, either due to age or having less free time, it was just too slow and difficult to play after all of these years.

While I don't play it any more, I am really glad that it is still online and even if it shuts down, there is another player-run (and licensed) rogue server available.

I met so many good friends in that game, including one of my best friends to this day, so I will always have fond memories of it.
by slau | 2025-07-05 06:04:39+00:00
With all due respect, and I’m particularly anti-LLM, you sound exactly like someone who has never tried the tech.

You can use LLMs without letting them run wild on the entire codebase. You have git, so you can see every minute change it makes. You can limit what files it’s allowed to change and how much context you give it.

You don’t have to give it root on your machine to make it useful. You don’t have to “Jesus, Take the Wheel”. It is possible to try it out at a smaller scale, even on critical code.
by whatevertrevor | 2025-07-05 06:05:02+00:00
I couldn't agree more, and not just on HN but the world at large.

For the general populace including many tech people who are not ML researchers, understanding how convolutional neural nets work is already tricky enough. For non tech people, I'd hazard a guess that LLM/ generative AI is complexity-indistinguishable from "The YouTube/Tiktok Algorithm".

And this lack of understanding, and in many cases lack of conscious acknowledgement of the lack of understanding has made many "debates" sound almost like theocratic arguments. Very little interest in grounding positions against facts, yet strongly held opinions.

Some are convinced we're going to get AGI in a couple years, others think it's just a glorified text generator that cannot produce new content. And worse there's seemingly little that changes their mind on it.

And there are self contradictory positions held too. Just as an example: I've heard people express AI produced stuff to not qualify as art (philosophically and in terms of output quality) but at the same express deep concern how tech companies will replace artists...
by Suppafly | 2025-07-05 06:05:15+00:00
Honestly, part of the overall ordering experience has pretty much always been included as part of the review on Amazon. It's weird that people take such umbrage with it. It may not be the author's "fault" but that's part of having your products on Amazon. I want to know if the product won't be delivered in a timely manner or if it won't be packed correctly.