MurphyA/hacker-news huggingface dataset:
by troad | 2025-12-03 06:04:01+00:00
You have pretty explicitly framed Zig as a C replacement yourself, e.g.: https://www.youtube.com/watch?v=Gv2I7qTux7g

More broadly, I think the observation tends to get repeated because C and Zig share a certain elegance and simplicity (even if C's elegance has dated). C++ is many things, but it's hardly elegant or simple.

I don't think anyone denies that Zig can be a C++ replacement, but that's hardly unusual, so can many other languages (Rust, Swift, etc). What's noteworthy here is that Zig is almost unique in having the potential to be a genuine C replacement. To its (and your) great credit, I might add.

>> At its core Zig is marketed as a competitor to C, not C++/Rust/etc, which makes me think it's harder to write working code that won't leak or crash than in other languages. Zig embraces manual memory management as well.

@GP: This is not a great take. All four languages are oriented around manual memory management. C++ inherits all of the footguns of C, whereas Zig and Rust try to sand off the rough edges.

Manual memory management is and will always remain necessary. The only reason someone writing JS scripts don't need to worry about managing their memory is because someone has already done that work for them.
by octoberfranklin | 2025-12-03 06:04:27+00:00
The dark fiber glut wasn't caused by DWDM suddenly appearing out of nowhere.

The telcos saw DWDM coming -- they funded a lot of the research that created it. The breakthrough that made DWDM possible was patented in 1991, long before the start of the dotcom mania:

https://patents.google.com/patent/US5159601

It was a straight up bubble -- the people digging those trenches really thought we'd need all that fiber even at dozens of wavelengths per strand.

They believed it because people kept showing them hockey-stick charts.
by mulmboy | 2025-12-03 06:05:33+00:00
> Everything it does can be done reasonable well with list comprehensions and objects that support type annotations and runtime type checking (if needed).

I see this take somewhat often, and usually with similar lack of nuance. How do you come to this? In other cases where I've seen this it's from people who haven't worked in any context where performance or scientific computing ecosystem interoperability matters - missing a massive part of the picture. I've struggled to get through to them before. Genuine question.
by kouteiheika | 2025-12-03 06:05:45+00:00
> Given the number of leaks, deliberate publications of weights, and worldwide competition, why do you believe this?

So where can I find the leaked weights of GPT-3/GPT-4/GPT-5? Or Claude? Or Gemini?

The only weights we are getting are those which the people on the top decided we can get, and precisely because they're not SOTA.

If any of those companies stumbles upon true AGI (as unlikely as it is), you can bet it will be tightly controlled and normal people will either have an extremely limited access to it, or none at all.

> Even if by "lobotomised" you mean "refuses to assist with CNB weapon development"

Right, because people who design/manufacture weapons of mass destruction will surely use ChatGPT to do it. The same ChatGPT who routinely hallucinates widely incorrect details even for the most trifling queries. If anything, that'd only sabotage their efforts if they're stupid enough to use an LLM for that.

Nevertheless, it's always fun when you ask an LLM to translate something from another language, and the line you're trying to translate coincidentally contains some "unsafe" language, and your query gets deleted and you get a nice, red warning that "your request violates our terms and conditions". Ah, yes, I'm feeling "safe" already.
by kamikazechaser | 2025-12-03 06:07:42+00:00
At this stage I don't think either is better over the other. Deno has inexplicable high memory usage issues in Linux containers. Bun more or less suffers from the same with an added dose of segfaults.

1. https://github.com/denoland/deno/issues?q=is%3Aissue%20state... 2. https://github.com/oven-sh/bun/issues?q=is%3Aissue%20state%3...

Node.js is a no-brainer for anyone shipping a TS/JS backend. I'd rather deal with poor DX and slightly worse performance than risk fighting runtime related issues on deployment.

Linux needs to be a first class citizen for any runtime/langauge toolchain.
by sho | 2025-12-03 06:08:51+00:00
> and provide inference at a loss

You say this like it's some sort of established fact. My understanding is the exact opposite and that inference is plenty profitable - the reason the companies are perpetually in the red is that they're always heavily investing in the next, larger generation.

I'm not Anthropic's CFO so i can't really prove who's right one way or the other, but I will note that your version relies on everyone involved being really, really stupid.
by schainks | 2025-12-03 06:11:09+00:00
You can't just "swap a font out" without redoing all the work.

Type layout in Japanese in particular has a system of layered, complex rules that include rules that define how to combine Western glyphs with Japanese glyphs and produce visually harmonic work. Swapping a font out due to a cost issue is not workable.

Also, not all pan-asian fonts contain all the glyphs you need to render all the characters you want. A CJK font has tens of thousands of characters, and it wouldn't surprise me if some of these video games will use fonts with particular glyphs that are not always included in other fonts.

Monotype is giving these customers the finger while also ramming a bulldozer in their asses with this change. It's completely unacceptable, painfully rude, and ridiculously tone deaf. In fairness, this is totally on brand for Monotype.
by spherelot | 2025-12-03 06:11:14+00:00
How do you prompt the model? In my experience, Qwen3-VL models have very accurate grounding capabilities (I’ve tested Qwen3-VL-30B-A3B-Instruct, Qwen3-VL-30B-A3B-Thinking, and Qwen3-VL-235B-A22B-Thinking-FP8).

Note that the returned values are not direct pixel coordinates. Instead, they are normalized to a 0–1000 range. For example, if you ask for a bounding box, the model might output:

```json [ {"bbox_2d": [217, 112, 920, 956], "label": "cat"} ] ```

Here, the values represent [x_min, y_min, x_max, y_max]. To convert these to pixel coordinates, use:

[x_min / 1000 * image_width, y_min / 1000 * image_height, x_max / 1000 * image_width, y_max / 1000 * image_height]

Also, if you’re running the model with vLLM > 0.11.0, you might be hitting this bug: https://github.com/vllm-project/vllm/issues/29595
by wakawaka28 | 2025-12-03 06:12:48+00:00
>I care that you have the technical ability to understand modern media tactics. It is well past things like bias.

I understand what they do very well. I'm at the point where if the media says it's raining, I go look outside.

I truly wonder if you know how modern suppression is achieved. I've been witnessing it for many years now. If you didn't already know, social media outlets like Twitter had backdoor access for government employees, where practically anyone who had access could request to infringe on their fellow citizens' First Amendment rights. They would throttle and ban people with as few as dozens of followers/subscribers. Liberals were very much of the "It's not happening but it's a good thing" attitude the whole time, like they do with every concern from the other side. Look at the tyrannical censorship, disarmament, surveillance, and financial oppression taking shape all over the Western world. Our "allies" are doing trial runs, and the "elites" have the same intentions for us stubbornly independent Americans.

If you want to go down another rabbit hole on this topic, look up Operation Mockingbird.
by somenameforme | 2025-12-03 06:13:33+00:00
A big difference is that in the past things like the potential of the PC were somewhat widely underestimated. And then the internet was again as well.

But in modern times it's rather the opposite scenario. The average entity is diving head first into AI simply expecting a revolutionary jump in capability that a more 'informed', for lack of any less snooty term, perspective would suggest is quite unlikely to occur anytime in the foreseeable future. Basically we have a modern day gold rush where companies and taking out unbelievably massive loans to invest in shovels.

The only way this doesn't catastrophically blow up is if AI companies manage to convince the government they're too big to fail, and get the Boeing, Banks, et al treatment. And I expect that's exactly the current strategy, but that's rather a high risk, low reward, type strategy.
by duskdozer | 2025-12-03 06:13:58+00:00
As someone who often wrote with bullet points, emoticons, some extra formatting, or dashes - albeit using the hyphen (incorrectly, I've learned) and not the em- - (:P) some LLM-generated text uses these things very liberally and much differently than most people did before. I didn't always have reactions like this, but after being baited by enough garbage search engine results and the like, I'm now often put off very quickly after noticing these patterns. And frankly, seeing it just makes it not feel worth it to continue reading and try to guess at what the person's actual ideas and thoughts are.
by alephnerd | 2025-12-03 06:14:10+00:00
> Monotype will have a much harder time trying to strongarm a PRC-based company if they decide to try this there

Monotype has a Chinese subsidiary [0] which has worked with Chinese champions like Tencent [1] and Alibaba [2].

As long as a foreign vs Chinese business dispute doesn't involve a national champion or a very politically connected Chinese firm (or the foreign company made a partnership with a politically connected partner) the dispute is somewhat fair.

While China's leadership is trying to build self-sufficiency, it is also still trying to attract foreign companies to China and prevent an FDI outflow [3], and that requires some level of impartiality in contract disputes. China is not as economically isolated as Russia is today - though even Russian authorities tend to only use the heavy hammer against American and European companies as can be seen with the continued operation of Japanese, Korean, Taiwanese, Vietnamese, and Indian firms in Russia despite the risk of sanctions.

[0] - https://cn.monotype-asia.com/contact-us

[1] - https://www.monotype.com/resources/case-studies/tencent-expa...

[2] - https://www.monotype.com/resources/case-studies/alibaba-grou...

[3] - https://www.gov.cn/zhengce/zhengceku/202507/content_7032625....
by benrutter | 2025-12-03 06:14:38+00:00
> AI isn’t especially environmentally unfriendly

I think the actual answer is more nuanced and less positive. Although I appreciste how many citations your comment has!

I'd point to just oe, which is a really good article MIT's technology review published about exactly this issue[0].

I'd make two overall points firstly to:

> when you have the opportunity to use human labour or AI, AI is almost certainly the greener option as well.

I think that this is never the trade off, AI normally generates marketing copy for someone in marketing, not by itself, and even when if it does everything itself, the marketing person might stop being employed but certainly doesn't stop existing and producing co2.

My point is, AI electricity usage is almost exclusively new usage, not replacing something else.

And secondly on Simon Wilison / Sam Altman's argument that:

> Assuming that higher end, a ChatGPT prompt by Sam Altman's estimate uses: > > 0.34 Wh / (240 Wh / 3600 seconds) = 5.1 seconds of Netflix > > Or double that, 10.2 seconds, if you take the lower end of the Netflix estimate instead.

This may well be true for prompts, but misses out the energy intensive training process. Which we can't do if we actually want to know the full emmisions impact. Especially in an environment when new models are being trained all the time.

On a more positive note, I think Ecosia's article makes a good point that AI requires electricity, not pollution. It's a really bad piece of timing that AI has taken off initially in the US at a time when the political climate is trying to steer energy away from safer more sustainable sources, and towards more dangerous, polluting ones. But that isn't an environment thay has to continue, and Chinese AI work in the last year has also done a good job of demonstrating that AI trainibg energy use can be a lot kess than previously assumed.

[0] https://www.technologyreview.com/2025/05/20/1116327/ai-energ...
Show HN: An emotional steering website for Qwen 2.5 7B
by nicetomeetyu | 2025-12-03 06:15:33+00:00
Make Qwen happy, sad, mad, surprised, afraid, or disgusted with the latest interpretability research https://www.lesswrong.com/posts/CHxLiTwZYvsGfLLhP/i-gave-llm...
by isolatedsystem | 2025-12-03 06:16:34+00:00
I've recently had to migrate over to Python from Matlab. Pandas has been doing my head in. The syntax is so unintuitive. In Matlab, everything begins with a `for` loop. Inelegant and slow, yes, but easy to reason about. Easy to see the scope and domain of the problem, to visualise the data wrangling.

Pandas insist you never use a for loop. So, I feel guilty if I ever need a throwaway variable on the way to creating a new column. Sometimes methods are attached to objects, other times they aren't. And if you need to use a function that isn't vectorised, you've got to do df.apply anyway. You have to remember to change the 'axis' too. Plotting is another thing that I can't get my head around. Am I supposed to use Pandas' helpers like df.plot() all the time? Or ditch it and use the low level matplotlib directly? What is idiomatic? I cannot find answers to much of it, even with ChatGPT. Worse, I can't seem to create a mental model of what Pandas expects me to do in a given situation.

Pandas has disabused me of the notion that Python syntax is self-explanatory and executable-pseudocode. I find it terrible to look at. Matlab was infinitely more enjoyable.
by kouteiheika | 2025-12-03 06:17:03+00:00
> The lack of competence from companies that acquire Japanese companies, and then fail to even price things in yen or offer support packages that cater to Japanese customers is really something.

In general I don't think it's just that. Pretty much all font foundries have... insufferable business models.

I once emailed one Japanese foundry asking to license one of their font to use on my website. I wanted a perpetual, one-time license to use on a single website, and I wanted to store and serve their font from my server. I was even prepared to pay low four figures for it.

Nope. I was told I need to pay a subscription fee, and I need to use their crappy Javascript to serve it. Okay, if you don't want my money then I'm not going to insist.
by jacquesm | 2025-12-03 06:17:17+00:00
I don't know about that. I was building inverters from scratch on intuition when I was 17 or so and I started with electronics properly when I was 11 reading library books, taking stuff apart and putting it (or something else) back together again.

Compared to an FFT, which would require a lot of math insight it seems to me a charge pump is trivial because charging and discharging is what capacitors do, it is the most basic thing you can do with a cap. In programming it would not be the equivalent of an FFT, but more like the equivalent of putting a value in a variable and expecting that value to still be there a while later.

Now, I came into software from hardware, to me software is having an infinite parts box so what's trivial to someone that started in hardware is probably entirely different from the view a software person has of the hardware world. Which is one reason why analog is such a barrier to programmers: they tend to look for the place where the state of the system is stored, rather than that the whole circuit is a continuous function of its input and what happened before. Getting analog circuitry to behave predictably can be quite tricky because of that and just hanging a probe of it will influence the circuit.

Resistors are easy, for the most part grade school math. Capacitors harder but not a lot harder, high school math, some basic integration required. Coils are where it gets more interesting and difficult math wise. And of course parasitic components are everywhere and can make your life harder, especially at higher frequencies or, in the case of single pulses shorter rise and fall times. A piece of wire is a resistor, capacitor and a coil for free all at once. Stripline takes advantage of that fact but without tooling it is next to impossible to work out the math and get predictable results (again, for me, I know people that can do this intuitively).

Multi-pole filters, high gain amplifiers, clean oscillators, those rise to the level of that FFT (for me).

The long tailed pair I agree with, that's a puzzler.

If you don't have one yet (and I assume you do, but just in case): get a scope. They're pretty cheap nowadays and a good scope will do wonders for such insights. I only got one when I was an adult and finally could afford it and it was an absolute game changer. If I had had one earlier I would have gotten a lot more mileage out of my time, especially when troubleshooting broken hardware. You don't need a fancy one, 100 MHz dual trace is more than good enough but that's table stakes now.

One big insight for me is that hardware 'is' and software 'does'. You don't tell a piece of hardware what to do, you design it to 'be' something and a computer simply (ok, maybe not so simply) needs to be told what to 'do'. This took me a long time to really grok after making the jump from hardware to software.
by eru | 2025-12-03 06:17:40+00:00
> Now you have 12 functions, scattered over multiple packages, [...]

Who says that the 12 functions need to be in multiple packages? And you can also keep them in the order you call them.

Having 12 functions is probably easier to test, too.

Yes, the 70 lines rules is arbitrary. But it's only as arbitrary as using 80 columns.
by davidmanescu | 2025-12-03 06:18:16+00:00
I have no special knowledge about IBM Vs Apple historically, but: a quarter billion in CAPEX when you've earned a billion in revenue in a single year is extremely different to what we're seeing now. These companies are spending all of their free cash flow, then taking on debt, to the tune of percentage points of world GDP, and multiples of any revenue they've seen so far. That kind of oversupply is a sure fire way to kill any ROI.
by GuestFAUniverse | 2025-12-03 06:20:01+00:00
Btw., critiquing: "This is how he cleans the code in 2024: Original version on the left; the cleaned-up version on the right:" -- that doesn't render side-by-side on my mobile and I wish every web author would consider labeling/naming content boxes instead; and would reference that, like good books are doing it.
by venturecruelty | 2025-12-03 06:21:06+00:00
Look at the power dynamics then. Who has more power in this situation: people with rent and mortgages? Or companies with more money than God? Companies could simply stop using LLMs and tomorrow and be fine. They brag about laying off thousands while turning record profits; they can turn off the slop machines.

Let's not blame the people with no power in this situation.
by rgmerk | 2025-12-03 06:21:33+00:00
Hugely unlikely.

Even if the power is free you still need a grid connection to move it to where you need it, and, guess what, the US grid is bursting at the seams. This is not just due to data center demand; it was struggling to cope with the transition away from coal well before that point.

You also can’t buy a gas turbine for love nor money at the moment, and they’re not ever going to be free.

If you plonked massive amounts of solar panels and batteries in the Nevada desert, that’s becoming cheap but it ain’t free, particularly as you’ll still need gas backup for a string of cloudy days.

If you think SMRs are going to be cheap I have a bridge to sell you, you’re also not going to build them right next to your data centre because the NRC won’t let you.

So that leaves fusion or geothermal. Geothermal is not presently “very cheap” and fusion power has not been demonstrated to work at any price.
by benrutter | 2025-12-03 06:21:43+00:00
I'll be interested to see how this pkays with their actual users.

As one myself, I don't object inherently to Ecosia providing AI search. I understand they need to stay competitive with other search.

But I find how prominent / hard to avoid their AI search is, reeeeaaally annoying. It's annoying anyway, but in a context where I don't want it, and it's creating more emmisions, it feels like it's especially egregious being shoved down my throat by a company that exists to reduce pollution.
by sparqlittlestar | 2025-12-03 06:22:10+00:00
1. Because fonts are works of art and any artist deserves to be paid. 2. Because there may not be a freely licensed font with the right aesthetics 3. Especially because Japanese fonts require much more work than Latn fonts, with not some hundred glyphs (a-zA-Z0-9 and punctuation), but with thousands upon thousands of glyphs
by MarkusQ | 2025-12-03 06:22:43+00:00
And their advice is...don't point your camera at their cars?

What about traffic cameras? Or dash cams? Or other self driving cars that use cameras (exclusively, or in addition to their own lidar systems)? If you go around firing a laser powerful enough to damage other people's property in all directions, it would seem that the onus should be on you, not on whoever you zapped.
by johnfn | 2025-12-03 06:23:03+00:00
johnfn@mac ~ % time deno eval 'console.log("hello world")' hello world deno eval 'console.log("hello world")' 0.04s user 0.02s system 87% cpu 0.074 total johnfn@mac ~ % time bun -e 'console.log("hello world")' hello world bun -e 'console.log("hello world")' 0.01s user 0.00s system 84% cpu 0.013 total

That's about 560% faster. Yes, it's a microbenchmark. But you said "absolutely zero chance", not "a very small chance".
by somenameforme | 2025-12-03 06:23:56+00:00
Vin Mariani was 7+mg/oz with a relatively low alcohol content which would have been further mitigated by the stimulant effect of the cocaine in any case. And then of course other concotions (including Coca-Cola) had no alcohol at all - Vin Mariani is just a fun example because of the endless famous names attached to it.

Obviously you're right that the absorption is going to be different and a modern coke head with high tolerance likely wouldn't even notice it had anything in it. But give it to a normal person, and they're indeed going to be coked out - in very much the same way that small doses of adderall to non-users can have a very significant effect. The obvious example there being college kids buying pills around around finals.
by Glawen | 2025-12-03 06:24:16+00:00
Not so fast. I "saved" guys from being fired by asking to be more patient with them. The last one was not in my team as I moved out to lead another team. Turned out the guy did not please an influencial team member, who then complained about him. What I saw instead was a young silent guy, given boring work and was longing for more interesting work. A tad later he took ownership of a neglected project, completed it and made a name of himself.
by snailmailman | 2025-12-03 06:24:53+00:00
I’m curious where you got any of those numbers. Many laptops use <20W. But most local-ai inferencing requires high end, power hungry nvidia GPUs that use multiple hundreds of watts. There’s a reason those GPUs are in high demand, with prices sky high, because those same (or similar) power hungry chips are in data centers.

Compared to traditional computing it seems to me like there’s no way AI is power efficient. Especially when so many of the generated tokens are just platitudes and hallucinations.