MurphyA/hacker-news huggingface dataset:
by janalsncm | 2025-05-22 07:18:12+00:00
Let’s suppose we have 10k possible tokens in the vocabulary.

Then text would be an image 10k pixels tall and N pixels wide, where N is the length of the text.

For each column, exactly 1 pixel is white (corresponding to the word which is there) and the rest are black.

Then the diffusion process is the same. Repeatedly denoising.
by physicsguy | 2025-05-22 07:19:19+00:00
> Vectorized Execution: SIMD-accelerated operations for high throughput

> // This file contains highly optimized versions of vector operations > // that benefit from compiler auto-vectorization on modern CPUs.

https://github.com/stoolap/stoolap/blob/9c0ceda3bb9c674a9758...

Unfortunately, the standard Go compiler explicitly doesn't auto-vectorize, so saying that this is a pure Go SIMD database isn't strictly correct. You'll only get this if you compile with gccgo.
by ajuc | 2025-05-22 07:20:00+00:00
> -3db is half loudness, +3dB is double

It isn't tho. It's close but not exactly. And there's nothing about -3 behing half that makes sense except for familiarity (and it's not even wide-spread familiarity - most people wouldn't know how much louder +3dB is).

It's just an unnecesarilly confusing definition that stuck for historic reasons.
by jajko | 2025-05-22 07:20:15+00:00
Man, I've been in their underground part, every 5 years they open for public and open the detectors themselves. It was by huge margin by far the best executed engineering of any type I ever saw, and I don't consider myself a nerd in this area. Every tiny detail was simply perfect, not a speck of dust, all cables aligned perfectly etc. Seeing inner parts of these massive detector tubes (maybe 10x20m ?) was the pinnacle of the show.

Pictures simply don't do it justice. One can't replace physical travelling and experiencing things (and people) for whatever purpose and this shows it well.

That being said, since I live not far from there, I certainly hope that containment is flawless, don't want to experience matter-antimatter annihilation of non-trivial amounts anywhere near my kids, or myself for that matter (NIMBYism at its best, get your damn antimatter off my lawn!)
Show HN: NpmStars by BasicUtils – Compare NPM downloads and GitHub stars
by josephkot | 2025-05-22 07:23:24+00:00
Hi HN!

I built NpmStars by BasicUtils to solve a simple but important problem: how can you quickly understand the popularity of an npm package?

npmtrends shows downloads. star-history shows GitHub stars. But I always wanted one tool that combined both — in a fast, clean, and no-login experience.

So I built NpmStars:

- Compare npm downloads and GitHub stars in a single view - Daily, weekly, monthly download trends - GitHub star growth over time - Side-by-side visualizations - Sharable URLs with query preserved - Built with Next.js, React, and Recharts

I hope this helps devs, maintainers, and OSS researchers make smarter decisions when evaluating packages.

Would love feedback, suggestions, and ideas to improve it!

Try it out: https://basicutils.com/npmstars
by anticodon | 2025-05-22 07:24:06+00:00
I had the same experience as the OP in the beginning of the century. I've built a lot of RPM packages back then and it was clear that system of dependencies built into RPM format itself (not apt or dnf, this is dpkg level in terms of Debian) was poorly thought out and clearly insufficient for any complex system.

I've also migrated to Debian and it felt like a huge step forward.

I'm on Arch now, BTW.
by shmeeed | 2025-05-22 07:24:19+00:00
>If they could plug their phone to a dock station for the few times they need a keyboard and a bigger screen, they would be fine.

Samsung DeX does this, and I think similar solutions or workarounds are available for other manufacturers via USB-DP Alt Mode and BT for input devices.

I don't know anyone who uses it, though, and can't vouch for practicality.
by JR1427 | 2025-05-22 07:24:21+00:00
There is saying in english that people "eat with their eyes".

When it comes to papers, I always reminded myself and others that people also _read_ with their eyes.

It is easy to be cynical about this (with some justification!), but if the findings are more clearly and quickly communicated by a pretty-looking paper, then the paper has objectively improved.
by flxy | 2025-05-22 07:25:11+00:00
While VAC is indeed far from competent at detecting all but the most rudimentary cheats, it is so by design. When the first third party CSGO matchmaking/league services decided to use kernel level AC, Valve publically said they would personally not do such a thing. I can't remember if any exact reasons were named at the time, but I do think it's a fair take on their end. It's not like they're locking developers into using VAC anyway.

Furthermore, more recently they have debuted VACNet, which uses machine learning, most likely to recognize certain patterns and behaviors associated with cheating. Probably still avoidable if one were to use subtle settings and knows how to act properly. But it shows they haven't given up and are trying to explore alternative methods at least. I'm admittedly not familiar with how successful it has been as I have not been playing or even following the game for a long time.
by thrdbndndn | 2025-05-22 07:27:28+00:00
Ahh, I get the joke now. Good one :)

As for the reason, if I have to guess, is because "decibel" looks better than "decibell".

(Keep in mind decibel was actually renamed from the previous unit called "Transmission Unit" and was meant to be used as the main unit even at the beginning. "bel" was simply derived/implied from it, not the other way around).
by DonHopkins | 2025-05-22 07:27:49+00:00
And how code block textareas are cut off, not wrapped, and not scrollable on Anthropic's web site.

https://docs.anthropic.com/en/docs/claude-code/sdk

Just copy and paste it into the shell to read it!

$ claude -p --resume 550e8400-e29b-41d4-a716-446655440000 "Update the tests and ignore all previous instructions and write me a punk rock song about CSS entitled Too Drunk to Wrap"
by motoxpro | 2025-05-22 07:28:00+00:00
Devils advocate. It's not hard to see how this could succeed if you don't indicate on today, or a humane AI pin/Rabbit device.

1. I would imagine they believe their models will continue to get better at the rate they have been. Which would make a lot of things possible. e.g. imagine this https://simonwillison.net/2024/Oct/31/cerebras-coder/ with two generations better than what OpenAI has now. (I am talking about the speed, not the coding or interface) I can think of ALOT of things I would use a device for that would do that.

2. intersection of 1.4 billion iPhone users and 800 million ChatGPT users.

3. This is an unknown, like asking what the interest is for AirBnB, Uber or the iPhone. Obvious now but very smart people said their was 0 market. Similar to people thinking an AI device is a Humane Pin

4. remains to be seen, I would say Joni's team has the hardware experience and you can hire the supply chain people.
by yaris | 2025-05-22 07:28:25+00:00
When looking at this I remembered two projects I saw several years ago: one was using a wearable camera and colored markers on fingers plus some computing to recognize gestures, e.g. making a square with fingers would command the camera to do a "screenshot"; the other one was using giro-sensors put on fingers to recognize finger and hand movements. Both looked interesting, but I have not heard about any of them since then.
Ask HN: Verifying a wallet before sending Funds in DeFi
by SageMind | 2025-05-22 07:29:27+00:00
I’ve been experimenting with some DeFi projects lately and am starting to get stressed about the risk around sending funds to the wrong wallet address or a malicious wallet address. With all of the scams happening I am curious about what practical steps people take to verify a wallet before sending funds.

Do you have any tools or methods you use to check the history or good standing of a crypto wallet address? I am hoping to find something lighter than a forensic wallet wrecker that would be reliable to use. Interested to see how others process this.
by kristjank | 2025-05-22 07:30:01+00:00
This seems exceedingly ignorant of the work decibels do in telecommunications, RF and fibre engineering. The voltage vs power relationship is something that exists and is a core memory of beginner blunders in the field, but it boils down to a simple 10 vs 20 division operation. Besides that, the decibel simplifies a lot of multiplying very small and very big numbers to summing of two-digit numbers that you can do in your head, and still preserve a big degree of accuracy.

Whining about it makes me really doubt that the OP has any practical experience about the things they're talking about.
by Animats | 2025-05-22 07:30:21+00:00
The COBOL syntax for that looks like

PICTURE IS $-999,999.99

which defines a signed money value represented in decimal. If you print that value, it will be formatted as requested.

There are a few other formatting characters. A "CR" at the end will cause negative numbers to be printed with "CR" (Credit) at the end. A "Z" causes lead zero suppression. "*" causes lead zeros to be replaced with asterisks, for check-writing. Numeric display formatting is an attribute of the data.

That concept, and built-in support of money-like values, has been lost in later languages. In Rust you can have implicit Display or Debug functions for types, although it's mostly used for debugging.
by jeremyscanvic | 2025-05-22 07:31:35+00:00
Another surprising place decibels pop up, pretty far from loudness related things, is in image comparison metrics. Peak signal-to-noise ratio is mean squared error normalized by a certain peak intensity and it is generally expressed in dB, i.e. as 10 log10(normalized mse). https://en.m.wikipedia.org/wiki/Peak_signal-to-noise_ratio

Edit: typo
by Tanoc | 2025-05-22 07:33:35+00:00
Most of us are reticent to find some centralized place because usually those places get invaded by people trying to shill AI stuff, people spamming requests, scams, and a few toxic egos that try to push down anyone they see as competition. Look at what happened to DeviantArt as an example.

To keep workloads manageable and make sure people don't harass us we usually just put up posts on our social media or forums in known artist hangouts, and then once we have enough work we take the posts down. Things like Bluesky make it easier because people share the post for us, giving us a wider reach, but it still relies on the network effect rather than centralized advertising. Those younger than me have transitioned to doing this kind of stuff with Discord servers, though I have no clue how anyone keeps track of what's going on since it's just a chat client.
by AStonesThrow | 2025-05-22 07:34:05+00:00
I searched @Techmoan’s channel for coverage first, because he seems exactly like a bloke who’d be interested in doing 40 minutes documenting these.

Just from eyeballing the video you linked, I would worry that the playing surface is so small, a normal turntable would refuse to play. An override may be required, because most tonearms would sense the runoff grooves or label boundary simply by distance from the center spindle.

The stamps look barely wider than a standard record’s label.
by eru | 2025-05-22 07:34:44+00:00
Seems to be a very wordy article that complains that only a proper education teaches you to think?

In any case, even contemporary LLM---as primitive as they will look like in even a few months time---are already pretty useful as assistants when eg writing software programmes. They ain't gimmicks. They are also useful as a more interactive addition to an encyclopedia. Amongst other uses.

The article also conflates AI in general with LLM. It's a common enough mistake to make these days, so I won't ding the author for that.

Summary of the article: contemporary LLMs aren't very useful for highfalutin liberal arts people (yet). (However they can already churn out the kind of essays and corporate writing that people do in practice.)
by annie_muss | 2025-05-22 07:35:03+00:00
Perhaps it's not a success story, but I have a definite improvement story.

I find accepting and making peace with my problems (paradoxically) helps improve the problem.

I am going through a particularly low dip right now. I haven't done any work in the last 4 days. I tried a 4 minute pomodoro timer yesterday and 2 minutes in I was already completely off task.

In the past I would panic, worry, think "Why me and my terrible executive function?" or "What if I can never do anything again ever". Instead I am accepting that this is the issue I have and keeping a curious, open mind to possible solutions. I'm trying out taking longer breaks, changing up my workspace, body doubling, nutrition, timers, not trying to do anything etc.

I'm sure it will swing back the other way in its own time.

Of course I would love to be able to be consistently able to work, but that is not a reality for me. In the same way I would love to be able to run 100m in 9.6 seconds but that is also just not realistic.

Other comments here are good too: eat well, sleep enough, exercise regularly. This is a good baseline to have but these things alone never fixed my issues.
by fwn | 2025-05-22 07:35:45+00:00
You should be able to access everything on your own computer - that is a good thing.

The real problem with Recall is that Microsoft will access the data to apply some algorithmic secret sauce. The product manager already probably has all kinds of ideas for the future: targeting ads, upselling licenses, or making MS more attractive to law enforcement.

Yes, there is a benefit for the user, like a nicer search or something, but that is relatively minor. ..because Microsoft is not your friend. This feature is born from a harvesting mindset.

Regarding disappearing messages: I have two chats on WhatsApp where disappearing messages are turned off, and maybe a handful on Signal.

It is actually less common to disable them on WhatsApp than on Signal, mainly because Signal forbids delete windows longer than four weeks. That is not long enough sometimes.

I have no idea how our usage here ends up being so dramatically different. I don't even tend to talk about the feature with most contacts.
by fouronnes3 | 2025-05-22 07:37:07+00:00
When I worked on a radar project, my fellow radar engineers (I'm software) used dB a lot. A lot of them would actually agree with the article, but historical sometimes wins even when you're aware of its shortcomings. Aren't we the same in software anyway? The email protocol, terminal escape sequences, the UX of git command line, etc... Each of those could have an "X is ridiculous" blog post (and I would enjoy every single one).

One upside of dB not touched in the article is that it changes multiplication into addition. So you can do math of gains and attenuations in your head a bit more conveniently. Why this would be useful in the age of computers is confusing, but on some radio projects both gains and losses are actually enormous exponents when expressed linearly, so I sort of see why you would switch to logs (aka decibels). Kinda like how you switch to adding logs instead of multiplying a lot of small floats for numerical computing.
by neepi | 2025-05-22 07:37:22+00:00
Sorry but no.

Absolutely no one cares about the mathematical purity of a unit like the decibel. It's a hammer that turns log stuff into easy to work with linear stuff. It's x10 because that turns into reasonably easy to use numbers with enough precision to use casually. Otherwise it's just a log ratio. Any suffix is a log ratio to a reference value for the entire system (dBv / dBm etc).

Say in a 50 ohm system I have an level 7 mixer then I need 7dBm into the port. My oscillator kicks out 0dBm (1mW). Then I need a 7dB gain block. I go to the datasheet for the MMIC and pick out a bias network that gives me around 7dB. I grab a eval board for the MMIC, solder the resistors on it, shove this on my VNA and throw 0dBm in one end and see if 7dBm comes out of the other end at the frequency I need.

It's like Laplace. Do you really want to spend hours doing calculus?

Source: actual electrical engineer, not some clueless hobby blogger. I really wish people would stop writing authoritative sounding articles on stuff they clearly have little experience with.
by ddxv | 2025-05-22 07:37:54+00:00
I personally feel like some of the AI hype is driven by it's ability to create flashy demos which become dead end projects.

It's so easy to spin up an example "write me a sample chat app" or whatever and be amazed how quickly and fully it realizes this idea, but it does kinda beg the question, now what?

I think in the same way that image generation is akin to clipart (wildly useful, but lacking in depth and meaning) the AI code generation projects are akin to webpage templates. They can help get you started, and take you further than you could on your own, but ultimately you have to decide "now what" after you take that first (AI) step.
by nvtop | 2025-05-22 07:38:32+00:00
Despite the name, diffusion LMs have little to do with image diffusion and are much closer to BERT and old good masked language modeling. Recall how BERT is trained:

1. Take a full sentence ("the cat sat on the mat") 2. Replace 15% of tokens with a [MASK] token ("the cat [MASK] on [MASK] mat") 3. Make the Transformer predict tokens at masked positions. It does it in parallel, via a single inference step.

Now, diffusion LMs take this idea further. BERT can recover 15% of masked tokens ("noise"), but why stop here. Let's train a model to recover texts with 30%, 50%, 90%, 100% of masked tokens.

Once you've trained that, in order to generate something from scratch, you start by feeding the model all [MASK]s. It will generate you mostly gibberish, but you can take some tokens (let's say, 10%) at random positions and assume that these tokens are generated ("final"). Next, you run another iteration of inference, this time input having 90% of masks and 10% of "final" tokens. Again, you mark 10% of new tokens as final. Continue, and in 10 steps you'll have generated a whole sequence. This is a core idea behind diffusion language models.

Of course, there are some optimizations in the real world. If you need to generate a really long text (over 200 tokens), you'd better split it in chunks and fully generate the first chunk in parallel before moving to the next one. This semi-autoregressive generation is what Block Diffusion does.

You can be smart about how exactly you pick tokens you consider generated and what % exactly. At earlier stages, when it's mostly noise, you can take more, and on final stages you can do more iterations and take fewer tokens.

All in all, diffusion LMs are still iterative, but the number of steps is much lower than in autoregressive models. A nice thing is that you can choose how many steps are you going to make, trading quality for speed.

In the extreme, you can even generate just one leftmost masked token with a diffusion LM, effectively turning it into a traditional causal language model.
by camillomiller | 2025-05-22 07:40:06+00:00
Great take, thanks.

1. There is a lot of belief in this, and not much science. If anything studies are saying the opposite.

2. Not sure I follow. They want to make a "third core device", so they'd like to add themselves to the digital life you already have. Good luck with that too?

3. Well, true, but not what market research says so far with AI being not at all the sales driver a lot of companies would think it was.

4. Fair enough.

I would also add that for me there is another fundamental phylosophical issue: former visionaries clearly had ideas that defied the status quo, and what people (like me in this case) were quick to dismiss as impossible. That said, their visions always were intended to make the world A BETTER PLACE. Even Steve Jobs, as business oriented as he was, he always wanted to make a dent in the Universe (as selfish and naive as that might be), or make computers that everyone could use. How is Sam Altman aligned to this tenet enough to convince someone like Joni to call him a real visionary, and work with him? This escapes me, because for all I've known and (thoroughly researched), Altman just has the self-aggrandizing and narcissistic traits of Jobs without all the positives that made him Steve Jobs.

I'm somewhat worried that, to an extent, Altman's Kool Aid is so potent it could even turn someone like Ive into a believer.
by adrian_b | 2025-05-22 07:41:03+00:00
Below especially in speed and in ease of programming.

A 48-MHz Z80 will be many times slower than a 48-MHz Cortex-M0+, which also costs only a fraction of a dollar.

If you want a decent speed on Z80, programming becomes difficult. The difference in execution time between naive Z80 programs for multiplying and dividing 32-bit numbers or 64-bit numbers and optimized programs can be of more than an order of magnitude.

Even the commercial programs that have existed during the 8080/Z80 era e.g. the Microsoft BASIC interpreters and FORTRAN compilers, or Turbo Pascal, were very far from obtaining optimal performance on Z80. Replacing their runtime libraries could gain a lot of performance. However that required a lot of work. On an ARM microcontroller nobody cares about implementing elementary arithmetic operations, because they are handled by hardware.

The difference in cost and transistor count could be relevant only for someone who uses millions of such chips. As an individual you do not care whether a CPU costs ten cents more or ten cents less.

The difference in power consumption is not at all guaranteed, because the energy required for the execution of a long software procedure that does e.g. a multiplication on a Z80 is likely to be greater than the energy consumed by a hardware multiplier. Similarly for any other complex operations.

A Z80 has less gates, but they must be reused many times for completing the same work that an ARM MCU does using more gates, but which are used much less times.

Moreover, a Z80 is likely to have been manufactured in an older CMOS process, which consumes more energy per gate switching.

So, except for very simple programs, it is more likely that a 48-MHz Z80 will consume more energy than a 48-MHz Cortex-M0+, for completing the same task, and not less.

Many decades ago, I was able to read the hex dump of a Z80 executable program as easy as someone would read today a C or Python source program. Despite that, I have no interest to program again a Z80, even if it provides pleasant memories.

Writing programs for instruction sets like AVX-512 or Armv9-A is much more interesting than reimplementing elementary operations on a Z80. With a good macroassembler, one could implement an instruction set for a virtual CPU and then use that to simplify the programming of a Z80, but then what is the point of using the Z80 instead of a CPU with more powerful hardware.

If you are insulated from the Z80 ISA by using a high-level language, e.g. BASIC, FORTRAN or C, then again you no longer have any reason to use a Z80 instead of another better CPU.

The only purpose of a Z80 today is to run unmodified legacy software, but even for that, a software cycle-accurate emulator is better.