MurphyA/hacker-news huggingface dataset:
by rvnx | 2025-05-31 06:01:04+00:00
I totally support antirez on this. He managed to exit with money for work that was beneficial to everyone and that stayed in the open, just as a separate fork. This is really fair. Redis had made my SRE life so much easier (in front were these horrors like memcached or Cassandra with ZK).

If that means that the package is now named Valkey this is totally fine.
by MangoToupe | 2025-05-31 06:03:19+00:00
In the context of LLMs, what do you mean by "reason"? What does reasoning look like in LLMs and how do you recognize it, and more importantly, how do you invoke it? I haven't had much success in getting LLMs to solve, well, basically any problem that involves logic.

Chain of thought at least introduces some skepticism, but that's not exactly reasoning. It makes me wonder what people refer to when they say "reason".
by motorest | 2025-05-31 06:04:21+00:00
> Yes, making money is bad. Open source is only in service of the monopolies.

What a spin. Extortion following licensing rug pulls goes way beyond earning a living. Trying to blame victims by framing them as "monopolies" is somewhere between laughable and disingenuous. It's bold of you to make these claims in a time where everyone can verify both the licensing changes and how the whole developer community unanimously reacted to it.

> Only AWS and the hyperscalers deserve to make millions from Redis. Screw the Redis authors and maintainers.

If you pay attention, you will realize that all major Linux distros rushed to replace Redis with ValKey. Quite bold of you to claim that this licensing rug pull only affected villains.

Enough with the nonsense. If you try to abuse your users and treat everyone as a fool, don't clutch your pearls when they just drop you without a second thought.
by matkoniecz | 2025-05-31 06:04:39+00:00
"Share of total current users/years in" on slide 3 seems like nonsense metric to me that is far from being interesting or relevant. Yes, we know that there was hype growth for LLM while Google has long history of growth. This chart gives no useful info and pretends to reveal something while just being repeat of "USA-based LLM users" on the same page.

Looks like yet another "numbers going up" report, not going to spend time on reading 300+ slides like that.

Maybe I am unfair, but I have no time to read every single report and I am willing to read only exceptional ones with no (or very limited) marketing slop.
by rfonseca | 2025-05-31 06:04:42+00:00
I may be missing something, but in addition to this threat of prompt injection, you also have to trade trusting the arbitrary MCP server for trusting MCP Defender.

In the default mode, the app will interpose on the communication between, say, Claude, and a local MCP server. It will send the contents of the message (which may include the very sensitive information it is trying to protect) to a remote LLM, which you have to trust. The "scans" will be stored on a log on the server. Not to mention the potential extra delay for every MCP exchange?

This may be more secure, but is it really?
by eddythompson80 | 2025-05-31 06:05:46+00:00
I completely disagree. I don't see the current status quo fundamentally changing.

That idea makes so much sense on paper, but until you start implementing it that you realized why no one does it (including Siri). "Some tasks are complex and better suited for complex giant model, but small models are perfectly capable of running simple limited task" makes a ton of sense, but the component best equipped at evaluating that decision is the smarter component of your system. At which point, you might as well have had it run the task.

It's like assigning the intern to triage your work items.

When actually implementing the application with that approach, every time you encounter an "AI-miss" you would (understandably) blame the small model, and eventually give up and delegate yet-another-scnario to the cloud model.

Eventually you feel you're artificially handcuffing yourself compared to literally every body else trying to ship something utilizing a 1b model. You have the worst of all options, crappy model with lots of hiccups yet it's still (by far) the most resource intensive part of your application making the whole thing super heavy and you are delegating more and more to the cloud model.

The local LLM scenario is going to be entirely driven by privacy concerns (around which there is no option. It's not like an E2EE LLM API could exist) or cost concerns if you believe you can run it cheaper.
by staindk | 2025-05-31 06:06:10+00:00
I have 2 rules set on my Pixel -

First one sets my phone to silent when I arrive at work (500m radius I think). It also sets it back to loud (or whatever the previous state was) automatically when I leave that radius.

Second one sets my phone to loud when my phone connects to my home WiFi. This helps with the problem you describe - but agreed, phone stuck on silent isn't generally an issue (until I miss some courier's phone call and kick myself).
by johncoltrane | 2025-05-31 06:06:19+00:00
FWIW… Tech fads used to be pretty limited to tech circles. You would be bombarded for a few months by content about this or that on HN and elsewhere without ever hearing about it on the subway or at a dinner. Crypto kind of crossed the line at some point, but it is still a niche thing. ChatGPT and that whole ML-marketed-as-AI thing, on the other hand… it is everywhere.

"Get rich quick" schemes are somewhat attractive to the masses but nothing seems to beat those new "don't do the work you are paid for" schemes.
by eastbound | 2025-05-31 06:07:21+00:00
Apart from the tax office suing you in oblivion because the startup you’ve founded is now worth 10x its revenue, so you need to pay 40% CGT with only 1/10th the income (at least that’s the French exit tax).

So basically once you are rich, you have to choose to leave most of it on the table to go to a poor country.
by binoct | 2025-05-31 06:07:48+00:00
One of my favorite things to question about autonomous driving is the goalposts. What do you mean the “stated goal of full self driving”, which is unachievable? Any vehicle, anywhere in the world, in any conditions? That seems an absurd goal that ignores the very real value in having vehicles that do not require drivers and are safer than humans but are limited to certain regions.

Absolutely driving is cultural (all things people do are cultural) but given 10’s of millions of miles driven by Waymo, clearly it has managed the cultural factor in the places they have been deployed. Modern autonomous driving is about how people drive far more than the rules of the road, even on the highly regulated streets of western countries. Absolutely the constraints of driving in Chennai are different, but what is fundamentally different? What leads to an impossible leap in processing power to operate there?
by WalterGR | 2025-05-31 06:08:19+00:00
Is MS-DOS `edlin` related in any way to `ed`?

Wikipedia:

“Edlin was created by Tim Paterson in two weeks in 1980, for Seattle Computer Products's 86-DOS (QDOS) based on the CP/M context editor ED, itself distantly inspired by the DEC PDP-10 TOPS-10 EDIT text editor.”
by ramesh31 | 2025-05-31 06:09:07+00:00
>Without well paid middle classes, who is buying all the fancy goods and services?

Rich people buying even fancier goods and services. You already see this in the auto industry. Why build a great $20,000 car for the masses when you can make the same revenue selling $80,000 cars to rich people (and at higher margins)? This doesn't work of course when you have a reasonably egalitarian society with reasonable wealth inequality. But the capitalists have figured out how to make 75% of us into willing slaves for the rest. A bonus of this is that a good portion of that 75% can be convinced to go into lifelong debt to "afford" those things they wish they could actually buy, further entrenching the servitude.
by motorest | 2025-05-31 06:09:20+00:00
> I'm curious, why hasn't Valkey picked up corporate sponsors to the degree OpenTofu did when HashiCorp changed Terraform's licensing?

You seem to be completely out of the loop. Valkey is backed by AWS, Google Cloud, Oracle, etc. If I recall correctly, a principal engineer from AWS was spearheading the project.

https://valkey.io/participants/
by bschwindHN | 2025-05-31 06:09:52+00:00
I got into electronics around 2016, right around when I was visiting my hometown from living abroad. There's been a Micro Center there for years and I ended up spending hours there looking at all the ESP8266 boards they had there, along with the various supplies of Arduinos and Adafruit boards. Pretty "recent" in terms of electronics tech, but somehow this is already close to 10 years ago :c
by ricardobayes | 2025-05-31 06:09:55+00:00
Frankly, we don't know. That "turning point" that seemed so close for many tech, never came for some of them. Think 3D-printing that was supposed to take over manufacturing. Or self-driving, that is "just around the corner" for a decade now. And still is probably a decade away. Only time will tell if GenAI/LLMs are color TV or 3D TV.
by aapoalas | 2025-05-31 06:10:15+00:00
I will! :)

But, an apology is also in order: the 70% number on our website is more misleading than I thought it is. Our test runner skips entirely Annex B[1] _and_ Intl tests; one could perhaps view the 70% number then as "percentage of ECMA262 specification done". The 58% value reported by test262.fyi is probably the correct value (unless we have a bug with debug prints that causes spurious failures there).

[1]: I remembered that we skip Annex B tests; those are fairly few in number and we pass 40% of them anyway, so their effect isn't large. Didn't remember the other category we skip, and absolutely didn't remember that it's a major one like Intl.
by threeseed | 2025-05-31 06:12:51+00:00
How are we in 0.1 of GenAI ? It's been developed for nearly a decade now.

And each successive model that has been released has done nothing to fundamentally change the use cases that the technology can be applied to i.e. those which are tolerant of a large percentage of incoherent mistakes. Which isn't all that many.

So you can keep your 10x better and 100x cheaper models because they are of limited usefulness let alone being a turning point for anything.
by MrJohz | 2025-05-31 06:13:45+00:00
This is a philosophical point about what's considered solveable. For example, in the sudoku community, there's this idea of bifurcation, which is when you get to a point in a puzzle where there are two options to take, and you step through each option manually until you figure out which one is correct, and backtrack if necessary.

You can do an entire puzzle this way (just keep on trying options and seeing if they work), but this is generally not on. If you build a puzzle that can only be solved this way, then you've built a bad puzzle, at least by the standards of the sudoku solving community. On the other hand, most complex or variant sudoku puzzles will have moments where there are two or three possibilities for a cell, and you need to look at the immediate effects of those possibilities to figure out which one is correct. So clearly some amount of bifurcation and backtracking is fine.

Fwiw, in the nonograms I've done in various apps, there's almost never a need to guess between different possibilities. I don't know if that's because the puzzle format itself is fairly constrained, or if the apps typically try to exclude these cases. But typically, it's always possible to see a next step, without needing to try things out and guess.
Ask HN: How do I learn practical electronic repair?
by juanse | 2025-05-31 06:14:47+00:00
In my country, 2 decades ago there are were plenty of people who knew the basics. Today, it feels like a lost art.

I would like to approach it as a hobby, not like electronic engineer level, but enough to debug problem and change components to a low level.

What is the pragmatic approach in this mission? I reckon it will be valuable in the future that comes.
by _wire_ | 2025-05-31 06:16:14+00:00
Google's Gemini in search just makes up something that arbitrarily appears to support the query without care for context and accuracy. Pure confabulation. Try it for yourself. Ridiculous. It works as memory support if you know the result you're looking for, but if you don't, you can't trust it as far as you can throw it.

If you look carefully at Google Veo output, it's similarly full of holes.

It's plain there's no reasoning whatsoever informing the output.

Veo output with goofy wrongness

https://arstechnica.com/ai/2025/05/ai-video-just-took-a-star...

Tesla FSD goes crazy

https://electrek.co/2025/05/23/tesla-full-self-driving-veers...
by eddythompson80 | 2025-05-31 06:16:46+00:00
I don't if I agree. Crypto, metaverse/vr, wearables, 3d printing, smart homes (iot), gig apps, smart assistants (the ChatGPT pre-alpha version), etc are all examples of fads that spanned tech and mainstream culture.

Sure, the NoSQL fad or the Rust craze didn't spill into pop culture, because that wouldn't make sense. Even something like html5/modern web while it had tremendous impact on pop culture and what the mainstream expectation of a website is like in 2025 vs 2006, the mainstream culture never really cared or commented on it for obvious reasons. The most it got is someone saying "something something, Steve Jobs was right about Flash, something something, html5, the web"

I'm NOT saying that AI/LLM are like the hype for wearables or the metaverse. Not at all. Just point that spills from tech into mainstream culture are common, they just have to make sense. tech impacts the internet, and the internet impacts mainstream culture.
by minimaxir | 2025-05-31 06:17:05+00:00
The simple "AI responses may include mistakes" disclaimer or ChatGPT's "ChatGPT can make mistakes. Check important info." CYA text at the bottom of the UI are clearly no longer sufficient. After years of news stories about LLM hallucinations in fact-specific domains and people still getting burnt by them, LLM providers should be more aggressive in educating users about their fallability since hallucinations can't ever be fully fixed, even if it means adding friction.
by threeseed | 2025-05-31 06:17:28+00:00
> I don’t use RAG, and have no doubt the infrastructure for integrating AI into a large codebase has improved

It really hasn't.

The problem is that a GenAI system needs to not only understand the large codebase but also the latest stable version of every transitive dependency it depends on. Which is typically in the order of hundreds or thousands.

Having it build a component with 10 year old, deprecated, CVE-riddled libraries is of limited use especially when libraries tend to be upgraded in interconnected waves. And so that component will likely not even work anyway.

I was assured that MCP was going to solve all of this but nope.
by ogoffart | 2025-05-31 06:17:54+00:00
> Rust could get a rock solid portable GUI toolkit that doesn't rely on a webview [...], but it's not there yet.

What would you say is missing in Slint?

> probably not much harder than wrapping Qt, to be honest

There are already Qt bindings for rust (cxx-qt, qmetaobject-rs). What's missing from these?
by lurk2 | 2025-05-31 06:21:57+00:00
> No, it's quite easy to make $1mm in a rich country and move to a poorer country and chill if you so desire.

On an aggregate level this is true and contrary to the prevailing sentiment of doomer skepticism, the developed world is usually still the best place to do it. On an individual level, a lot of things can go wrong between here and a million dollars.
by mmooss | 2025-05-31 06:22:12+00:00
> They get sanctioned and can sue instead.

Do you mean, if the government 'sanctions' you, your remedy is to sue the government?

The government can't sanction you without due process. Executive branch agencies have internal legal processes, with administrative judges, that can be appealed to the courts.

Also, you can't sue the government in most cases due to sovereign immunity.
by vouaobrasil | 2025-05-31 06:24:10+00:00
Beyond simple statistics and random sampling, everyone voting is important because let's say 1000 people are required to determine the result beyond reasonable uncertainty. Then those 1000 consequently hold too much power and thus can be easily bribed and the result affected far more easily than if everyone voted.

Of course, psychologically, everyone needs to vote to have a say. But beyond even that psychological thing, everyone voting is really a security measure against tampering.
by zeristor | 2025-05-31 06:27:11+00:00
Abstract

Our proposed ion acceleration scheme, micronozzle acceleration (MNA), generates proton beams with extremely high kinetic energies on the giga-electron-volt (GeV) order. The underlying physics and performance of MNA are studied with two-dimensional particle-in-cell simulations. In MNA targets, a micron-sized hydrogen rod is embedded inside a hollow micronozzle. Subsequent illumination of the target along the symmetric axis by an ultraintense ultrashort laser pulse forms a strong electrostatic field with a long lifetime and an extensive space around the downstream tail of the nozzle. The electric field significantly amplifies the kinetic energies of the accelerated protons, and >~ GeV protons are generated at an applied laser intensity of W/cm2.
by leoedin | 2025-05-31 06:27:36+00:00
Biological muscles are proof that you can make incredibly small and forceful actuators. But the state of robotics is nowhere near them, because the fundamental construction of every robotic actuator is completely different.

We’ve been building actuators for 100s of years and we still haven’t got anything comparable to a muscle. And even if you build a better hydraulic ram or brushless motor driven linear actuator you will still never achieve the same kind of behaviour, because the technologies are fundamentally different.

I don’t know where the ceiling of LLM performance will be, but as the building blocks are fundamentally different to those of biological computers, it seems unlikely that the limits will be in any way linked to those of the human brain. In much the same way the best hydraulic ram has completely different qualities to a human arm. In some dimensions it’s many orders of magnitudes better, but in others it’s much much worse.
by squigz | 2025-05-31 06:27:58+00:00
I guess it depends on what you mean by "quite far"

Regardless of what they choose to use for their leisure time, computers will still be important in school and likely at work in the future. Not to mention that many young people still use computers regularly for leisure (gaming, chatting, etc)

In any case, learning touch typing would still translate somewhat to typing on a phone - certainly things are different, but getting used to where the letters are still helps.
by LegionMammal978 | 2025-05-31 06:30:50+00:00
> What do you mean the “stated goal of full self driving”, which is unachievable? Any vehicle, anywhere in the world, in any conditions? That seems an absurd goal that ignores the very real value in having vehicles that do not require drivers and are safer than humans but are limited to certain regions.

I definitely recall reading some thinkpieces along the lines of "In the year 203X, there will be no more human drivers in America!" which was and still is clearly absurd. Just about any stupidly high goalpost you can think of has been uttered by someone in the world early on.

Anyway, I'd be interested in a breakdown on reliability figures in urban vs. suburban vs. rural environments, if there is such a thing, and not just the shallow take of "everything outside cities is trivial!" I sometimes see. Waymo is very heavily skewed toward (a short list of) cities, so I'd question whether that's just a matter of policy, or whether there are distinct challenges outside of them. Self-driving cars that only work in cities would be useful to people living there, but they wouldn't displace the majority of human driving-miles like some want them to.
by antisol | 2025-05-31 06:30:52+00:00
You are not the only one thinking this. A couple of years ago I was working with some people who were using next.js.

For some feature they wanted, they explained to me how nextjs has this great "feature", which was "really exciting" and allowed all kinds of fancy stuff that I've been doing since about 2003. They were going to turn on next's server-side rendering.

My immediate reaction was to point out "congratulations, you've just reinvented PHP, only with a much much worse language and two extra servers".

A lot of these "solutions" use three servers, not the two you mention: you use one server you don't have any control over, e.g google static hosting, to host the "compiled" static stuff - then you have that point at a server running node and another copy of all your terrible javascript, and then finally a third server running some more sensible stack, which could easily and more cleanly do the job of the other two using tech that isn't trash.

It's called "progress", and people like you and me just need to get with the times, it seems.
by 9x39 | 2025-05-31 06:31:05+00:00
Gemini appears tuned to try to handle the typical questions people type in, while more traditional things you search for get some confabulated nonsense.

I've observed a great deal of people trust the AI Overview as an oracle. IMO, it's how 'normal' people interact with AI if they aren't direct LLM users. It's not even age gated like trusting the news - trusting AI outputs seems to cross most demographics. We love our confident-based-on-nothing computer answers as a species, I think.
by dragonwriter | 2025-05-31 06:31:44+00:00
> The declaration of war and your uniform make the homicide legal.

Declarations of war have very little international importance any more, since the recognition of the crime of aggression; either you are engaging in aggressive war, which a declaration does nothing to legitimize, or you are engaging in defensive war against an aggressor, where it is the aggression, not any declaration, that gives your fighting legitimacy.
by throwaway81523 | 2025-05-31 06:32:08+00:00
The running time of a CUDA kernel is apparently impossible to determine except by experiment and measurement, and might be nondeterministic. By contrast for a more typical CPU, there's a compiler whose assembly output you can examine, and there's a processor manual that gives the cycle timing of each instruction. So you can compute the running time at least of inner loops that stay in cache, and that sort of thing.
by potamic | 2025-05-31 06:33:24+00:00
A 100% sample is unattainable, not just practically, but fundamentally. Even if you made voting mandatory and ensured collection of every single vote, there will always be people who will fudge their vote because they are not interested in the process. I argue that any election is only representative of people engaged with the process and that fundamentally cannot change. Within that subset, you shouldn't need 100% sampling for high confidence.

But agree that random distribution is key to this, but I don't see how that could change with the messaging that every one must vote, versus saying just vote if you're interested.