MurphyA/hacker-news huggingface dataset:
by impendia | 2025-06-26 17:12:32+00:00
Personally, I fall somewhere in the middle. I'd be happy to pay a modest bit of money to buy a simple app, and see if it helps -- but I'm very reluctant to sign up for a subscription.

Perhaps ironically, the less the app claims to do, the more likely I am to be interested.

I've only signed up for a paid mental health app subscription once -- and that was an app designed by a well-known psychologist with both an M.D. and a Ph.D., and even then only after reading his book.
by plorntus | 2025-06-26 17:13:23+00:00
Honestly tried it out, I wanted to like it but in its current form I found myself frustrated enough to just end the 'call' and close the app. Been learning Spanish for quite some time now so wasn't put off by the 'it always talks in X language' thing people are talking about.

The thing that put me off was the speech recognition. I am not in a loud environment and I wasn't even talking and it was picking up responses and responding to it before I even opened my mouth. It blazed through the 'preferences' set up itself making up responses. Then when I did get to talk it just simply got my answers wrong. It would often interject too at random during my sentences.
by kjkjadksj | 2025-06-26 17:13:26+00:00
Seems to me shelfspace is more significant than billboard space. E.g. is the brand out advertising another or did they lease more shelfspace at sephora? Is sephora out advertising other makeup retailers or do they simply have the sales they do from a walmart sort of regional agglomeration strategy that eliminated other options from the market for consumers to choose among? Hard to imagine a successful ad campaign today that didn’t move in lock step with simply putting the product in front of more consumers in limited marketplaces where their choosing your product would be inevitable.
by mexicocitinluez | 2025-06-26 17:13:41+00:00
Being asked if I'm kidding by the person comparing Google glasses to machine learning algorithms is pretty funny ngl.

And the "I don't use these tools and never will" sentiment is rampant in the tech community right now. So yes, I am serious.

Youre not talking about the blog post that completely ignored agentless uses are you? The one that came to the conclusion LLMs arent useful despite only using a subset of its features?
by bobjordan | 2025-06-26 17:13:45+00:00
Thank you for sharing your deep experience. It's a valid perspective, especially from an expert in the world of testing.

You're right to call out the need for vigilance and to place the burden of proof on those of us who advocate for this tool. That burden is not met by simply trusting the AI, you're right, that would be foolish. The burden is met by changing our craft to incorporate the necessary oversight to not be reckless in our use of this new tool.

Coming from the manufacturing world, I think of it like the transition in metalwork industry from hand tools to advanced CNC machines and robotics. A master craftsman with a set of metal working files has total, intimate control. When a CNC machine is introduced, it brings incredible speed and capability, but also a new kind of danger. It has no judgment. It will execute a flawed design with perfect, precision.

An amateur using the CNC machine will trust it blindly and create "plausibly good" work that doesn’t meet the specifications. A master, however, learns a new set of skills: CAD design, calibrating the machine, and, most importantly, inspecting the output. Their vigilance is what turns reckless use of a new tool into an asset that allows them to create things they couldn't before. They don't trust the tool, they trust their process for using it.

My experience with LLM use has been the same. The "vigilance" I practice is my new craft. I spend less time on the manual labor of coding and more time on architecture, design, and critical review. That's the only way to manage the risks.

So I agree with your premise, with one key distinction: I don’t believe tools themselves can be reckless, only their users can. Ultimately, like any powerful tool, its value is unlocked not by the tool itself, but by the disciplined, expert process used to control it.
by WorldMaker | 2025-06-26 17:13:46+00:00
It's not a terrible description of what Borderlands complex web of shaders are doing. A base layer part of it is effectively a cell-shader, but Borderlands is doing more other things, too.

Relatedly, cell-shading and other shaders are sometimes very heavy GPU compute workloads (which would also be far more expensive if they needed to run on the CPU due to a bad graphics card or driver). It seems funny to dismiss cell-shading as "not super demanding", when cell-shading was a technical dream or expensive technical demo thing to do for quite a while in the time before modern GPU shaders.
by observationist | 2025-06-26 17:14:10+00:00
There's no reason to think AI will stop improving, and the rate of improvement is increasing as well, and no reason to think that these tools won't vastly outperform us in the very near future. Putting aside AGI and ASI, simply improving the frameworks of instructions and context, breaking down problems into smaller problems, and methodology of tools will result in quality multiplication.

Making these sort of blanket assessments of AI, as if it were a singular, static phenomena is bad thinking. You can say things like "AI Code bad!" about a particular model, or a particular model used in a particular context, and make sense. You cannot make generalized statements about LLMs as if they are uniform in their flaws and failure modes.

They're as bad now as they're ever going to be again, and they're getting better faster, at a rate outpacing the expectations and predictions of all the experts.

The best experts in the world, working on these systems, have a nearly universal sentiment of "holy shit" when working on and building better AI - we should probably pay attention to what they're seeing and saying.

There's a huge swathe of performance gains to be made in fixing awful human code. There's a ton of low hanging fruit to be gotten by doing repetitive and tedious stuff humans won't or can't do. Those two things mean at least 20 or more years of impressive utility from AI code can be had.

Things are just going to get faster, and weirder, and weirder faster.
by munificent | 2025-06-26 17:15:42+00:00
> New “efficiency features” regularly get introduced in ILS and written into contracts. One of the most transformative has been the use of parametrics. Unlike traditional insurance, which calculates payouts based on actual losses (what’s called indemnity), parametric insurance uses preset triggers to determine whether money gets released. During an interview, a London-based parametric expert gave me this example of a parametric scenario: If, during a hurricane, wind speeds off the Florida coast hit a predetermined trigger speed — say 175 mph — at a trigger distance of two miles offshore within a preset longitude and latitude grid, the payout is, in theory, immediate. No actual damage need occur; the trigger measures just need to be met.

Wow, that is absolutely begging for exploitation.

Whoever controls the authority reporting these figures now controls whether these bonds pay out. That in turn means that whoever holds those bonds has a huge financial incentive to manipulate what that authority says.

Put another way, if you're holding a bond that will cost you $100 million if a hurricane windspeed hits 175 MPH, then you have $99 million bucks that are worth spending trying to get the NOAA to say anything but that.
by bluefirebrand | 2025-06-26 17:16:48+00:00
I think it's analogous to physical labour

In the past someone might have been physically healthy and strong enough to physically shovel dirt all day long

Nowadays this is rarer because we use an excavator instead. Yes, a professional dirt mover is more productive with an excavator than a shovel, but is likely not as physically fit as someone spending their days moving dirt with a shovel

I think it will be similar with AI. It is absolutely going to offload a lot of people's thinking into the LLMs and their "do it by hand" muscles will atrophy. For knowledge workers, that's our brain

I know this was a similar concern with search engines and Stack Overflow, so I am trying to temper my concern here as best I can. But I can't shake the feeling that LLMs provide a way for people to offload their thinking and go on autopilot a lot more easily than Search ever did

I'm not saying that we were better off when we had to move dirt by hand either. I'm just saying there was a physical tradeoff when people moved out of the fields and into offices. I suspect there will be a cognitive tradeoff now that we are moving away from researching solutions to problems and towards asking the AI to give us solutions to problems
by om2 | 2025-06-26 17:16:59+00:00
We have contributed a number of upstream fixes

$ cd gnome-libxml2.git $ git log --oneline --author=@apple.com | wc -l 43

The main reason we have a fork at all is that upstream libxml2 has broken source and binary compatibility in various ways, and we can't take those changes because libxml2 is public API on our platforms. We do make an effort to upstream all security fixes, though we sometimes get to it only after we ship.
by o11c | 2025-06-26 17:17:08+00:00
Noncompliant, since `malloc(0)` is specified to return a unique pointer if it's not `NULL`.

On most platforms an implementation could just return adjacent addresses from the top half of the address space. On 32-bit platforms it doesn't take long to run out of such address space however, and you don't want to waste the space for a bitmap allocator. I suppose you could just use a counter for each 64K region or something, so you can reuse it if the right number of elements has been freed ...
by testing22321 | 2025-06-26 17:17:42+00:00
We put 7.8kw on our roof on a snowy mountain town in Canada in a tight valley. In 12 months it generated $950 worth of power at $0.13/kwh, and we now have no power bill for our house and all heating and cooling with a heat pump.

We tore out the old natural gas furnace and had the line disconnected, saving us about $2k/year for the heating.

Game changer.
by wiradikusuma | 2025-06-26 17:17:50+00:00
"Stack: OpenAI API (GPT-4o for data generation)" -- I wonder if someday we'll have a generic API like how it's done in Java (e.g., Servlet API implemented by Tomcat, JBoss etc), so everyone can use their favorite LLM instead of having to register each provider like streaming services e.g. Disney+, Netflix, etc.
by Justsignedup | 2025-06-26 17:18:11+00:00
I had a kid at 22, I am now 40 with a kid going to college. I can echo this exact sentiment.

However at 22 I wasn't the experienced person I am today. Nor was I stable, nor could I jump on opportunities like my peers could.

If having a child in your early 20s would mean not losing opportunities in progressing in a career, at least with enough free childcare and food to feed the children, people could be more inclined to have children while they get their life together. Our culture of moving away from home is also a big problem -- having 2 sets of grandparents helping raise a child REALLY helped me at my youth not miss out on youth and still raise my child.

kids between 25-32 is something our society should aim to be as practical and pleasant as possible.
by jmyeet | 2025-06-26 17:18:44+00:00
So this is the AI gold rush and of course this isn't the first AI language product I've seen of course. No hate to you or your product but I have a question.

If AI succeeds, will we even need language learning? Language learning is notoriously difficult and time-consuming. We're rapidly approaching a future like Star Trek of universal translators.

If so, what is the realistic future for AI language learning products?
by FridayoLeary | 2025-06-26 17:18:47+00:00
The author offers no major new insights on the effectiveness of drones. His counter argument is against the maximalists who claim quadcopters are revolutionising warfare and render armour and artillery obsolete. But nobody serious ever suggested that. The same way tanks are relevant despite rpgs. They simply represent a new element in the battlefield, and a useful one as well. The fact that they are not ideally suited for dropping bombs doesn't matter. They are great for surveillance and giving units situational awareness, and the fact that they can occasionally be used to attack targets that otherwise would be impossible simply augments their usefulness. The article is interesting, but it's attacking a straw man. I have a great respect for the ukrainian armed forces but to be perfectly honest their combat effectiveness is not exactly world beating. The suggestion that NATO should be taking lessons from how Ukraine is fighting Russia is odd.
by wiradikusuma | 2025-06-26 17:19:13+00:00
I still don't understand the difference between Gemma and Gemini for on-device, since both don't need network access. From https://developer.android.com/ai/gemini-nano :

"Gemini Nano allows you to deliver rich generative AI experiences without needing a network connection or sending data to the cloud." -- replace Gemini with Gemma and the sentence still valid.
by trollbridge | 2025-06-26 17:19:31+00:00
It should be pointed out that VMware started as a tiny, scrappy company mostly focused on selling workstation seats for you to run Windows on your Linux computer (which I did back circa 1999, so I could use Linux on my desktop), and VirtualBox started out from InnoTek, a tiny company which was essentially making software to emulate Windows on OS/2, and then later did a contract with Connectix to run OS/2 on Windows (or other hosts) using Virtual PC.

Connectix got bought by Windows, and InnoTek got bought by Sun, which is now Oracle. Connectix themselves started as a scrappy outfit making it possible to run DOS/Win95 on a Mac.

The core emulation was pretty much done and stable and optimised before the billion-dollar corps bought them out.
by clbrmbr | 2025-06-26 17:19:49+00:00
Nice! I’ve wanted this for years.

Suggestion: you may be able to integrate SRS into the conversation. —- you could encourage the model to use certain words, and more importantly you can track the student’s active use of words that are on the review list, basically acting as if it were an SRS step. — this could totally eliminate the need for flashcards.
by danielhanchen | 2025-06-26 17:20:05+00:00
Made some GGUFs if anyone wants to run them!

./llama.cpp/llama-cli -hf unsloth/gemma-3n-E4B-it-GGUF:UD-Q4_K_XL -ngl 99 --jinja --temp 0.0

./llama.cpp/llama-cli -hf unsloth/gemma-3n-E2B-it-GGUF:UD-Q4_K_XL -ngl 99 --jinja --temp 0.0

I'm also working on an inference + finetuning Colab demo! I'm very impressed since Gemma 3N has audio, text and vision! https://docs.unsloth.ai/basics/gemma-3n-how-to-run-and-fine-...
by reverendsteveii | 2025-06-26 17:21:11+00:00
> It uses Meta’s Private Processing technology, which the company claims will prevent it and other third parties from snooping on your messages.

There is no way that a thing owned by Meta can read your messages but Meta can't. I especially don't believe it because Meta already shares data between WhatsApp and Facebook for marketing and advertising purposes (https://theconversation.com/why-meta-is-in-trouble-in-nigeri...) and has been fined for more money than any other company in the history of the GDPR for transferring European user data out of the jurisdiction of the GDPR (https://www.forbes.com/sites/siladityaray/2023/05/22/meta-fi...).

tldr - they say that they're not reading your messages. they also have a history of violating users' privacy and then lying about it. take it for what you will.
by zdragnar | 2025-06-26 17:23:10+00:00
If you have a house in the countryside, then water and food are relatively easy. You've got your own well and septic system for water, and plenty of room to stock up on food, plus you can supplement your diet by growing your own vegetables and raising chickens, fishing or hunting as seasonally appropriate per your local regulations.

The well and septic system require no real effort on your part once installed, though you may find harvesting your own food to be too time consuming or labor intensive to really be actually independent.
by I_Lorem | 2025-06-26 17:24:12+00:00
He's making a good point on trust, but, really, doesn't the trust flow both directions? Should the Sr. Engineer rubber stamp or just take a quick glance at Bob's implementation because he's earned his chops, or should the Sr. Engineer apply the same level of review regardless of whether it's Bob, Mary, or Rando Calrissian submitting their work for review?
by vjerancrnjak | 2025-06-26 17:24:58+00:00
The app is optimized on the whole population, not on individual level. They even publish papers on global optimization.

These kinds of learning apps are destined to become mediocre over time.

The learning metric is so easy to capture, the learning content so easy to produce, yet no one has an individualized loop to make learning work well.

For example, I'd press "Training" on Duolingo, and would get nowhere. Same lessons all of the time. Bread and water.
by mzs | 2025-06-26 17:25:01+00:00
Your site is fine, thank you very much, I was not able to able to save it in the internet archive though: https://web.archive.org/save/https://www.solipsys.co.uk/ZimE...

"Save Page Now could not capture this URL because it was unreachable. If the site is online, it may be blocking access from our service."
by bluefirebrand | 2025-06-26 17:25:05+00:00
> And the "I don't use these tools and never will" sentiment is rampant in the tech community right now

So is the "These tools are game changers and are going to make all work obsolete soon" sentiment

Don't start pretending that AI boosters aren't everywhere in tech right now

I think the major difference I'm noticing is that many of the Boosters are not people who write any code. They are executives, managers, product owners, team leads, etc. Former Engineers maybe but very often not actively writing software daily
by morkalork | 2025-06-26 17:25:15+00:00
That is true, although I think a lot of what can be invested in, is transferable. Control software, targeting, AI could be adapted to larger or smaller scale drones. Manufacturing capabilities can be as well. ISR drones are pervasive and it used to be uneconomical to shoot down a relatively cheap one, like an Orlan, with something that cost as much or more. Now there's cheap counter-ISR FPVs. I don't think the future is manually guided at all though.
by the_other | 2025-06-26 17:25:53+00:00
Same.

Sometimes I enjoy the translucent menus. They make the machine look "glossy" and expensive. But they're definitely harder to read than opaque flat ones.

With "reduce transparency" on, it's better, but the menubar still isn't white. It's a textured light grey that's closer to the look of an unfocused app window than the solid, dependable, flat thing I wish it still was.
by pierrec | 2025-06-26 17:26:26+00:00
This was basically the original plan, but I had to make some choices with my limited resources. After going down the path of "manually" placing audio sources, it becomes difficult to switch to procedural layout, I would basically have to start over from scratch in terms of composition. Nonetheless I might revisit it in the future as I've improved my ability to lay out the sound, it might be easier to expand it considerably.
by readthenotes1 | 2025-06-26 17:26:35+00:00
Perplexity.ai gave an easier to understand response than Gemini 2.5 afaict.

Gemini nano is for Android only.

Gemma is available for other platforms and has multiple size options.

So it seems like Gemini nano might be a very focused Gemma everywhere to follow the biology metaphor instead of the Italian name interpretation
by bostick | 2025-06-26 17:26:42+00:00
I am also interested in the Crucial SSD 5184 hour thing. Here are the options as I see them:

* related to 5124 hours = 2^64 picoseconds

Then how to account for the extra 60 hours? Maybe there is some rounding error involved with the arithmetic? Maybe initialized at -60 hours and somehow the first rollover did not trigger any bad behavior? Maybe it IS 5124 hours and the formatting is incorrect?

* NOT related to 5124 hours

Counting picoseconds is ridiculously precise for this scenario, so ignore the fact that it is close to 5124 hours. What other frequencies and limits could break at 5184 hours?

I would love know the EXACT time that the trouble begins. Is it EXACTLY 5124 hours? How many minutes, seconds, etc? But of course, I would love to know the root cause.

I love tracking down date / time bugs. See:

What happened on December 13, 2024? [1]

[1] https://bostick.github.io/blog/2025/04/what-happened/
by mariano54 | 2025-06-26 17:27:14+00:00
ISSEN is designed from the ground up for this use case.

* curriculum, completely customizable, with grammar, roleplay, topics, speaking speech, transcript, dictionary, corrections, etc

* prompting and AI models all chosen to be a better fit for multilingual, easy to understand, etc.

* the tutor actively tries to teach you, it's not an assistant

* integrated flashcards that go hand in hand with the speaking immersion
Ask HN: Why does my Node.js multiplayer game lag at 500 players with low CPU?
by hnroo99 | 2025-06-26 17:27:44+00:00
I’m hosting a turn-based multiplayer browser game on a single Hetzner CCX23 x86 cloud server (4 vCPU, 16GB RAM, 80GB disk). The backend is built with Node.js and Socket.IO and is run via Docker Swarm. I use also use Traefik for load balancing.

Matchmaking uses a round-robin sharding approach: each room is always handled by the same backend instance, letting me keep game state in memory and scale horizontally without Redis.

Here’s the issue: At ~500 concurrent players across ~60 rooms (max 8 players/room), I see low CPU usage but high event loop lag. One feature in my game is typing during a player's turn - each throttled keystroke is broadcast to the other players in real-time. If I remove this logic, I can handle 1000+ players without issue.

Scaling out backend instances on my single-server doesn't help. I expected less load per backend instance to help, but I still hit the same limit around 500 players. This suggests to me that the bottleneck isn’t CPU or app logic, but something deeper in the stack. But I’m not sure what.

Some server metrics at 500 players:

- CPU: 25% per core (according to htop)

- PPS: ~3000 in / ~3000 out

- Bandwidth: ~100KBps in / ~800KBps out

Could 500 concurrent players just be a realistic upper bound for my single-server setup, or is something misconfigured? I know scaling out with new servers should fix the issue, but I wanted to check in with the internet first to see if I'm missing anything. I’m new to multiplayer architecture so any insight would be greatly appreciated.
by overfeed | 2025-06-26 17:27:52+00:00
> Care to explain how an ethno-nationalist government implemented socialism?

By using the state treasury to provide disproportionate infrastructure and services to the ruling ethic minority, while leaving the bantustans - with no say in national politics or budget - to largely fend for themselves. This incidentally has similarities to the US/Puerto Rico dynamic.

All the things you complain about can be explained by regression to mean[1], which the not even the apartheid government would have been able to prevent had they decided to adopt an egalitarian governance model.

edit: I didn't even get into how the "ethno-nationalist government" seized the means of production for the express benefit of a specific ethno.

1. I fully expect that the per-capita X (for any X you're claiming is worse) has actually improved for South Africans - all South Africans - between 1990 and now.