MurphyA/hacker-news huggingface dataset:
by norapap | 2025-11-26 19:52:50+00:00
They can be cancelled if CPU drops below the scale-in threshold. In my case the activities were CPU-heavy, batch-style, and not client-facing — so preferred occasional retries and slightly longer runtimes over blowing up the AWS bill. For that workload, CPU-based autoscaling was perfectly fine.

I originally ran this setup on Temporal Cloud, and pulling detailed worker/queue metrics directly from Cloud can be tricky... you need to expose custom worker metrics yourself, then pipe them into CloudWatch. If you host Temporal yourself, it is easier:)
by toast0 | 2025-11-26 19:53:06+00:00
Oh, the overall smart status is mostly useless. But some of the individual fields are helpful.

The ones for relocated sectors, pending sectors, etc. When those add up to N, it's time to replace and you can calibrate that based on your monitoring cycle and backup needs. For a look every once in a while, single copy use case, I'd replace around 10 sectors; for daily monitoring, multiple copies, I'd replace towards 100 sectors. You probably won't get warranty coverage at those numbers though.

Mostly I've only seen the smart status warning fire for too many power on hours, which isn't very useful. Power on hours isn't a good indicator of impending doom (unless there's a firmware error at specific values, which can happen for SSDs or spinners)
by bigbadfeline | 2025-11-26 19:53:20+00:00
> I am fully aware that any negative sentiment towards social media makes young and insecure people terribly sad

Ad hominem through the back door coupled with missing the point entirely.

"Any negative sentiment" is very different from legislation and enforcement armed with machine guns and grenades.

Then, what is "social media"? It could be anything at all and it's likely to be defined as anything the king doesn't like, because... what else?

> I would make an exception for basic protocols

Once you are "extremely in favor of blocking young people" nobody would ask you about your subtle nuances, that's a given. I would suggest expressing only extremely cautious optimism because you obviously don't understand what kind of forces are involved here.
by 0manrho | 2025-11-26 19:53:41+00:00
> Any guidelines for what's a good used enterprise SSD

Micron, Samsung and Intel (enterprise, branded DCxxxx) / SK Hynix / Solidigm (Intel sold it's SSD business to SK which they merged into Solidigm) are the go to's for brands. HGST can also be good.

The best guideline is buying from reputable sellers with a decent volume of business (eg, >1000 sales with high ratings on ebay) that focus on enterprise hardware and have a decent return/DOA policy.

You should expect these drives to be partially worn (regardless of the SMART data, that often gets wiped) if for no other reason than the secure erasure process mandated by a lot of org's data security policies resulting in multiple intensive disk writes, but also due to actually having been used. Drives that have recently been released (within 12 months, eg Micron 7600) are suspect as that implies there was a bad batch or that they were misused - especially if they aren't write focused drives. Not uncommon for a medium to smaller-end large business pinching pennies and buying the wrong drives and then wrecking them and their vendor/VAR rejecting warranty claims. That said, that's not always the case, it's entirely possible to get perfectly good recently made drives from reputable 2nd hand market sellers, just don't expect a massive discount in that case.

Otherwise best advice I can give you, is redundancy is your friend. If you can't afford buy at least 2 drives for an array, you should probably stick to buying new. I've had a few lemons over the years, but since availability on the second hand market for any given model can be variable and you tend to want to build arrays from like-devices, you should purchase them with the expectation that at least 1 per batch will be bad just to be safe. Worst case scenario you end up with an extra drive/hotspare.
by surgical_fire | 2025-11-26 19:53:45+00:00
> things written on paper.

"things written on paper" is the basis of any serious, respectable country. "Things written on paper" should be respected, because when you are serious about your commitments, words matter.

I don't want to see the country I live in become a shithole because local armed forces or police think themselves above the law.

The ultimate legitimacy test is whether you are serious about the things you sign. Not if some proto-fascist wants to tear down institutions.
by soulbadguy | 2025-11-26 19:54:00+00:00
As compiler have become more sophisticated, and hardware architecture more complicated, there are been a growing sentiment that some of the code transformation done by modern compiler make the code hard to reason about and to predict.

A lot of software engineer are seeing this as compiler engineer only caring about performance as opposed to other aspect such as debuggability, safety, compile time and productivity etc... I think that's where the "sabotage" comes from. Basically the focus on performance at the detriment of other things.

My 2 cents : The core problem is programmers expecting invariant and properties not defined in the languange standard. The compiler only garanty things as defined in the standard, expecting anything else is problematic.
by liamconnell | 2025-11-26 19:54:02+00:00
Unfortunately for OpenAI, they are not positioned to capture value from any of the "big margin" use cases that they highlight as key to their future. I think all of these are pretty unrealistic for them:

- Revenue sharing from drug discovery (called out by OpenAI CFO): Why would a pharma company give away the upside to a commoditized intelligence layer? Why would OpenAI have a more compelling story than Google Deep Mind, which has serious accolades in this space?

- Media generation for ads and other content: For ads, OpenAI is facing off against Google, Meta and Amazon, all of which have existing relationships with advertisers. For the foreseeable future, AI content will be a major discount product compared to humans. OpenAI will not get to charge $1M for an ad like a production company does. So the TAM of ad production (~$50B) shrinks below $1B because AI deflates prices so much.

- Other agent use cases: OpenAI doesnt have a surface to build these on. Google has chrome, Microsoft has office, Apple has OS's. The other use cases like coding will be a low-margin competition between model providers until some of them throw in the towel. The players with the best cash position win - and thats not OAI.

I think the place that they could win is retail (also called out by OAI CFO). They made deals with Etsy and other small retailers. I was fixing my guitar the other day and would have instantly bought the tools it had suggested that I would need. The problem is that they have to win against Amazon here, and there is zero chance of a partnership for obvious reasons.
by vee-kay | 2025-11-26 19:54:14+00:00
Awesome, thanks. I think the video I had linked was Google's tribute to this Power Of Ten video that you have linked, a classic video that demonstrates the scale of the Universe from the micro to the macro perspectives in a scaling increase by a factor of ten for each scene.

Another relevant video (thanks to user christev for sharing the link): A Brief History of Geologic Time: https://youtu.be/rWp5ZpJAIAE

Absolutely humbling to realise how infinitesimally small and irrelevant our existence is, in the grand scheme of theme. Nature and science are amazing.
by TrainedMonkey | 2025-11-26 19:54:16+00:00
Fundamentally because demand and supply curves are lagged. This drives DRAM flood and drought cycles. Right now high DRAM prices are driving fab investment up and demand down. In 3-5 years new fabs will cause DRAM glut that will drive prices down. Lower prices will stimulate demand via things like doubling DRAM size in consumer electronics as companies compete on getting the number bigger. Eventually demand curve will eclipse the supply and we will end up in the DRAM drought again.

This time things are further complicated by the fact that the world is investing a sizable chunk of GDP into building RAM hungry data centers in hopes of building a god which will convert the rest of the world into data centers.
by senotrusov | 2025-11-26 19:54:18+00:00
>this lets you use Gemini 2.5 Pro for free with generous usage limits

Considering that access is limited to the countries on the list [0], I wonder what motivated their choices, especially since many Balkan countries were left out.

[0]: https://developers.google.com/gemini-code-assist/resources/a...
by mbesto | 2025-11-26 19:55:09+00:00
> This kind of task is perfect for AI in a way that doesn't take away too much from the human experience.

Not the current form of AI. I regularly use Project Farm to find the best "insert tool". In an ideal world a robot runs all of these tests in perpetuity covering every physical appliance possible (with every variation, etc.). However, current AI cannot do this. Obviously LLMs can't do this because they don't operate in the physical world.
by __jonas | 2025-11-26 19:56:32+00:00
Not sure where to submit a bug report but I chose the option for kids and got this as the 'correct' message for a painting:

> Correct! Well done, detective!

> This image shows authentic human photography with natural imperfections, consistent lighting, and realistic proportions that indicate genuine capture rather than artificial generation.

> Albert Pinkham Ryder, Seacoast in Moonlight (1890, the Phillips Collection, Washington)

The image is not photography, I guess technically it's a photograph of a painting but still, confusing text.
by vee-kay | 2025-11-26 19:56:50+00:00
I think the video I have linked above is Google's tribute to this Power Of Ten video (linked below, thanks to user dtgriscom for sharing the link in another comment), a classic video that demonstrates the scale of the Universe from the micro to the macro perspectives in a scaling increase by a factor of ten for each scene.

Power of 10: https://www.youtube.com/watch?v=0fKBhvDjuy0

Another relevant video (thanks to user christev for sharing the link): A Brief History of Geologic Time: https://youtu.be/rWp5ZpJAIAE

Absolutely humbling to realise how infinitesimally small and irrelevant our existence is, in the grand scheme of theme. Nature and science are amazing.
by zaptheimpaler | 2025-11-26 19:57:06+00:00
I would love to set this up, I really want all my chats to be on one platform. The problem is, the AI companies seem to want the opposite.

My main concern is how well do all the extra features work compared to the native versions? Like web search, RAG on a document, or deep research, adding images, voice chats - my understanding is the models providers don't provide any API's for any of this stuff, so you have your own implementations of all the extra stuff right? Usually I find the open source versions of all these features aren't up to par with the corporate versions and they lag behind in development.
by redwall_hp | 2025-11-26 19:57:09+00:00
Map/filter/reduce are idiomatic Java/Kotlin/Scala.

SELECT thing1, thing2 FROM things WHERE thing2 != 2;

val thingMap = things.map { it.thing2 to it.thing2 }.filter { it.thing2 !=2 }

Then you've got distinct(), sorting methods, take/drop for limits, count/sumOf/average/minOf/maxOf.

There are set operations, so you can do unions and differences, check for presence, etc.

Joins are the hard part, but map() and some lambda work can pull it off.
by az09mugen | 2025-11-26 19:57:12+00:00
As long as LLVM (C++ but still) is not rewritten is rust [0] , I don't buy it. C is like JavaScript, it's not perfect, is everywhere and you cannot replace it without a lot of effort and bugfix/regression tests.

If I take for example sqlite (25 years old [3]) there are already 2 rewrites in rust [1] and [2], and each one has its bugs.

And as an end user I'm more enclined to trust the battle-tested original for my prod than its copies. As long as I don't have the proof the rewrite is at least as good as the original, I'll stay with the original. Simple equals more maintainable. That's also why sqlite maintainers won't rewrite it in any other language [4].

The trade of rust is "you can lose features and have unexpected bugs like any other language, but don't worry they will be memory safe bugs".

I'm not saying rust is bad and you should not rewrite anything in it, but IMHO rust programmers tend to overestimate the quality of the features they deliver [5] or something along these lines.

Memory safe != good product

[0] https://rustc-dev-guide.rust-lang.org/overview.html [1] https://github.com/epilys/rsqlite3 [2] https://github.com/tursodatabase/turso/ [3] https://sqlite.org/chronology.html [4] https://www.sqlite.org/whyc.html [5] https://www.phoronix.com/news/Ubuntu-25.10-Broken-Upgrade
by schmuckonwheels | 2025-11-26 19:57:28+00:00
I get it, you did what you had to do, but you're not the only example.

They have the knowledge and it's existed in the past (Xserve) but they will never do it again because they design and sell furniture now.

Tell me they couldn't design a Mac Mini with holes for rack ears, built in BMC or serial console.... even if it was a specialty product people would pay a premium
by dilippkumar | 2025-11-26 19:57:45+00:00
Thanks for the pointer.

I went down the rabbithole, and as far as I can tell, you have to axiomatically assume infinities are real in order to prove Goodstein’s theorem.

I challenge the existence of ordinal numbers in the first place. I’m calling into question the axioms that conjure up these ordinal numbers out of (what I consider sketchy) logic.

But it was a really fun rabbithole to get into, and I do appreciate the elegance of the Goodstein’s theorem proof. It was a little mind bending.
by hummbl-dev | 2025-11-26 19:57:47+00:00
Sharing a case study from building HUMMBL—a systematic mental models framework for complex problem-solving.

The meta-recursive twist: I used the framework's own models to architect, validate, and deploy it.

Key technical decisions:

1. 6 transformations, not categories: Perspective, Inversion, Composition, Decomposition, Recursion, Systems. Every model maps to exactly one.

2. Base-N scaling: Base6 for literacy, Base42 for wicked problems, Base120 for pedagogical completeness. Match complexity to problem tier.

3. Quantitative wickedness scoring: 5-question rubric (variables, stakeholders, predictability, interdependencies, reversibility) replacing subjective tier assignment.

4. Multi-agent development: Treated Claude, ChatGPT, Windsurf, and Cursor as team members with defined roles. SITREP protocol for coordination. 4x parallel execution.

Results: - 120 models, 9.2/10 quality score - 140 chaos tests, 100% pass rate - MCP server for Claude Desktop - 22 months, solo founder

Tech stack: React, Cloudflare Workers, D1, TypeScript

Links: - Live: hummbl.io - MCP: npm @hummbl/mcp-server - Case study: https://github.com/hummbl-dev/mcp-server/blob/main/docs/case...

Would love feedback on the framework architecture and multi-agent coordination approach. AMA about the development process.
by jsheard | 2025-11-26 19:58:11+00:00
> Continuing to act like these ugly hacks are a normal way of doing business, is a continual signal to Apple that they don't need to build a rack-mount PC or server ever again.

They technically still have the Rack Mac Pro, but that's such a half-assed offering that it's easy to forget it exists. It's a huge 5U chassis but if you look at the internals it's comical how little of the space is actually used for anything, because they kept the same layout as the Intel version which was designed to host multiple high-power GPUs, but dropped dGPU support in the Apple Silicon transition.
by rolph | 2025-11-26 19:58:14+00:00
sarcophagus looks to be 2 feet by 7 feet based on scale of objects in the image.

is 1.75 cubic feet of solid material reasonable?

the image displays distinct relief cracks of a drying wet slurry, the dark staining inside the coffin suggests high fluid mark was maybe 4inches, it may have knocked an urn over, before recedeing, and evaporating.

while not up on the finer points of such burial practice, it doesnt seem unreasonable that a consideral amount of flowers and other plant materials may be involved, there should be considerable pollen present, potassium and sodium salts of the decedent, adipocere, and perhaps diatoms dependent on the nature of the soil, and source of water percolating into the sarcophagus.

i believe considering it to be just mud, would be to overlook, a volume of pertinant discovery.
by locknitpicker | 2025-11-26 19:58:37+00:00
> This article actually explains how this bug in particular could have been avoided.

Not really. The article is a textbook example of hindsight bias. It's a simplistic analysis of a far more complex problem that goes over the blogger's head, and results in a string of simplistic assertions that fail to address any of the issues. Read up on the definition of monday morning quarterback.
by Animats | 2025-11-26 19:58:42+00:00
> Somebody has to come up with an idea first.

There are lots of ideas. Some may work.

The space in which people seem to be looking is deep learning on something other than text tokens. Yet most successes punt on feature extraction / "early vision" and just throw compute at raw pixels. That's the "bitter lesson" approach, which seems to be hitting the ceiling of how many gigawatts of data center you can afford.

Is there a useful non-linguistic abstraction of the real world that works and leads to "common sense"? Squirrels must have something; they're not verbal and have a brain the size of a peanut. But what?
by Sanzig | 2025-11-26 19:58:44+00:00
I thought I was pretty clear that I don't see this happening for hundreds of years at least.

The engineering problem is insurmountable today. But there doesn't seem to be any reason it couldn't be done eventually, given our technological trajectory, unless we believe we are truly on the precipice of severe diminishing returns in most science and engineering fields, and I just don't see that right now.

George Cayley figured out how to build an airplane in 1799, but it wasn't for another century until materials science and high power-to-weight ratio engines made the Wright Flyer possible.

There are plenty of depths to plumb in space systems engineering that we haven't even really had a proper look at yet. A Mars mission with chemical propulsion is hard, but could be made substantially easier with nuclear thermal propulsion - something we know should work, given the successful test fires on the NERVA program back in the 60s. First stage reusability was fantasy 15 years ago, today it's routine.

Obviously, I'm extrapolating a long way out, and maybe at some point we'll run against an unexpected wall. But we'll never know until we get there.
by gizzlon | 2025-11-26 19:58:47+00:00
What are "untrusted URLs" ? Or, more to the point: What are trusted URLs?

Prompt injection is just text, right? So if you can input some text and get a site to serve it it you win. There's got to be million of places where someone could do this, including under *.google.com. This seems like a whack-a-mole they are doomed to lose.
by godelski | 2025-11-26 19:59:01+00:00
> This is not a hypothetical, nor an incremental difference. People are drowning in garbage, and if they don’t use garbage generation themselves, they get pushed out

I think of special notice is that even Apple and Disney are doing this. Two companies who have traditionally been far more cautious and extremely protective of their image. When entities like these are caving, I think it's safe to say we're well into Bizaro land.

Disney is the best example here. Iger recently suggested Disney+ users could make short form personalized content using Disney characters. This is very surprising to hear from a company who is extremely protective of those characters and the image of those characters. We do not yet have control over these image and video generation such that we can absolutely prevent certain classes of generation from happening. If they go through with it I'll give it a week (a month tops) before someone is able to generate porn with it. But hey, maybe the hit in stock will not be greater than the rise from the hype. But maybe that's part of the problem. Though they also don't appear to be getting any of that hype money either...
by egl2020 | 2025-11-26 19:59:03+00:00
Three considerations that come into play in deciding about using RL: 1) how informative is the loss on each example, 2) can you see how to adjust the model based on the loss signal, and 3) how complex is the feature space?

For the house value problem, you can quantify how far the prediction is from the true value, there are lots of regression models with proven methods of adjusting the model parameters (e.g. gradient descent), and the feature space comprises mostly monotone, weakly interacting features like quality of neighborhood schools and square footage. It's a "traditional" problem and can be solved as well as possible by the traditional methods we know and love. RL is unnecessary, might require more data than you have, and might produce an inferior result.

In contrast, for a sequential decision problem like playing go, the binary won-lost signal doesn't tell us much about how well or poorly the game was played, it's not clear how to improve the strategy, and there are a large number of moves at each turn with no evident ranking. In this setting RL is a difficult but possible approach.
by charcircuit | 2025-11-26 19:59:12+00:00
>we'd be immediately in violation of the California Consumer Privacy Act (CCPA), California Privacy Rights Act (CPRA), Telephone Consumer Protection Act (TCPA), CAN-SPAM Act, Americans with Disabilities Act (ADA).

>How could a platform be that bad?

People care about technology solving their problems, not that it is 100% legal.
by swat535 | 2025-11-26 19:59:24+00:00
> That happened because technology stopped being fun.

Exactly and I'm sure it was our naivete to think otherwise. As software became more common, it grew, regulations came in, corporate greed took over and "normies" started to use.

As a result, now everything is filled in subscriptions, ads, cookie banners and junk.

Let's also not kid ourselves but an entire generation of "bootcamp" devs joined the industry in the quest of making money. This group never shared any particular interest in technology, software or hardware.
by jjk166 | 2025-11-26 19:59:38+00:00
This is not an example of nor even an attempt at long horizon thinking. Voyager wasn't built with the intention that it would last for decades. It was a rush job to take advantage of a very rare planetary alignment and it's primary mission was completed 12 years after it started.

It is a testament to the ingenuity of the engineers who have worked and are still working on the project that they've managed to keep it to some degree functioning for so much longer than it was intended to last.
by keeda | 2025-11-26 20:00:14+00:00
Hah so, I have a couple of old Mac Minis in my homelab that I use very occassionally but would like to access over the Internet (say, via Tailscale etc.) Ideally they'd be sleeping most of the time to conserve power, and only be kicked awake when needed, e.g. by a Wake-on-Lan packet.

Unfortunately I would need another device active at all times to listen for commands and send that packet on demand. I was toying with the idea of using a Raspberry Pi connected to the router to perform that specific function, but I never got around to it.

Funny to see that idea scaled up to a server rack!
by DaveZale | 2025-11-26 20:00:14+00:00
9/10 on the bullshit meter. okay.... Okay! I've done my share of algorithmic fitting of far simpler lab spectral data to be convinced that "trying to hard to find something" can result in convenient delusions. Still, it's worth studying. It's still not 10/10 and enough discoveries are purely accidental, so why not increase the odds of an accident. Or, in a Zen-like approach, "doing not-knowing"