MurphyA/hacker-news huggingface dataset:
by Retric | 2025-12-02 22:01:07+00:00
A little help for millions likely ends up mattering for some of them. It’s a head start in that it removes a single minor issue, shows the value of compound interest in a more tangible way, or possibly gets them to retirement weeks/months earlier.

Obviously many people are happy to spend whatever, but with 25 million people you’ll see a wide range of personalities and life situations. Imagine an otherwise identical life without 600 dollars of credit card debt, that’s a worth quite a bit over time and will likely apply to some of these individuals. Perhaps a musical instrument or similar purchase will end up really helping someone kid, you never really know.
by camgunz | 2025-12-02 22:01:21+00:00
We're not disagreeing. Your best example is throwaway mocks: temporary slop, which these models are good at, but all the costs and externalities are hidden from you. They're not actually economical to use (even if you don't consider training etc as part of the cost, which is ridiculous as they're some of the costliest things humans have ever done).
by int_19h | 2025-12-02 22:01:22+00:00
> What exactly is the moral dilemma with AI? We are all reading this message on devices built off of far more ethically questionable operations.

The main difference is that for those devices, the people negatively affected by operations are far away in another country, and we're already conditioned to accept their exploitation as "that's just how the world works" or "they're better off that way". With AI, the people affected - those whose work was used to train, and those who lose jobs because of it - are much closer. For software engineers in particular, these are often colleagues and friends.
by defrost | 2025-12-02 22:01:32+00:00
Good question - I'm still running 10 daily, I'm busy today and only tangentially follow the community - but it is still an issue being tracked:

https://github.com/ChrisTitusTech/winutil/issues/2358

( it might be resolved via another number - worth checking by d/loading to 11 and checking the hotlink notes in the update tab ... )
by waffletower | 2025-12-02 22:01:46+00:00
If a student is given a task that a machine can do, and there is some intrinsic value for the student to perform this task manually and hermetically, this value ought to be explained to the student, and they can decide for themselves how to confront the challenge. I think LLMs pose an excellent challenge to educators -- if they are lazily asking for regurgitation from students they are likely to receive machine-aided regurgitation in 2025.
by pscanf | 2025-12-02 22:01:56+00:00
Thanks for the detailed answer!

I think I do want to solve conflicts. My use case is for a personal database, which simplifies things a bit: sync is between devices of a single person, so it's unlikely for concurrent offline changes to occur.

What I have in mind is a setup like the one from this experiment: https://tonsky.me/blog/crdt-filesync/ . I don't know if it's at all possible in my use case though, or–in case it is possible–if it ends up being practical. As you said, the resulting user experience might be so strange that it's not something users want.

Anyway, thanks again for the info and good luck with DocNode. :)
by frellus | 2025-12-02 22:02:22+00:00
What kids really need is a mandatory personal finance class at the High School level. This would teach them how to handle money, debt, spending, budgeting and general financial health.

Nothing would help the next generation more, even above giving them seed investment money, than helping them avoid the pitfalls which are just waiting for them around every corner.

My daughter took an elective for this in HS, and every day would come home and say how much she was learning and how empowered she felt about money afterwards.
by vessenes | 2025-12-02 22:02:51+00:00
The moment you knew they were serious was when they pulled Jeff Dean in and paired him with Demis. That was, I imagine, a very expensive move to make internally, (rumors are Dean had wanted to retire / move on), and Demis had nearly unilateral control of his corner of the AI universe at Google for roughly a decade. We're seeing the results of that move right now.
by andersmurphy | 2025-12-02 22:03:00+00:00
I'd argue the opposite most applications are fine with an hour of downtime a month and arguably much more downtime then that. The recent AWS and Cloudflare outages have proven that.

You can achieve zero downtime with Sqlite if you really need to.

TPS is not a synthetic metric when you cap out at 100 TPS because of Amdahl's law and your users having a power distribution.
by jhatemyjob | 2025-12-02 22:03:36+00:00
Maybe we crossed the Rubicon and there's too much opportunity cost to learn how to implement the fundamental DS&A. Instead of memorizing the ~10 lines of code for binary search, memorize the words "binary search". Thanks to the C compiler, we don't have to remember to push our registers and then jump to the subroutine. I think LLMs provide similar benefits. It frees your headspace for other stuff.

The analogy isn't perfect since a compiler will error if it can't create valid output. LLMs hallucinate. But still. Time is limited. I don't think it's a good idea to spend your formative years learning how to manage registers.
by addaon | 2025-12-02 22:03:37+00:00
A relevant part that changed my view of charge pumps is the LTC7820 [0]. This is an inductorless charge pump that can be used as a an unregulated voltage doubler or halver... at 500+ W and 98%+ efficiency. I used to think of charge pumps as designed for generating bias voltages where the actual power is quite small... but this shows that they scale quite well. (There's also the LTC7821 that combines the unreglated inductorless halver of the '7820 with a regulated, nominally-2:1 buck to give a regulated 48V -> 12V converter with some impressive efficiency numbers.)

[0] https://www.analog.com/media/en/technical-documentation/data...
by toss1 | 2025-12-02 22:03:44+00:00
Now this actually sounds like a good use-case for LLM/'AI'-enhanced browsers. Everyone has different triggers and YUK! levels and it would take an insane amount of time & effort to encode all that, and setup on each different person's client side, but an 'AI-browser' with 'smart filtering' (or whatever they'd call it) would likely be quick to setup for each user's (dis-)tastes and be quite flexible in recognizing the patterns and taking the desired action (hide, warn, summarize w/o the triggers, sanitize, etc.).

Maybe it already exists(?) but I've avoided 'AI-browsers', keeping my use in their apps/sites.
by shwaj | 2025-12-02 22:03:54+00:00
The bet, (I would have thought) obviously, is that AI will be a huge part of humanity’s future, and that Anthropic will be able to get a big piece of that pie.

This is (I would have thought) obviously different from selling dollars for $0.50, which is a plan with zero probability of profit.

Edit: perhaps the question was meant to be about how Bun fits in? But the context of this sub-thread has veered to achieving a $7 billion revenue.
by WorldMaker | 2025-12-02 22:04:29+00:00
It is an approach that has already seen some success in Python. Languages often have constructs that are reserved for future use or that "parse but don't validate". JS has a lot of reserved keywords (thanks to ES4 and ES5, especially) that "don't mean anything" today but could in the future and still parse even though they'll give a runtime error. Beyond that, almost every language has a syntax for comments. Comments don't mean anything to the parser/compiler either, but they mean a lot to the people writing the source files and they still need syntax to write them.
by rprend | 2025-12-02 22:04:32+00:00
“Port it to a different language” a language that’s more out of distribution? Bad devex. Store data as an unreadable binary file? Bad devex.

Stay in distribution and in the wave as much as possible.

Good devex is all you need. Claude code team iterates and ships fast, and these decisions make total sense when you realize that dev velocity is the point.
by observationist | 2025-12-02 22:04:47+00:00
People who work the most with these bots are going to be the researchers whose job it is to churn out this stuff, so they're going to become acclimated to the style, stop noticing the things that stick out, and they'll also be the most likely to accept an AI revision as "yes, that means what I originally wrote and looks good."

Those turns of phrase and the structure underneath the text become tell-tales for AI authorship. I see all sorts of politicians and pundits thinking they're getting away with AI writing, or ghost-writing at best, but it's not even really that hard to see the difference. Just like I can read a page and tell it's Brandon Sanderson, or Patrick Rothfuss, or Douglas Adams, or the "style" of those writers.

Hopefully the AI employees are being diligent about making sure their ideas remain intact. If their training processes start allowing unwanted transformations of source ideas as a side-effect, then the whole rewriting/editing pipeline use case becomes a lot more iffy.
by radiospiel | 2025-12-02 22:05:06+00:00
> how you might be able to get such a syntax to work in pure Ruby, but gave up because there is no built-in reflection API to get the parameter default values

what I have done successfully here https://github.com/radiospiel/simple-service/blob/master/lib... is to install a TracePoint which immediately throws, and then call the method. The tracepoint then receives the value of the default arguments.

Not pretty, and I wouldn't run this in production critical parts of a system, but it works.
by hedora | 2025-12-02 22:05:13+00:00
If it’s at 5-15ms of downtime already, you’re in the space where the “zero” downtime FS might actually cause more downtime. In addition to pauses while the snapshot is taken, you’d need to carefully measure things like performance degradation while the snapshot exists (incurring COW costs) and while it’s being GCed in the background.

Also, the last time I checked the Linux scheduling quanta was about 10ms, so it’s not clear backups are going to even be the maximum duration downtime while the system is healthy.
by throwup238 | 2025-12-02 22:05:35+00:00
That’s exactly the behavior I’m describing.

`sleepy_future = sleepy()` creates the state machine without running anything, `create_task` actually schedules it to run via a queue, `asyncio.sleep` suspends the main task so that the newly scheduled task can run, and `await sleepy_task` either yields the main task until sleepy_task can finish, or no-ops immediately if it has already finished without yielding the main task.

My original point is that last bit is a very common optimization in languages with async/await since if the future has already resolved, there’s no reason to suspend the current task and pay the switching overhead if the task isn’t blocked waiting for anything.
by TkTech | 2025-12-02 22:06:06+00:00
It's a tiny pittance of what would have been owed had they been taxed appropriately, and seems conveniently timed to bury the news of Dell (via Dell Federal Systems) funding ICE (it's completely erased it from the first page search results for "dell funds ice" in less than 24 hours).

This isn't badass, it's a disgrace. They've hoarded an incredible amount of wealth generated by others and returned a sliver of it. You've been so conditioned to accept this system that you're even grateful for the scraps.

If they gave $100 billion, they'd still have over $51 billion in the bank. That's roughly $7 million a day for every day he's been alive, or enough to feed every child in America for over a decade. Imagine the regional economic stimulus if instead of being hoarded for nearly half a century that money was paid out in salaries to those actually earning that money. _And_ they'd still have billions.
by ijidak | 2025-12-02 22:06:30+00:00
Isn't the NVIDIA-TSMC duopoly the problem here?

The cost of these data centers and ongoing inference is mostly the outrageous cost of GPUs, no?

I don't understand why the entire industry isn't looking to diversify the GPU constraint so that the hardware makers drop prices.

Why no industry initiative to break NVIDIA's strangehold and next TSMC's?

Or are GPUs a small line item in the outrageous spend companies like OpenAI are committing to?
by lordnacho | 2025-12-02 22:06:31+00:00
99% of us can't live like that.

The other place you will meet struggling artists is sports. Train several times a week, neglect your social life, your studies, just learn how to chase after a ball.

Only people who are crazy driven will actually do this. The ones who don't make it, they try to climb up from lower league clubs. They go on and on, carving out a career.

But most kids do not have a burning passion for anything. They are curious, they're smart, they want to explore the world. But they haven't found a calling. If they try to go through the eye of the needle, they find it's quite hard, because those paths are taken by guys with a mental lock on a certain career.

What to tell the guy? He's picked the subject that is the most useful for learning about the world. Go around and look at things. There's so much that a person who can code and can deal with statistics can apply himself do.
by camgunz | 2025-12-02 22:06:52+00:00
There's no serious company who would do anything equivalent to "hey Jr Dev make me a Counterstrike", so examples like these do way more harm than good, because they give the impression of superpowers but this is really just the best they can do.

They're not thinking or reasoning or understanding. It's just amazing autocomplete. Humans not being able to keep themselves from extrapolating or gold rushing doesn't change that.
by unyttigfjelltol | 2025-12-02 22:07:26+00:00
I don’t really understand the underlying US government program— specifically why in a time of alarm over deficits “we” are enacting new private giveaways of public funds. Cynically, I doubt the folks who enacted this care one whit about folks who will turn 18 in the year 2044, 19 years from now. They only care about pumping the stock market today and winning elections in 2026 by transforming the Federal government into something like a hedge fund with a “save the children” sticker on the front door.

As for the Dells— they really do seem to care about our children and their philanthropy is beautiful.
by littlestymaar | 2025-12-02 22:07:38+00:00
I'd be a little bit more nuanced:

I think there's something off with their plans right now: it's pretty clear at this point that they can't own the technological frontier, Google is just too close already and from a purely technological PoV they are much better suited to have the best tech in the medium term. (There's no moat and Google has way more data and compute available, and also tons of cash to burn without depending on external funding).

But ChatGPT is an insane brand and for most (free) customers I don't think model capabilities (aka “intelligence”) are that important. So if they stopped training frontier models right now and focus on driving their costs low by optimizing their inference compute budget while serving ads, they can make a lot of money from their user base.

But that would probably mean losing most of its paying customers over the long run (companies won't be buying mediocre token at a premium for long) and more importantly it would require abandoning the AGI bullshit narrative, which I'm not sure Altman is willing to do. (And even if he was, how to do that without collapsing from lack of liquidity due to investors feeling betrayed is an open question).
by spiralpolitik | 2025-12-02 22:07:45+00:00
There is no moat in the models. The moat is in the UX. The problem is that OpenAI is far away from where the user is and not going to get there anytime soon. Google meanwhile is exactly where the user is.

OpenAI IMHO is a dead company at this point. They are overvalued relative to the fundamentals and don't appear to have any way of getting the numbers to work in the timeframe that their investors will expect. They are throwing stuff against the wall in the hope something sticks.

They are almost certainly looking for a bag holder. This will either be the retail investor via an IPO or the Federal government via "we are too big to fail".
by raw_anon_1111 | 2025-12-02 22:07:51+00:00
Given a choice between being “locked in” to a major cloud provider and trusting your business to a randomish little company, you are never going to get a compliance department to go for the latter. “no one ever got fired for choosing AWS”.

This is the API - it’s basically the same for all supported languages

https://docs.aws.amazon.com/code-library/latest/ug/python_3_...

Real companies aren’t concerned about cost as much as working with other real companies, compliance, etc and are comparing cost or opportunities between doing a thing and not doing a thing.

One of my specialties is call centers. Every call deflected by using AI vs talking to a human agent can save from $5 - $15.

Even saving money by allowing your cheaper human agents to handle a problem where they are using AI in the background, can save money. $15 saved can buy a lot of inference.

And the lock in boogeyman is something only geeks care about. Migrations from one provider to another costs so much money at even a medium scale they are hardly ever worth it between the costs, distractions from doing value added work, and risks of regressions and downtime.
by tetha | 2025-12-02 22:07:58+00:00
She's a fairly young seemingly career politician heading a fairly new government initiative. This feels like a very negative read with that context.

Reading this like I'd read something from my CEO:

> No, they don't. This is just made up. Developers develop with open source software. They do not spend 2/3 of their time "adapting" it.

Many of our devs jam few-line functions into Spring Boot / JPA / Hibernate / Flask / FastAPI / Django /Some other framework, updating these frameworks, configuring these frameworks. We have a few admins poking configs at PostgreSQL or other OSS solutions. It's not that wrong to call it like that.

> This persons does not understand what python or curl are. They do not "go down". This is just someone not having a single clue what they are talking about.

If you don't build, fix and maintain the software on your own, US embargoes can take down any SaaS solution, and cut you off of binary distribution (I know a guy who couldn't install binaries on an IP that was flagged as russian), source distribution (people getting banned from GH), patches, ...

It does not go down in the traditional sense, but if you have no devs of something in the EU, you can easily get cut off of security updates and get exploited with known problems from a hostile side. If you have your own devs in there it's at least less clear who cuts of whom and who keeps what security problems around in the libraries for whose benefit.

All in all, this reads like a managers take on stuff, but then again, 20M is on the level of pennies at that scale and overall an orientation to OSS and open standards is a good thing imo.
by runako | 2025-12-02 22:08:10+00:00
FWIW the selling $1 for $0.2 is widely applied to any business that is selling goods below cost.

For example: free shipping at Amazon does not have resale value and is not obviously fungible, but everyone understands they are eating a cost that otherwise would be borne by their customers. The suggestion is that OpenAI is doing similar, though it is harder to tease out because their books are opaque.
by alephnerd | 2025-12-02 22:08:21+00:00
> For a long time people were able to make a living for themselves by studying hard (usually STEM) and end up with a career which payed off

Recessions like the GFC, the Dot Bomb, the early 90s, the Asian Financial Crisis, the early 80s, Stagflation, and others show otherwise.

The extended bull run that SWEs had from the early 2010s to 2022 was an outlier, and the whiplash being felt today is comparable to what law and finance grads faced in the 2010s, accounting majors in the 2000s, and Aerospace/MechE majors in the 1990s.
by doctorpangloss | 2025-12-02 22:08:23+00:00
what it means is that this paper shows probable causality and models a lot of interesting features. it is most definitely not flawed.

i think the tough thing is that 0.6 percentage points gain for the average student is quite small. it's actually less than you gain by studying for 1h for the SAT, which is probably about 0.9 percentage points, depending on how you interpret college board's research (it recommends 20h of studying). that is to say, if students studied one fucking hour for the FAST, they would probably get a bigger benefit on it than all the time they get back not looking at their phones throughout two years of school.

so whatever cell phone use (1) in school (2) causes, it causes a small effect on test scores.

you would have to pick some other objective criteria, for example mental health assessment, for maybe a larger effect, or seek a larger treatment, perhaps a complete ban of cell phones period, to observe a larger effect.
by tartoran | 2025-12-02 22:08:28+00:00
I'm starting with Claude at work but did have an okay experience with OpenAi so far. For clearly delimited tasks it does produce working code more often than not. I've seen some improvement on their side compared to say, last year. For something more complex and not clearly defined in advance, yes, it does produce plausible garbage and it goes off the rails a lot. I was migrating a project and asked ChatGPT to analyze the original code base and produce a migration plan. The result seemed good and encouraging because I didn't know much about that project at that time. But I ended up taking a different route and when I finished the migration (with bits of help from ChatGPT) I looked at the original migration plan out of curiosity since I had become more familiar with the project by now. And the migration plan was an absolutely useless and senseless hallucination.
by whytevuhuni | 2025-12-02 22:08:35+00:00
> Because they don't use async inside.

But they use I/O inside, and we arrive at this issue:

I'm writing async, and I need to call std::fs::read. I can't, because it blocks the thread; I could use spawn_blocking but that defeats the purpose of async. So instead I have to go look for a similar function but of the other color, probably from tokio.

In Zig, if you're writing sync, you call the standard library function for reading files. If you're writing async, you call the same library function for reading files. Then, the creator of the `io` object decides whether the whole thing will be sync or async.
by throwuxiytayq | 2025-12-02 22:08:38+00:00
If you find these pictures distressing, you might want to consider consciously and carefully exposing yourself to more of the same to build a minimal amount of tolerance. I’m pretty sure it’s literally impossible to go through life without experiencing (sometimes personally) medical conditions that are significantly more visually unpleasant. I’m not a huge fan of the meat-creature-universe we all rolled, but it literally is what it is.
by cobolcomesback | 2025-12-02 22:08:53+00:00
This is the Anthropic press release from last year saying they will use Trainium: https://www.anthropic.com/news/anthropic-amazon-trainium

This is the AWS press release from last month saying Anthropic is using 500k Trainium chips and will use 500k more: https://finance.yahoo.com/news/amazon-says-anthropic-will-us...

And this is the Anthropic press release from last month saying they will use more Google TPUs but also are continuing to use Trainium (see the last 2 paragraphs specifically): https://www.anthropic.com/news/expanding-our-use-of-google-c...