skysight-inc/HackerNews huggingface dataset:
There are some benchmarks such as Fiction.LiveBench[0] that give an indication and the new Graphwalks approach looks super interesting.

But I'd love to see one specifically for "meaningful coding." Coding has specific properties that are important such as variable tracking (following coreference chains) described in RULER[1]. This paper also cautions against Single-Needle-In-The-Haystack tests which I think the OpenAI one might be. You really need at least Multi-NIAH for it to tell you anything meaningful, which is what they've done for the Gemini models.

I think something a bit more interpretable like `pass@1 rate for coding turns at 128k` would so much more useful than "we have 1m context" (with the acknowledgement that good-enough performance is often domain dependant)

[0] https://fiction.live/stories/Fiction-liveBench-Mar-25-2025/o...

[1] https://arxiv.org/pdf/2404.06654
Theory here is that 4.1-nano is competing with that tier, 4.1 with flash-thinking (although likely to do significantly worse), and o4-mini or o3-large will compete with 2.5 thinking
A company with $350B in annual Revenue, $200B in Gross Profit, $100B in Cash in the bank lays off a few hundred people making a few hundred thousand dollars a year each, the savings amount to rounding errors. It's hard to understand what these Tech companies are trying to accomplish with the never ending rolling layoffs other than to engender fear in the workforce. It's like all that Great Resignation and Quiet Quitting stuff a few years back broke the collective brains of the C-Suite and they decided they just cannot tolerate labor having any sort of bargaining power at all and needed to mete out punishment to put workers back in their place.
"We couldn't make something work, so nobody can make anything work" is also a claim you can make, yes.

It's rather unsound reasoning, but you certainly can.
https://fiction.live/stories/Fiction-liveBench-Mar-25-2025/o...

IMO this is the best long context benchmark. Hopefully they will run it for the new models soon. Needle-in-a-haystack is useless at this point. Llama-4 had perfect needle in a haystack results but horrible real-world-performance.
Did they get an all-you-can-deport deal on that 6 million paid to Bukele? Why are they so obsessed with using that prison? Did I get trapped in a dystopian story or an Onion article, or is this real life?

Some talking points that the right would say if they weren't the ones doing this: "foreign countries are better at prison than we are now", we need to "bring back prison jobs for Americans", and "why is taxpayer money going to foreign countries?" I didn't think I would be rooting for American prison industry, but now they're more humane than the alternative.

See also: Bukele refusing to return a prisoner the US Supreme Court says should not have been deported. https://www.npr.org/2025/04/14/nx-s1-5364502/trump-bukele-el...
That's correct — The user obtains a short-lived SSH certificate (signed/issued by a CA).
I worked 80 hours a week in medical school, depending on the rotation. From that experience I can tell you, the majority of people that say they work 80 hours a week, don't even know what that looks like.
So use Rust, fine by me.

I might too some day, who knows.
Unless that has changed, anthropics (and gemini) caches are opt-in though if I recall, openai automatically chaches for you.
> why would they deprecate when it's the better model? too expensive?

Too expensive, but not for them - for their customers. The only reason they’d deprecated it is if it wasn’t seeing usage worth keeping it up and that probably stems from it being insanely more expensive and slower than everything else.
Thanks. I guess the integral promotion is related to byte-addressing. If you have bytes but can not directly do arithmetic on them, promoting them to word size seems natural.
I did it this way back in 2007 when I didn't even have a smartphone, you can develop an eye for it at the ground level as well. I camped 8 nights without paying once and never had an issue. The only time I had to resort to help was in suburban Cleveland area, it got dark and it was too built up to stealth camp anywhere, so I ended up stopping at the fire station and they let me camp in their yard. They are there all night anyway so they are usually fine with it.

The weirdest spot was in another suburban area, I camped behind a row of shrubs next to a cellphone tower installation haha. Wasn't the best setup but places like that usually don't get any traffic until business hours, so as long as you're in late and out early, you're fine.
Polaroid Death Machine
Watch out everyone. As long as they can get you on the plane before anyone realizes, then apparently nothing can be done. And SCOTUS is ok with that.
Peaceful protestors were already abducted in unmarked vans during Trump's first term: https://www.npr.org/2020/07/17/892277592/federal-officers-us...
AFAIK the truth is a little more complex: SSRIs do work for many people, but we don't really understand why and it's not as simple as 'more serotonin good.' They also don't work for everyone, and we don't understand why they don't work for some people either.
Typescript never generates classes or constructors that aren't present in source code. Whether or not constructors are present is completely independent from whether you're using code gen.
Human-Tech Institute has developed new system for the early detection of Autism
I really love the SSD1306 for its educational value. If you've bought a sensor kit for Arduino or ESP32 or Pico or whatever, chances are decent that you already have an SSD1306 lying around. There's so much example code for it. And the datasheet was pretty easy to grok IMO. My first exposure to it was in the pico-examples repo: https://github.com/raspberrypi/pico-examples/tree/master/i2c...

There's a few Rust libraries for it, too. And it's supported in Wokwi! https://wokwi.com/projects/425067706980448257
Who knew that giving power to unpaid volunteers who don‘t necessarily have the users or the companies‘ best interest in mind might turn out to be a bad business practice.
Internet Technology and Social Media, I would guess.
No, most of CECOT is prisoners arrested within El Salvador. Only a small section is previously US domiciled persons. The US only funded 300 of the available 40,000 slots. Most of them were from domestic gang round-ups, though I'm sure that process was highly imperfect.

So Mr. Garcia will be surrounded by a gigantic cohort of legitimate, full body 'MS-13' tattood, hard hitting gang members. If he wasn't in a gang before he likely is now, or getting the living shit beat out of him because he lacks gang protection.
Because chatgpt-4o-latest already has all of those improvements, the largest point of this release (IMO) is to offer developers a stable snapshot of something that compares to modern 4o latest. Altman said that they'd offer a stable snapshot of chatgpt 4o latest on the API, he perhaps did really mean GPT 4.1.
Check out feedback alignment. You provide feedback with a random static linear transformation of the loss to earlier layers, and they eventually align with the feedback matrix to enable learning.

It's certifiably insane that it works at all. And not even vaguely backprop, though if you really wanted to stretch the definition I guess you could say that the feedforward layers align to take advantage of a synthetic gradient in a way that approximates backprop.
I don't know why you would as it ignores half of all pregnant Americans, but if you exclude all groups except white women the age-standardized annual and aggregated rate of pregnancy-related mortality is still 27.6 deaths per 100,000 pregnancies.

Double that of Europe.

That is pathetic and unquestionably attributable in large part to our shitty and broken healthcare disaster.
> I consider [having a big benefit at 100% vs an 80/20 rule] a characteristic of type systems in general; a type system that you can rely on is vastly more useful than a type system you can almost rely on, and it doesn’t take much “almost” to greatly diminish the utility of a given type system.

This! This is why I don't particularly care for gradual typing in languages like Python. It's a lot of extra overhead but you still can't really rely on it for much. Typescript types are just barely over the hump in terms of being "always" enough reliable to really lean on it.
That's why I said "arguably", cause you're about to get argued with.

I won't, though. I tend to agree (under current idioms, I DO think it holds promise for software development when used properly.)
Show HN: Instantly view your team's SaaS usage across 2,500 tools
I needed a fast, simple way to uncover what SaaS tools my team was using (or not using), notify me of new tools that folks start to use, and map our stack without chasing people down. Not only were were wasting money on underused seats and tools but tracking all of it was too hard.

Most existing "SaaS management" tools felt like giant platforms that do many things, built for enterprise, and cost a ton. I just wanted a self-service that focused on usage to uncover all our tools. Fast. And nice to look at.

So I made Hapstack — a free browser extension that shows you:

- All the tools your team is using, by person

- Usage over time (so you can spot waste)

- Newly discovered tools as they show up

- A clean view of your whole SaaS stack, automatically

It’s built on Google Workspace. Takes 2-3 minutes to deploy and reveals up to 6 months of data immediately.

I'd love any feedback on the idea, setup experience, or use cases.
Definitely, but the idea is that its unique feature set is worth it.
Suspend functions appear as regular JVM methods with an extra Continuation parameter. Tools like runBlocking make them straightforward to call from Java.

My main point was that you can use Java code as is without modifications from Kotlin, and that if you wanted you could have Java code in your project and it will work just fine. Of course if you wanna start calling co-routines from the Java part of your project to the Kotlin part, hey that's up to you.
After quite some exploring around and struggles I made my peace with https://raindrop.io. Am I happy with that? Of course not. But that's the only hosted one which has extensions and apps for almost every browser and OS I use. I wish there a functional open source service (hosted) with wide range of platforms support that I could pay for and use.
What the best ads of the 2000s reveal about American culture
The problem is that while you can train a model with the hyperparameter of "context size" set to 1M, there's very little 1M data to train on. Most of your model's ability to follow long context comes from the fact that it's trained on lots of (stolen) books; in fact I believe OpenAI just outright said in court that they can't do long context without training on books.

Novels are usually measured in terms of words; and there's a rule of thumb that four tokens make up about three words. So that 200k token wall you're hitting is right when most authors stop writing. 150k is already considered long for a novel, and to train 1M properly, you'd need not only a 750k book, but many of them. Humans just don't write or read that much text at once.

To get around this, whoever is training these models would need to change their training strategy to either:

- Group books in a series together as a single, very long text to be trained on

- Train on multiple unrelated books at once in the same context window

- Amplify the gradients by the length of the text being trained on so that the fewer long texts that do exist have greater influence on the model weights as a whole.

I suspect they're doing #2, just to get some gradients onto the longer end of the context window, but that also is going to diminish long-context reasoning because there's no reason for the model to develop a connection between, say, token 32 and token 985,234.
look at all the graphs in the article
> then it wouldn't be correct

Indeed. And then what would be the point of the contract? Nobody is going to hold prisoners from another country indefinitely for free, even El Salvador, that just Does Not Compute (TM). I would much prefer to assume the DOJ is simply lying and that they are wrong, as to me that seems extremely likely.
I was hoping this article would be a little more concrete, but it seems that it largely is talking about the takeaways about functional programming in a philosophical, effort-in vs value-out kind of way. This is valuable, but for people unfamiliar with functional programming I'm not sure that it gives much context for understanding.

I agree with the high-level, though. I find that people (with respect to programming languages) focus far too much on the specific, nitpicky details (whether I use the `let` keyword, whether I have explicit type annotations or type inference). I find the global, project-level benefits to be far more tangible.
Some interesting stuff in the article, but it doesn't substantiate its headline conclusion.

Not anywhere close, IMO.

E.g., I'm sure Oracle doesn't want to lose $1B on a datacenter, but that's a bruise, not a catastrophic loss to them. I'm sure NVIDIA likes all the OpenAI revenue, but we're talking about how steeply the slope of their revenue line goes up. (They will inevitably face the problem where the line no longer shoots straight up, and a faltering OpenAI could make that happen sooner, but OpenAI itself isn't a life-or-death problem for them.)
RakuAST Syntax Highlighting
Meilisearch is really good for a corpus that rarely changes from my experience so far. If the documents frequently change and you have a need to have those changes available in search results fairly quickly it ends up with pending tasks for hours.

I don't have a good solution for this use-case other than maybe just the good old RDBMS. I'm open for suggestions or anyway to tweak Meilisearch for documents that gets updated every few seconds. We have about 7 million documents that's about 5kb each. What kind of instance do I need to handle this.
Why? Where does the money come from? What's the product?

If AGI destroys millions of jobs, who is paying for products?
Definitely some overlap there for sure but with different architecture — this is also an extension of the broader Infisical platform that a lot of companies use for secrets management.
I basically have switched to /active. IMO it's a stronger and more relevant set of articles, and tends not to be clogged with all the "Here's a thing, but with AI!" blogspam and endless number of "I ported this angular script to rust" turds that always seem to make it to the normal front page.
I will just add another +1 to say it's not common to work 60-80 hours per week in the US tech industry. It's not unheard of, and some companies (Amazon) are notorious for expecting that of their employees. But most of the time what you will see is that most people work 40ish hours (some weeks a bit more, some a bit less), and only a handful of colleagues with an unhealthy relationship to the job will work 50+ hours per week. Management doesn't generally expect people to do that, though of course bad managers do exist and can make your life miserable.

The only time I've ever been expected to put in those kinds of long hours was in case of an emergency. Stuff like, a natural disaster hit the company's primary data center so they needed to be all hands on deck to get services restored. But it's definitely not common day to day, and even in case of emergencies the company generally gives you a little something (extra time off, a bonus, whatever) to compensate you for the long hard hours you had to work.
My point is, it may be interesting if it’s faster than filing up. Now, is it likely? Not at the moment, as you correctly pointed out.

Can I guarantee it will never happen? No. Hence my comment. It was not about stating what will happen or not, I don’t feel this type of prediction has any reliability. Millions of people smarter than me get it wrong every day, especially the very long term ones are almost always wrong.
corpos are really good at creating a false narrative around shared missions/values/etc
I ran NoLiMa on Quasar Alpha (GPT-4.1's stealth mode): https://news.ycombinator.com/item?id=43640166#43640790

Updated results from the authors: https://github.com/adobe-research/NoLiMa

It's the best known performer on this benchmark, but still falls off quickly at even relatively modest context lengths (85% perf at 16K). (Cutting edge reasoning models like Gemini 2.5 Pro haven't been evaluated due to their cost and might outperform it.)
To join in the faux rigor?
ChaCha is in many ways better, but so far AES tends to win on most chips due to the existence of AES acceleration hardware. Without acceleration ChaCha is a lot faster, but with acceleration AES beats it quite a bit in both raw performance and power consumption.

Security-wise they are roughly equivalent in practice if they are used properly.
Things Queueing Theory can teach us about software development
I did 7,000 miles of touring in the US in 2006 without a cell phone, relying mostly on a paper Rand McNally road atlas and partially on Adventure Cycling's paper maps. I did most of the Western Express, and a good chunk of the Trans-Am between where they join and Missouri.

You are greatly overestimating the hazards associated with bike touring.

Folks are decent, and if you're on Adventure Cycling's routes, they are familiar with seeing cyclists. People offer help and stop to ask if you're ok. The route is well travelled by cars; if you passed out from heat exhaustion in the middle of the road, you'd be no more than an hour from being found, and in most places, a good deal less.

Water is pretty readily available, and most of the route passes through populated areas where you're a knock on a door away from a fillup if you're desperate. Mostly, I filled up with water at gas stations or where I camped in the evenings.

If you can ride a bike, fix a flat (you'll likely get a lot. I did), camp in a tent, and cook over a camp stove, you can do what the author of TFA did. Maybe a little/lot slower (75 miles a day is hauling ass fully loaded touring) but it's totally doable.

NB: Trek discontinued the 520 in 2023. Dozens of us are furious. The Surly Disc Trucker is well-recommended for touring, though I haven't been on one personally. Any bike that fits you with relaxed enough geometry, a long enough wheelbase, low enough gears, and the capacity to carry you and your gear will do.
Even AWS sells it. Pretty much a commodity.
Noted, TY
I learned about "cog in the machine" a few years after starting in tech and I became a contractor and have been ever since (20+ years). I get paid a daily rate and as long as there is work I keep earning, no sick/holiday pay, no reviews, bs corporate networking for promotions etc.

I have zero job security and could be let go any time, but that's built into my rate and I realised that's the case for normal employees anyway as the OP has discovered to his horror. The funny thing is I have outlived many a "permanent" employee in some places I've worked.
Thanks for the thoughtful reply!

One of the advantages of hardware kill switches, shutters on cameras, and the like is social signaling: other people can see them, and can see them being used. If I put my mass-manufactured phone on the table, and you can see the hardware sensors switch is "off", you can be quite sure I'm not recording you.

I think there's a chance for us to normalize this sort of thing, and make it table stakes for a lot of interactions. In a meeting room and there isn't a shutter on the camera? That's breaking the rules and we need to find one. And so on.

Relevant to this discussion, another thought I had is location- and QoS-aware enabling and disabling of the cell radios so I'm using wifi whenever I can, automatically. If I have a good internet connection other than through the cell radio, the cell radio is shut off.

Thank you again for your thoughtful reply and your work.
Right, I meant editor performance. None of the options should impact runtime performance anyway.
I was thinking the same thing. The impact _why left on ruby is one of the things that make it such a unique language with interesting and weird projects like this. I love it.
I worked at a startup where I joined as the second employee before they raised any money and I basically got 0.5% of the company. They went on to raise over $100 million in VC.

I got $0 for my equity. Start ups have SO many ways to screw employees out of their equity.

The most basic is that you have options that you are not allowed to sell during equity rounds. If you accept them then you need to pay the strike price and they count as taxable income even though you got shares instead of money so you just lose a lot of money.

Say what you will about Elon, but at Space X employees are allowed to sell their shares for actual money at regular intervals. Very few start ups that succeed allow their employees to do that.

90% of startups that succeed just want to grind down their employees rather than pay them the equity they earned.
> Cursor agent mode puked all over itself using Gemini 2.5. It could summarize what changes would need to be made, but it was totally incapable of making the changes.

Gemini 2.5 is currently broken with the Cursor agent; it doesn't seem to be able to issue tool calls correctly. I've been using Gemini to write plans, which Claude then executes, and this seems to work well as a workaround. Still unfortunate that it's like this, though.
Microsoft Neural Language Processing Hyperscale Datacenter Enterprise Edition 4.1

A massive transformer-based language model requiring:

- 128 Xeon server-grade CPUs

- 25,000MB RAM minimum (40,000MB recommended)

- 80GB hard disk space for model weights

- Dedicated NVIDIA Quantum Accelerator Cards (minimum 8)

- Enterprise-grade cooling solution

- Dedicated 30-amp power circuit

- Windows NT Advanced Server with Parallel Processing Extensions

~

Features:

- Natural language understanding and generation

- Context window of 8,192 tokens

- Enterprise security compliance module

- Custom prompt engineering interface

- API gateway for third-party applications

*Includes 24/7 on-call Microsoft support team and requires dedicated server room with raised floor cooling
This certainly isn't new. I know someone who worked at Google who mentioned the company culture has been souring since the start of the pandemic. I suspect Google will have a slow death akin to Yahoo in the coming years.
There is a WARN[1] period before the employee is officially laid off, but their access to all the corporate resources are cut off immediately. From the employee perspective, they have lost everything the moment they are being told that they are laid off. It doesn't matter that they are still getting paid.

[1] https://edd.ca.gov/en/jobs_and_training/Layoff_Services_WARN...
I think it's just called the passing of time. Our bodies build up senescent cells. Our personalities do it as we move through being new adults in the world to old people shouting at clouds. You have something new and novel and empty and you add two pieces of knowledge/whatever and wow this is lively useful discussion. Over time you have 20,000 bits of knowledge/songs in the genre/etc and those two new bits aren't that exciting, get lost in the noise, get canceled by what came before.
I mean, can’t they just train on some huge codebases? There’s lots of 100KLOC codebases out there which would probably get close to 1M tokens.
> depending on how your codegen works and how you're using protos at runtime, this approach might actually be faster at runtime

If your codegen is introducing runtime overhead you should use a different codegen.

> type inference in VSCode seemed reasonably fast with the toy examples I was playing with

It usually is. It can become a problem in a real project that has a lot of stuff going on, though.