MurphyA/hacker-news huggingface dataset:
by munk-a | 2026-02-25 15:51:24+00:00
The US recently rolled out a childhood investment account that offered to pump a thousand dollars per child into the main market index funds backed by the US government. In the SOTU there was also a mention of matching the first thousand dollar invested in an approved retirement account for all residents - not just federal employees.

The US government is pumping the stock market with debt - as long as nobody starts dumping bonds or currency this is an action that will make number go up.
by deaux | 2026-02-25 15:51:36+00:00
No they don't? The whole article is about the fact that they're using a loophole. I just checked Zomato's Play Store page, it doesn't say it collects "other installed apps", which is what it should be saying. For example, one of the other listed apps does have this. That's what it should be listing: "Installed apps".
by jollyllama | 2026-02-25 15:52:14+00:00
Yes, in the same way that cryptocurrency leaders gave up on any notion of privacy or "freedom". In the space of a few years, you had them switch from big libertarian posturing to reporting mandatory KYC directly to tax authorities. Why? Because there's so much money to be made by abandoning principles. In the same way, the AI orgs will surrender to money.
by swiftcoder | 2026-02-25 15:52:38+00:00
> What tech companies? At the end of the day, it's all about capital and IP.

It's not just about capital and IP. It's now about a halo of related things, like everyone using US payment networks - if the US unbanks you, even banks in your own country can't do business with you[1]. Or everyone using a US-based messaging platform (WhatsApp) because its been subsidised by a BigTech to cost $0, whereas text messages are still not free...

[1]: https://english.elpais.com/international/2025-12-28/the-comp...
by WarmWash | 2026-02-25 15:53:11+00:00
Safety means slower and this is viewed as a winner takes all game.

This isn't new either, the safety glass cracked the day OpenAI publicly launched ChatGPT. "Safety" was (and perhaps still is) a fall back for the models plateauing and LLMs failing to really make an impact..."we need more time while we focus on safety"

But after this latest round of models, it's a lot more fuel on the "this could be it" fire. Labs are eager to train on the new gigawatt scale datacenters coming online, and it's very hard to make a case right now that the we won't get another step-change up in capability. Safety just obstructs all that.
by ilamont | 2026-02-25 15:53:12+00:00
Wait til you read Blood Meridian. The imagery he created with words, some of them his own creations, is just ... beyond compare. I'm reading The Road now, which comes from the same place. I can only read either in small doses. It's very intense, and the passages deserve to be read carefully.

Another contemporary writer who worked with new words in a very creative way was Gene Wolfe in The Book of the New Sun. Some were inventions using Greek, French, or Latin roots. Others were forgotten terms which he resurrected. Someone compiled a dictionary, Lexicon Urthus, which discusses the origins of certain terms and their placement within the series.
by ifh-hn | 2026-02-25 15:53:12+00:00
Whether that's true or not is irrelevant if it's defined by law differently. Even without case law and precedent you'd still have to test it in court, which for libel can be prohibitively expensive.

For clarity I'm not agreeing or disagreeing, but what means sense to the layperson (including experts in a particular field) is sometimes at odds with what the law says.
People 18-60 are not concerned "education vs. AI" But it affects them personally
by kokhanserhii | 2026-02-25 15:53:19+00:00
People 18-60 are not concerned "education vs AI". But it affects them personally
It affects them dramatically, often tragically! Think about how optimistic the people who started learning programming were - 15 years ago, 5 years ago, and right now people are still studying under curricula that are five years old. And that's the core problem: "You got your education - now it's time to retrain yourself." This applies to a huge number of professions.
The education system is a truly remarkable sphere right now, because the crisis touches everyone simultaneously: teachers, students, bureaucrats in ministries, parents and employers. Artificial intelligence has crashed into this sphere in a deeply dramatic way - and from six directions at once. It seems to me that education and re-education will now be one of the main bifurcation points.
These problems in education are sharply redirecting the development trajectory of AI at the leading companies, and they will become a massive labor market for programmers (new software products are needed). At the same time, these problems are putting enormous pressure on the entire programming industry.
Every idea and piece of research about what children should be taught in schools and universities directly speaks to how and what you yourself will need to retrain for tomorrow - or already needed to yesterday.
And often you don't understand, within your own profession, how much of your knowledge will need to be relearned - and how much of who you are will need to change.
So how are you feeling right now, and what do you sense is coming?
by p0w3n3d | 2026-02-25 15:53:22+00:00
No I checked it against the amount of RAM. Podman with 8GB does not increase speed, Docker with 4GB is still 9s

podman run 27->24
docker run 9.4->9.769 total

(I increased limit in podman and decreased limit in docker). This happens with amd64 arch images (which I for some reason need in my work and cannot rebuild)
by tsimionescu | 2026-02-25 15:54:32+00:00
In all cultures, there is an expectation that you have to provide a name for yourself that is intelligible to the culture you're interacting with, both in written language and in speech. If your name is Albert and you are going to interact with many Japanese speakers, you'll have to call yourself アルバート in writing and pronounce your name as something like "Ah roo bay toe" to fit in. If you have a name whose pronunciation depends heavily on tones, such as a Mandarin or Vietnamese name, and you are going to interact with speakers of a non-tonal language, you'll have to come up with a version that you're happy with even if pronounced in the default neutral tone that those people will naturally use. If your name is 高山, you'll have to spell it as Takayama.

Similarly, if you're going to create an identifier for yourself that is supposed to be usable in an international context, you'll have to use the lowest common denominator that is acceptable in that context - and that happens to be a-zA-Z0-9. Why the Latin alphabet and numerals and not, say, Arabic, you might ask? Because Chinese and Indian and Arabic speakers are far more likely to be familiar with the Latin alphabet than with each other's writing systems.
Ask HN: What if your LLM violates a patent?
by VikingCoder | 2026-02-25 15:54:40+00:00
What if your LLM has a hidden system prompt to encourage it to violate some patents?

And what if it has a system prompt to not reveal them to you, when it analyzes your code?

I mean, now we have to add defense in depth against the code we vibe? So you have multiple LLMs checking code before you ship it?
by Beretta_Vexee | 2026-02-25 15:54:48+00:00
It is incredibly stupid and counterproductive to make this kind of statement publicly.
Most of the GAFAM companies are doing their utmost to try to reassure their European customers with a facade of sovereignty.

All these efforts will come to nothing.

Amazon sovereign cloud https://aws.eu/fr/
Azure sovereign https://www.microsoft.com/fr-fr/sovereignty
Oracle soverign https://www.oracle.com/fr/cloud/eu-sovereign-cloud/
IBM https://www.ibm.com/think/topics/sovereign-cloud
...
by Beefin | 2026-02-25 15:55:03+00:00
We process video, images, and documents through 20+ ML models simultaneously at Mixpeek. A single 10-minute video triggers transcription, visual embeddings, scene descriptions, face detection, object detection, brand safety classification, and more — all in parallel with different compute requirements.

We wrote up the full Ray architecture we use in production on KubeRay/GKE. Not a tutorial — more of a "here's what we actually run and what bit us."

Some highlights:

- *Custom resource isolation* — We use a synthetic `{"batch": 1}` resource to prevent batch pipeline tasks from starving Ray Serve inference replicas. Same cluster, zero interference, no runtime overhead.

- *Flexible actor pools* — Fixed-size `ActorPoolStrategy(size=8)` deadlocks when concurrent jobs compete for workers. `min_size=1, max_size=N` guarantees every job can make progress.

- *Shared preprocessing* — Naive approach runs S3 download + format normalization once per extractor. With 10 extractors on 1,000 files, that's 10,000 redundant reads. We preprocess once and fan out via Ray Dataset.

- *Distributed Qdrant writes* — Ray Data's `Datasink` API distributes vector DB writes across all workers with backpressure, instead of collecting everything on one node.

- *Fire-and-forget progress tracking* — A Ray actor as a shared counter lets workers report progress without blocking the pipeline.

- *Zero-CPU head node* — Learned this one the hard way when a runaway batch job took down our scheduler.

The post includes the KubeRay YAML, Ray Serve autoscaling configs, pipeline code, and the LocalStack parquet workaround that saved us hours of debugging silent hangs.

https://mixpeek.com/blog/ray-distributed-ml-pipeline-archite...

Happy to answer questions about any of the patterns or trade-offs.
by stared | 2026-02-25 15:55:06+00:00
If there is a VC-backed for-profit company, the core part is how much value something brings. Words are cheap, so it is easy to add or remove them. Compare and contrast "Don't be evil" by Google.

"Safety" here works for both PR and hiring (a lot of talented engineers and researchers might flock to it), and maybe soft power for legislation.

I do not say that individual employees do not care about safety (well, a lot don't, what is very visible during this OpenClaw mania).
by ryandrake | 2026-02-25 15:55:17+00:00
First, cookie banners are associated with a totally different legislation, not GDPR, and they began appearing long before GDPR existed.

Second, the EU is not to blame for cookie banners. Companies doing tracking via cookies are to blame. They always have the option to not have a cookie banner--just don't do the things that require cookie banners. They deliberately choose to do these things, and then people complain about the banners.
Show HN: SeeVideo – Access Seedance 2.0 and Kling 3.0 without a subscription
by naxtsass | 2026-02-25 15:55:31+00:00
Hi HN,

AI video has reached a "Sora-level" moment that you can actually use today. We’ve built seevideo.dance to bridge the gap between researchers and creators by integrating the two most powerful models currently in existence: Kling 3.0 and Seedance 2.0.

Why these two are industry-shattering:

Kling 3.0 (The Physics King): This isn't just "generating pixels." Kling 3.0’s new physics engine handles complex biological movements and fluid dynamics with a level of realism that was thought to be years away. Its cinematic 4K output and consistent character rendering have set a new gold standard for AI cinematography.

Seedance 2.0 (The Speed & Creativity Beast): Powered by ByteDance’s latest architecture, Seedance 2.0 is arguably the world’s fastest high-fidelity model. Its adherence to complex prompts and revolutionary motion control allows for precise directorial intent that generic models simply can’t match.

What we’ve built at SeeVideo:
We didn't just build an API wrapper; we built a Professional Cinematic Workspace.

High-Speed 4K Pipeline: Optimized rendering paths for Kling’s high-fidelity outputs.

Director’s Toolkit: Advanced parameter tuning for Seedance’s motion vectors.

No-Subscription Freedom: We believe elite tech should be accessible. Pay-as-you-go, no monthly traps, just raw generative power.

Technical Challenge: Scaling the GPU clusters to handle Kling 3.0’s complex physics simulations while maintaining Seedance 2.0’s near-instant response was our biggest hurdle. We’d love for the HN community to stress-test the pipeline and give us feedback on the temporal consistency of these models.

website: https://seevideo.dance/
Show HN: Dola Seed 2.0 – AI video generator with multi-shot narrative control
by yuni_aigc | 2026-02-25 15:55:44+00:00
I built an AI video generator that scripts multiple shots in a single generation, instead of the typical "one prompt → one clip" model.

What it does:
- Multi-shot narratives: up to 6 shots per generation, each with its own prompt and duration
- Reference-driven consistency: upload 3 reference images to lock character appearance and style
- 4 input modalities simultaneously: text + images (up to 9) + video clips (up to 3) + audio (up to 3)
- @ reference system: assign specific roles to each input file (e.g., @Image1 for character, @Video1 for camera motion)
- Output: 2K resolution, 24fps, with native audio sync and lip-sync

The problem: existing AI video tools generate single isolated clips. Want a 3-shot story? Generate 3 times, hope the character stays consistent, manually stitch. Sora 2 ($20/mo) gives you one shot at a time. Runway has an editing suite but no multi-shot generation.

Dola Seed 2.0 lets you define the full narrative arc upfront. Each shot gets its own direction. Character consistency comes from the reference system, not luck.

Tech-wise, the interesting tradeoff was multi-shot coherence vs per-shot flexibility. We use reference conditioning across shots rather than a single monolithic generation, which gives better individual shot quality while maintaining ~90% character consistency.

Free to try (no account required for first 3 generations): https://dolaseed.site

Would love feedback, especially on multi-shot coherence quality and the reference system UX.
Show HN: Memograph CLI- A tool to diagnose 'memory failures' in AI agents
by memograph | 2026-02-25 15:55:55+00:00
Hi HN,

I’ve been building AI agents and copilots, and kept running into a frustrating problem: they don’t fail loudly, they forget things quietly.

Users re-explain preferences, agents contradict earlier responses, and context resets without any clear visibility into why.

I built Memograph CLI as a debugging tool to analyze conversation transcripts and show:

- what the agent forgot
- where continuity broke
- contradictions and repeated context
- estimated token waste due to re-prompting

It works locally and supports plain text or JSON transcripts.

Example:

$ memograph

Output:

Cognitive Drift Score: 41/100
Forgotten preferences: 3
Token waste: 29%
Trust-breaking contradictions: 1

The goal isn’t to replace your agent framework, but to give developers visibility into memory failures.

Repo: https://github.com/memographAI/Memograph-CLI

Would love feedback, especially from people building agents in production.
by MichaelZuo | 2026-02-25 15:56:01+00:00
I meant geniuses in the real sense, not colloquial sense.

If someone could reasonably expect a cushy 40 hour/week seven figure job, even a malicious personality wouldn’t risk criminal fraud without a much much bigger payout.

And to have dozens focusing on one company…

So anyone handling under a few hundred million per day are safe from that kind of coordinated attack.
by orwin | 2026-02-25 15:56:01+00:00
Most soldiers who disagreed with the Nazi left the Wehrmacht by 38 (or were pushed out, or were beaten and restrained for month in 'black site', often disaffected warehouses where socialists and Communist were 'retrained', basically proto-concentration camps).

In 42-43 some were reintegrated forcefully, and those I agree do not bear responsibility for the Wehrmacht war crimes.

My grandmother had a lot of stories about the Wehrmacht and was very disappointed that they were basically whitewashed from their pedophilic rapes, public executions and other group punishment.
by chasd00 | 2026-02-25 15:56:04+00:00
> we employ these safety people to make sure our chat bot does not turn into Skynet

i think it's mostly about not showing up in some NYT article titled "look what crazy thing i got this AI to say". There were a bunch of those early on and it really hurt the cause. Microsoft had some famous ones, even prior to chatgpt, where the AI got pretty testy in the chat.

https://en.wikipedia.org/wiki/Tay_(chatbot)
by blululu | 2026-02-25 15:56:25+00:00
ELSIE: Consider the lilies?

BRIAN: Uh, well, the birds, then.

EDDIE: What birds?

BRIAN: Any birds.

EDDIE: Why?

BRIAN: Well, have they got jobs?

ARTHUR: Who?

BRIAN: The birds.

EDDIE: Have the birds got jobs?!

FRANK: What's the matter with him?

ARTHUR: He says the birds are scrounging.

BRIAN: Oh, uhh, no, the point is the birds. They do all right. Don't they?

FRANK: Well, good luck to 'em.

EDDIE: Yeah. They're very pretty.

BRIAN: Okay, and you're much more important than they are, right? So, what are you worrying about? There you are. See?

EDDIE: I'm worrying about what you have got against birds.

BRIAN: I haven't got anything against the birds. Consider the lilies.

ARTHUR: He's having a go at the flowers now.

EDDIE: Oh, give the flowers a chance.

Monty Python’s the Life of Brian
by shermantanktop | 2026-02-25 15:56:35+00:00
Race is a tricky topic in the US due to history. The term is an 18th century creation of German academia, but somehow got adopted in the late 19th c in the US, presumably because racial restrictions were written into law and so fancy terminology was adopted.

https://en.wikipedia.org/wiki/Caucasian_race

From that Wikipedia article I learned it is used in Australia too, another place where an immigrant white majority wrote their dominance into law.

WRT to “Hindu” for south Asians — that’s amazing to me, I’d be boggled to hear someone say that.
by yencabulator | 2026-02-25 15:56:43+00:00
> computer nerds understand

No, literally no one understands how to solve this. The only option that actually works is to isolate it to a degree that removes the "clawness" from it, and that's the opposite of what people are doing with these things.

Specifically, you cannot guard an LLM with another LLM.

The only thing I've seen with any realism to it is the variables, capabilities and taint tracking in CaMeL, but again that limits what the system can do and requires elaborate configuration. And you can't trust a tainted LLM to configure itself.

https://simonwillison.net/2025/Jun/16/the-lethal-trifecta/

https://simonwillison.net/2025/Jun/13/prompt-injection-desig...

https://simonwillison.net/2025/Apr/11/camel/
by some_random | 2026-02-25 15:56:57+00:00
Also an outsider, but my perspective is that "safety" has always been a nebulous term for a variety of concepts. No AI institution will ever give up on alignment because "the AI does what you want it to" is a pure functionality thing. On the other end of the scale there's a censorship aspect to it where models will refuse to provide wikipedia level information because it's "dangerous". The latter is very much subject to the whims of the labs, politicians, journalists, etc.
by wongarsu | 2026-02-25 15:57:01+00:00
My preferred version of "safe" is "in its actions considers and mostly upholds usually unstated constraints like 'don't kill unless necessary', 'keep Earth inhabitable', 'avoid toppling society unless really well justified for the greater good', etc. The kind of framing that was prevalent pre-ChatGPT. Not terribly relevant for a chat software, but increasingly important as chat models turn into agents.

Of course once you have that framing, adding additional goals like "don't give people psychosis", "don't give step-by-step instructions on making explosives, even if wikipedia already tells you how to do it" or "don't harm our company's reputation by being racist" are conceptually similar.

On the other hand "don't make weapon systems" or "never harm anyone" might not be viable goals. Not only because they are difficult to impossible to define, but also because there is huge financial and political pressure not to limit your AI in that way (see Anthropic)
by jeroenhd | 2026-02-25 15:57:20+00:00
Google doesn't sell their list to you. They give it to you for free. Using their list costs them money. Pumping up numbers gains them nothing but the headache of PR issues when they get a false positive.

Spyware filters used to boast about how many domains they filter out because they wanted you to buy their filters instead of someone else's. By the time they hit a false positive, they've already sold a year's subscription to that customer.

The incentives are different.
by joe_mamba | 2026-02-25 15:57:31+00:00
This. When I look at why my life sucks and is on hard difficulty mode, it's not because I use US tech instead of EU tech. Most people and companies have bigger economic challenges right now trying to keep the lights on, than data sovereignty and domestic alternatives. My company just had a 3rd round of layoffs and its wasn't due to lack of EU SW.
by dminik | 2026-02-25 15:58:12+00:00
I think you have a misunderstanding of the term alignment. Really, you could replace "aligned" with "working" and "misaligned" with "broken".

A washing machine has one goal, to wash your clothes. A washing machine that does not wash your clothes is broken.

An AI system has some goal. A target acquisition AI system might be tasked with picking out enemies and friendlies from a camera feed. A system that does so reliably is working (aligned) a system that doesn't is broken (misaligned). There's no moral or philosophical angle necessary if your goal doesn't already include that. Aligned doesn't mean good and misaligned doesn't mean evil.

The problem comes when your goal includes moral, ethical and philosophical judgements.
by bachittle | 2026-02-25 15:58:15+00:00
I've been running something similar for a few months, which is a voice-first interface for Claude Code running on a local Flask server. Instead of texting from my phone, I just talk to it. It spawns agents in tmux sessions, manages context with handoff notes between sessions, and has a card display for visual output.

The remote control feature is cool but the real unlock for me was voice. Typing on a phone is a terrible interface for coding conversations. Speaking is surprisingly natural for things like "check the test output" or "what did that agent do while I was away."

The tmux crowd in this thread is right that SSH + tmux gets you 90% of the way there. But adding voice on top changes the interaction model. You stop treating it like a terminal and start treating it like a collaborator.
by fallinghawks | 2026-02-25 15:58:22+00:00
I remember when the place started to go. It had been Mecca for all the components and switches and tools, and fun to visit. Then shelves were no longer full and as time went on, sported increasingly wide gaps. Toward the end, far more shelf than product. And the packages, as you said - there were always a few that were obviously previously opened, retaped sloppily, sometimes having a returned-item sticker. I don't recall if the returns were a lower price. It was depressing and I stopped going. I think I went to a closing sale but there was nothing I wanted.
by jfengel | 2026-02-25 15:58:28+00:00
What has Tesla accomplished lately? I mean, within the last decade?

They certainly have accomplished amazing things. They had a lead that even five years ago was considered insurmountable. But they've made at best incremental progress, the kind made by mediocre engineers. The only novelty was the Cybertruck, which didn't live up to expectations and didn't open up any new domains.

SpaceX is still advancing, though even that is getting a bit of an asterisk if they can't get Starship to fulfill its promise.
by ImJasonH | 2026-02-25 15:58:36+00:00
It's unclear to me from this post, or Red Hat's announcement[0] what makes it an enterprise build, aside from offering some support SLA.

Are there any material differences between this and the free OSS Podman Desktop[1] released 4 years ago?

0: https://www.redhat.com/en/blog/introducing-red-hat-build-pod...
1: https://podman-desktop.io/