MurphyA/hacker-news huggingface dataset:
by asdefghyk | 2026-02-04 05:51:45+00:00
The patent
https://patents.google.com/patent/US5490216A/en

The MAC address was only one parameter (of many) that allowed the creation of a unique hardware id (apparently)

A wikipedia page specifically about the dispute with Microsoft
https://en.wikipedia.org/wiki/Uniloc_USA,_Inc._v._Microsoft_....

A AI summary reposted (sorry if this not allowed ?) below

Australian inventor Ric Richardson pioneered software activation in the early 1990s, developing a "try-before-you-buy" system (Demoware) using a unique machine fingerprint and key-code unlocking system, now used on billions of computers.
His 1992 patent (US5490216) resulted in a major legal victory against Microsoft, ending in a confidential settlement valued at over $530 million.

Key details of the Ric Richardson patent and dispute:
The Invention: Richardson created a method for software anti-piracy where, upon purchase, a user receives a code to unlock full functionality, addressing the need to try software before buying.
Uniloc Company: Richardson founded Uniloc to develop and market this copy-protection software.

The Microsoft Dispute: In 1993, Richardson demonstrated his technology to Microsoft, which subsequently developed a similar activation system for products like Office, Windows XP, and Windows Server.

Legal Battle: After eight years of litigation, a US court found Microsoft infringed on the patent (Number 5,490,216), resulting in a settlement estimated to be in the low 9 figures (after earlier awards of $388 million, then over $530 million).

Legacy: The technology is widely used globally, and Richardson continued to innovate in cybersecurity, developing new, secure operating system methods.
by belZaah | 2026-02-04 05:52:15+00:00
Depends on the problem. If the complexity of what you are solving is in the business logic or, generally low, you are absolutely right. Manually coding a signup flow #875 is not my idea of fun either. But if the complexity is in the implementation, it’s different. Doing complex cryptography, doing performance optimization or near-hardware stuff is just a different class of problems.
by raeroumeliotis | 2026-02-04 05:52:23+00:00
This event equips developers and cloud engineers with a practical understanding of trusted execution environments, confidential VMs, and hardware enclaves—along with real-world examples and a clear path to building secure, compliant applications using confidential computing.

In this playlist

How to Build Confidential Computing on an Open Source Stack - Roman Zhukov, Red Hat

Getting Started with Google Confidential VMs - Malini Bhandaru, Independent & Ronghua (Jerry) Yu, Intel

Three Confidential Computing Use Cases - Steve Van Lare, Anjuna Security

Data Sovereignty in the Age of Agentic AI - Giorgio Natili, Oracle

Trust Without Compromise: Enabling Verifiable DEXs with TEE Technology - Giovanni Mazzeo, Trillion
by autoexec | 2026-02-04 05:52:25+00:00
> A right to vote includes the right to not vote.

Then add an abstain option to the ballot while still requiring people to show up and select the box. While I do think voting should be mandatory, I'd say that we should make it substantially easier. More polling places, mail in voting, having a mandated paid day off to vote and having more than one day to vote in person would go a long way to making the requirement workable.
by vander_elst | 2026-02-04 05:52:28+00:00
I don't think you are wrong, I do want guardrails and personally try to ensure that there are those guardrails before driving. However, it seems that a lot of people cannot wait for them and just want to go out and drive, fast, even if everything points towards the fact that that's not a good idea. If someone really wants to touch the fire after everyone stated multiple times that they shouldn't do it, I guess it's ok to let them go fo it.
by kavalg | 2026-02-04 05:52:31+00:00
Perception changes with every next generation. For the last 8 years, I've been teaching at the Faculty of Mathematics and Informatics at our University. One of the courses that I lead is IoT, where students get to program on bare metal (embedded) systems. I noticed that newer (cloud) generations have a harder time accepting the constraints of embedded hardware and living with them.
by numpad0 | 2026-02-04 05:52:42+00:00
no, no, no, the key enabler to space datacenter is complete out-of-world computer 3D printers. You print entire 130nm, hell, even 130 micrometer GPUs and DDR2 VRAMs to go with, entirely on the Moon solely from Moon dusts, and shoot the complete satellites out into Earth LEO using maglev sleds. PUEs, opex, nothing matter because the Moon factory is self contained and don't interact with Earthian economy at all. The ssh key into the factory will be the source to free money to whoever holding it.

Is that possible in our lifetime? I'd be optimistic about that. Can SpaceX pull that off? Space what? ...
by ezulabs | 2026-02-04 05:53:52+00:00
Tried both, openai models are also good, but something with agent getting out of plan after iterating for me, initial plan says to use xyz library and it uses, later on something goes wrong and fallbacks to a hack or simpler solution despite I correct again and again. I feel like summary of summary for the context causing the issue. Do you use it as snapshot task handling or MVPs? How do you manage long sessions?
by fspoettel | 2026-02-04 05:53:56+00:00
Thanks for the pointer, not doubting that is true. My egress is unfortunately too large for it to make financial sense.

However, at the time I did plenty of trace routes to confirm that the Pro plans peering is at least better than the Free plan for the Telekom problem. Free plan would route traffic to NYC and back, while Pro plan traffic terminates in Frankfurt.
by rammy1234 | 2026-02-04 05:54:05+00:00
Great article. Moment I finished reading this article, I thought of my time in solving a UI menu problem with lot of items in it and algorithm I came up with to solve for different screen sizes. It took solid 2 hrs of walking and thinking. I still remember how I was excited when I had the feeling of cracking the problem. Deep thinking is something everyone has it within and it varies how fast you can think. But we all got it with right environment and time we all got it in us. But thats long time ago. Now I always off load some thinking to AI. it comes up with options and you just have to steer it. By time it is getting better. Just ask it you know. But I feel like it is good old days to think deep by yourself. Now I have a partner in AI to think along with me. Great article.
by fhd2 | 2026-02-04 05:55:22+00:00
I _think_ the idea is that the first one to hit self improving AGI will, in a short period of time, pull _so_ far ahead that competition will quickly die out, no longer having any chance to compete economically.

At the same time, it'd give the country controlling it so much economic, political and military power that it becomes impossible to challenge.

I find that all to be a bit of a stretch, but I think that's roughly what people talking about "the AI race" have in mind.
by NitpickLawyer | 2026-02-04 05:55:39+00:00
> You are confidently incorrect.

No, he's not. Dragon is using CotS, non rad-hardened CPUs. And it's rated to carry humans to space.

> AWST: So, NASA does not require SpaceX to use radiation-hardened computer systems on the Dragon?

John Muratore: No, as a matter of fact NASA doesn't require it on their own systems, either. I spent 30 years at NASA and in the Air Force doing this kind of work. My last job was chief engineer of the shuttle program at NASA, and before that as shuttle flight director. I managed flight programs and built the mission control center that we use there today.

On the space station, some areas are using rad-hardened parts and other parts use COTS parts. Most of the control of the space station occurs through laptop computers which are not radiation hardened.

> Q: So, these flight computers on Dragon – there are three on board, and that's for redundancy?

A: There are actually six computers. They operate in pairs, so there are three computer units, each of which have two computers checking on each other. The reason we have three is when operating in proximity of ISS, we have to always have two computer strings voting on something on critical actions. We have three so we can tolerate a failure and still have two voting on each other. And that has nothing to do with radiation, that has to do with ensuring that we're safe when we're flying our vehicle in the proximity of the space station.

I went into the lab earlier today, and we have 18 different processing units with computers in them. We have three main computers, but 18 units that have a computer of some kind, and all of them are triple computers – everything is three processors. So we have like 54 processors on the spacecraft. It's a highly distributed design and very fault-tolerant and very robust.

[1] - https://aviationweek.com/dragons-radiation-tolerant-design
by protocolture | 2026-02-04 05:56:00+00:00
Carriage services have long been exempt from liability for the services they carry, as long as they follow other laws like lawful intercept, so that criminals can be detected.

Sorry but I feel this needs to be said: DUHHHHHHHH!!!!!!!!!

Also I need you to understand that the person who creates the child porn is the ultimate villain, transferring it across a carriage service or unrelated OS is only a crime if they can detect and prevent it. In this case, Grok is being used as an automated, turnkey child porn creation system. The OS, following your logic, would only be at fault if Grok is so thoroughly bad it cannot be removed through other means and OS level functions were required to block it. Ditto, its very possible that Grok might find its way onto an internet filter, if the outcome of this investigation leads to its blacklisting but the US government continues to permit it to seed the planet with indecent images of young people. In which case a router might be taken as evidence against an ISP that failed to implement the ban.

Sorry again, but this is just so blindingly obvious: DERRRRRRRRRRRRRR!!!!!!!!!

I am doing my best to act in keeping with the requirements of this website, unfortunately you have just made some statements so patently ridiculous, that its a moral imperative that they be immediately and thoroughly be ridiculed. Ridicule, is the only possible response because there's no argument or supposition behind these statements, only a complete leaden lack of thought, foresight or understanding.

If you want to come up with something better than the worlds worst combination non sequitur/whataboutism, I will do my best to take it seriously. Until then, you should reflect on why you made such an overwhelmingly dense statement. Duh.
by autoexec | 2026-02-04 05:57:10+00:00
I think people not being able to vote because their right to vote has been taken from them, or their vote was made pointless through gerrymandering, or because of other acts of voter suppression does change elections. The ability for it to change the outcome of a race is why voter suppression happens.

People who don't bother to vote for any reason changes elections. It also makes it very hard to make claims about what the majority of Americans want, since so many didn't make their opinions known
by dboreham | 2026-02-04 05:59:00+00:00
I think you under appreciate him a bit here. No he's not a super genius. He's probably not even a good engineer. But he is a) a total a.hole and b) a tremendous bullshitter. There are circumstances in which you need such a person to succeed (see also Steve Jobs). He yelled at people for 10 years straight and he was crucial in facilitating capital to build these very capital intensive products. A regular smart person would absolutely not have succeeded, for these reasons.
by tavavex | 2026-02-04 05:59:25+00:00
Other people have already pointed out the differences between implementing a check for a specific banned print and a vague categorical ban. It would be like if printer manufacturers weren't just asked to prevent the printing of US dollars, but anything that looks like money, having an ability to detect if something is money-like based on look and feel alone, without relying on an existing database or hardcoded watermarks.

Your implication makes me think that you assume that this useful-yet-not-overreaching detection tech is possible. Do you have any ideas for how this would be implemented? Because in my mind, the only way to ensure compliance would be either a manual check (uplink to the manufacturer or relevant government authority, where an employee or a model trained on known gun models tries to estimate the probability of a print being part of a gun) or a deterministic algorithm that makes blanket bans on anything remotely gun-like (pipe-like parts, parts where any mechanical action is similar to anything that could be in a gun). These scenarios seem to be both a lot more annoying and a lot more invasive. There's no negative consequences for tuning detection to always err on the side of caution and flood the user with false-positive refusals to print. Both scenarios are obviously a lot more involved and complicated than a basic algorithm checking if you're trying to print an image of a US dollar. Therefore I don't see a reason why drawing this comparison is useful. The only thing these implementations have in common is that they're detecting something.
by bgballer | 2026-02-04 05:59:52+00:00
We just launched BALLGAME.COM.

It’s a free-to-play sports lottery built around live YES / NO predictions.

The idea is simple.

You make quick YES or NO calls on real sports moments.
If you’re right, you earn entries into a lottery.
Lottery draws are on-chain and payouts are in USDC.

There are no deposits.
No betting.
No odds.

Everyone gets free daily plays.

Skill determines how many entries you earn.
Chance determines who wins the draw.

We built this because existing options felt broken in different ways.

Sports betting requires money upfront and pushes risk.
Prediction markets feel technical and niche.
Traditional lotteries are passive and disconnected from skill.

This sits in between.

Interactive like predictions.
Accessible like a lottery.
Transparent by default.

Key differences from what’s out there:

• Free to play. Always.
• No wagering or odds shopping.
• Entries earned through correct predictions, not money.
• On-chain draws anyone can verify.
• Built for casual fans, not traders.

At launch we support NBA, MLB & NFL,
More sports are coming v soon!

This is early.
We’re testing assumptions in the open.
Genuinely interested in feedback, criticism, and edge cases we haven’t thought through.

Happy to answer questions.
by stevep98 | 2026-02-04 05:59:57+00:00
Surely, the question is: how big do the radiators have to be?

gemini says that the NVIDIA DGX H100 is 130kg and takes 11kW.

It says space-based radiators in the 100kW range are approx 15kg per kW. And space-based solar panels are approx 1kg per kW.

So let's says we're talking about 1 system that bundles 9 DGX H100's. That's 1.2T for the computing system, 1.5T for the radiator, 100kg for the solar panels, and let's say 2T for the propulsion, propellant, guidance, and all the other spacecraft stuff. That's a total of about 5T, and the radiator is just about 20% of the mass budget.

The power radiated is proportional to the 4th power of the temperature, so they would be incentivized to develop a heat exchanger with a high temperature working fluid.
by int_19h | 2026-02-04 06:00:47+00:00
> And when you're done that, can you build another one and sell it to me?

Yep, that's exactly what the fed undercover will say.

And sure, they can't catch everyone, but they don't have to. They just need to catch and visibly prosecute enough people to create a chilling effect. It's about making it harder, not making it impossible.

Whether the cost/benefit here justifies those gains is a different question.
by isr | 2026-02-04 06:01:00+00:00
Ah, so the daily LARGE protests, in Venezuela, against his kidnapping are not indicative of "the vast majority of Venezuela".

But the celebratory pics, which were claimed to be from Venezuela, but were actually from Miami and elsewhere (including, I kid you not, an attempt to pass off Argentine's celebrating a Copa America win) ... that is indicative of "the vast majority of Venezuela"?

If I were smarter, I might start to wonder why, if President Maduro was so unpopular, why would his abductors have to resort to fake footage - which was systematically outed & destroyed by independent journalists within 24 hours? I mean, surely, enough real footage should exist.

Probably better not to have inconvenient non-US-approved independent thoughts like that.
by _trampeltier | 2026-02-04 06:02:29+00:00
It is very different. It is YOUR 3d printer, no one else is involved. You might print a knife and kill somebody with it, you go to jail, not third party involved.

If you use a service like Grok, then you use somebody elses computer / things. X is the owner from computer that produced CP. So of course X is at least also a bit liable for producing CP.
by lambda | 2026-02-04 06:03:04+00:00
> I wrote this comment the same way. The LLM fixed 14 grammar mistakes that I think would distract readers more than any LLM-ish phrasing.

I don't think that assumption is correct. As you can see by the discussion we're having here, the LLM "fixed" text is actually quite distracting, while text written by a reasonably proficient non-native speaker is generally perfectly readable. It's only if your English is extremely poor to non-existant that it makes more sense to use machine translation or editing rather than writing it yourself.

One problem is that people are becoming quite sensitive to slop, where people just post completely unreviewed, AI generated text. It's quite frustrating, because it's asking readers to read something that no one has ever bothered to write, and it frequently crowds out discussion that people are more interested in. So everyone is kind of hyper-sensitive to signs of AI written text right now, which means when you start to see such signs, your brain moves over to trying to interpret whether it's AI generated rather than reading the text itself.
Show HN: Video2docs – Turn Screen Recordings into Step-by-Step Instructions
by angelina200 | 2026-02-04 06:03:23+00:00
We recently automated a task that used to take some manual hours and was pretty boring itself - documentation and user how-to instructions creation, since before the ability to use AI technology, this was pretty time-consuming thing to do. Now it takes around 15 minutes.

The workflow is simple: record your screen of a task, workflow or feature walkthrough (even without audio) -> get a step-by-step guide with titles, descriptions, and contextual screenshots out of it automatically, auto-translate, and edit the output if needed as in a regular doc before final export. How it works? by analyzing unique video frames via LLM and then combining that information into final docs.

This automates the process and makes documentation much less painful, because you can start with a solid base and refine if needed instead of a blank page. We built our own tool based on this workflow, and maybe will be useful for others, too.

It is free to try, and we are happy to hear any feedback! Thank you.
Show HN: Chitram – Open-source image hosting with automatic AI tagging
by araju | 2026-02-04 06:03:26+00:00
I wanted to learn distributed systems by building something real instead of just reading about them. So I built an image hosting service that automatically tags uploads using GPT-4o-mini vision.

What it does: Upload an image → Celery worker picks it up → sends to OpenAI Vision API → tags get saved to PostgreSQL. Takes about 10 seconds, costs ~$0.004/image.

Why I built it this way:

I kept running into the same architecture decisions at work (swapping providers, handling async tasks, testing background workers) but never had full context. Building end-to-end gave me that.

The hardest bug: my tests were passing but production failed. Turned out BackgroundTasks grab new database sessions, so the worker couldn't see test data. Took 45 minutes to figure out it was a code duplication issue between my app and worker initialization.

Stack: FastAPI, PostgreSQL, MinIO (S3-compatible), Celery, Redis, Docker

Try it: https://chitram.io

Source: https://github.com/abhi10/chitram

Blog series documenting the build: https://araju.dev/blog

I'm an AI Automation engineer looking for my next role. Happy to answer questions about the architecture or the debugging rabbit holes I fell into.
by KingMob | 2026-02-04 06:03:51+00:00
That actually confirms what the other commenter said.

Your assertion was "Every datacentre I know going up right now is spending 90% of their bullshit budget on battlig state and local governments" and you haven't demonstrated any expertise is building data centers.

You've given a very extraordinary claim about DC costs, with no evidence presented, nor expertise cited to sway our priors.
Show HN: A personal feed that turns videos/podcasts/blogs into Twitter-y threads
by The_Amp_Walrus | 2026-02-04 06:04:38+00:00
I originally built this site as a content aggregator that would pull in blogs and podcasts and YouTube videos that I was interested in. I found I wasn't really reading very many of them, and I tried generating summaries for each item, but also found that I wasn't reading the summaries very often. And so taking inspiration from Twitter, I decided to try and convert the text/audio/video into a Twitter style thread, which I tend to read. I find I read most threads now and have a higher rate of clicking through to actually read articles, etc.

The overall sort of architecture and way that this works is documented here.
https://github.com/MattSegal/feed-plan

I'm running Parakeet on my Mac Mini to transcribe the audio from videos and podcasts.
https://github.com/MattSegal/parakeet-server
by raaihank | 2026-02-04 06:04:56+00:00
Costbase is an LLM cost optimization proxy. We just shipped TOON (Token-Oriented Object Notation) compression.

TOON is an open format (not ours): https://github.com/toon-format/toon

It converts JSON like this:

{"id": "cust_001", "name": "Acme", "mrr": 15000}

Into:
id: cust_001
name: Acme
mrr: 15000

We integrated it into our gateway to automatically compress JSON in tool results, user messages, and tool call arguments before they hit the LLM.

Benchmarks on real payloads:

- CRM query (10 records): 48% tokens saved
- E-commerce orders (4 orders): 34% saved
- API metrics (8 endpoints): 43% saved

Sub-100μs latency overhead. LLMs parse it correctly in our testing (GPT-4o, Claude, etc).

Not a silver bullet — works best on arrays of objects with uniform schemas. Deeply nested or irregular JSON sees less benefit.

Curious what strategies others use for token compression. We considered CSV for tabular data but it doesn't handle nested structures.

https://www.costbase.ai
by JimsonYang | 2026-02-04 06:05:11+00:00
AI makes technical debt so much worse. Speaking from the frontend perspective- reducing technical debt is all about making changeable standardized code. However models change structure, variables names, or changing variables means I'm building a lot of frontend on a shaky foundation. I routinely spend hours a week just fixing weird frontend builds. And as I'm the frontend role, my cofounder doesn't understand design, so I often get messy code