MurphyA/hacker-news huggingface dataset:
by machardmachard | 2026-02-20 12:37:07+00:00
DID NETFLIX REALLY BELIEVE THEY WOULD BEAT STREAMROOT ?

Post 897: Popcorn Time iR³

Streaming App on Pure Flux Foundation - ~250 Lines

From Post 878: iR³ Alpha pure flux foundation (~1700 lines)

From Post 880: Private marketplace via DHT + P2P

From Post 884: iR³Reputation app (~300 lines)

From Post 881: Circular economy fusion reactor

The realization: Popcorn Time isn’t a separate implementation - it’s an APPLICATION on iR³ foundation. Just ~250 lines.

Result: Netflix-like streaming + creator payments + reputation, all on pure flux

https://bitcoin-zero-down-2ea152.gitlab.io/gallery/gallery-i...
by Gareth321 | 2026-02-20 12:37:16+00:00
It's an edge but I think it's going to become hard to gate data as they do. Soon our AI assistants will see and hear everything we see and hear in real-time. All of that will be ingested somewhere. Google can't prevent us from recording the things we see and hear.

Perhaps the competitive moat of the future will be time critical access to data. Google likely gets new data faster than everyone else, and they could use this time arbitrage in products like news, finance, research, etc.
by Frieren | 2026-02-20 12:37:36+00:00
There was never any move to align the USA and Europe politically, it always has just been an economic and militarist alliance.

If currently there is still a lot of support for USA companies inside the EU is because individual politicians have stakes on them or are Epstein-level implicated in corruption and scandals.

Even that to let American corporations control European business is destroying the EUs working class and it should be stopped. I still see a future of economic cooperation with the USA in the same way that can exist with India, Mercousur, etc. Collaborating and trading can benefit everyone without need to importing the USAs billionaire driven economy.
by arolihas | 2026-02-20 12:38:22+00:00
They have money. It’s taken from the rest of us and given to them. The rules you follow in life will be based on the behavior of the bottom quintile, the taxes you pay are to support the bottom quintile, the greatest risks to your life and property will come from the bottom quintile, the dearth of comfortable public spaces is because you have to allow the bottom quintile to be there, our zoning laws are developed for fear of the bottom quintile.
by rounce | 2026-02-20 12:38:59+00:00
> for the new UI --- any word on that? (Just an annotated copy would be great)

I also am not a fan of the icon-only toolbars and so I always use this plugin: https://github.com/APEbbers/FreeCAD-Ribbon

IMO it's a big improvement (I have it configured to only show small sized icons with labels) but then again I know not everyone is a fan of this type of toolbar because of the amount of screen space it takes up.
by Applejinx | 2026-02-20 12:39:23+00:00
Here's the problem: nobody is ever the asshole to themselves in the heat of rationalization, and the guts of this thing being instructed in this way are human language, NOT reason.

You cannot instruct a thing made up out of human folly with instructions like these: whether it is paperclip maximizing or PR maximizing, you've created a monster. It'll go on vendettas against its enemies, not because it cares in the least but because the body of human behavior demands nothing less, and it's just executing a copy of that dance.

If it's in a sandbox, you get to watch. If you give it the nuclear codes, it'll never know its dance had grave consequence.
by tclancy | 2026-02-20 12:39:32+00:00
This is an interesting approach. I think, in a way, it mirrors what I do. Having contracted for much of my career, I’ve had to get up to speed on a number of codebases quickly. When I have a choice of how to do this, I find a recently closed issue and try to write a unit test for it. If nothing else, you learn where the tests live, assuming they exist, and how much of a safety net you have if you start hacking away at things. Once I know how to add tests and run them (which is a really good way to deal with the codebase setup problem mentioned in the article because a lot of onboarding docs only get you to the codebase running without all the plumbing you need), I feel like I can get by without a full understanding of the code as I can throw in a couple of tests to prove what I want to get to and then hope the tests or CI or hooks prevent me from doing A Bad Thing. Not perfect and it varies depending on on how well the project is built and maintained, but if I can break things easily, people are probably used to things breaking and then I have an avenue to my first meaningful contribution. Making things break less.
by akst | 2026-02-20 12:39:37+00:00
As someone who spent the last year messing around with web components, I think there’s some cool stuff there but I have a new level of appreciation for actual components APIs from actual frameworks.

It’s more a custom element API than a component API, I mean that line in the sand is pretty subjective, but I just can’t see this API being a part of any major web framework, I can see that with shadow dom, I can’t see that with the whole customElement.register and garbage you have to do in the constructor.

Also the goals of this API are just not aligned with the purpose of a framework/component system. I do encourage people to play around with them but it’s really annoying to hear how they’re being promoted they’re are a lot less exciting than the platform advocates are willing to admit but that doesn’t mean they are useless but we need up stop pretending they’re the future of web applications.

Frameworks are often designed with the goal of managing application complexity without being overwhelmed by the shortcomings of the platforms. Web Components have done little to reduce the need for such a thing.
by amabito | 2026-02-20 12:39:45+00:00
One thing I find fascinating about epoll/kqueue is how much modern async frameworks abstract away the underlying readiness model.

A lot of people talk about “async performance” without realizing the core efficiency gain came from avoiding O(n) scans on idle FDs.

Curious how many higher-level runtimes still leak edge-triggered vs level-triggered semantics in subtle ways.
by freakynit | 2026-02-20 12:40:16+00:00
Exactly. One easily relatable use-case is structured content extraction or/and conversion to markdown for web page data. I used to use groq for same (gpt-oss20b model), but even that used to feel slow when doing theis task at scale.

LLM's have opened-up natural language interface to machines. This chip makes it realtime. And that opens a lot of use-cases.
by XorNot | 2026-02-20 12:40:17+00:00
Because you said "that's obviously intentional" as though that's a thing that could be done.

My point was that tarriffs or other trade sanctions on Europe are hardly going to change the calculus or consumption of services by Europe - the most that could be done is accelerate the migration away, but European consumers wouldn't notice a thing by those mechanisms (because US digital services are an import - "kind of" - given actual corporate structures).
by leoedin | 2026-02-20 12:40:44+00:00
Even if this first generation is not useful, the learning and architecture decisions in this generation will be. You really can't think of any value to having a chip which can run LLMs at high speed and locally for 1/10 of the energy budget and (presumably) significantly lower cost than a GPU?

If you look at any development in computing, ASICs are the next step. It seems almost inevitable. Yes, it will always trail behind state of the art. But value will come quickly in a few generations.
by Orygin | 2026-02-20 12:40:47+00:00
Mechanical and Ergonomic keyboard prices suffer because they are niche and way lower volume. The switches are not that expensive if you use common ones, but if you want some special keycaps, prepare to fork some good money. Most of them are made in very low batches and most of the expense is in the molds you have to make.
Your $10 keyboard is probably so mass produced that literal millions have been manufactured. Versus custom-ish keyboard designs that are made for at most a thousand buyers.
by g947o | 2026-02-20 12:41:02+00:00
Yes. You can tell the author either doesn't have experience using web components in a non trivial page, or they are intentionally hiding the complexity. Realistically, you don't want to make pure web components. You want to use a framework to build it for you.

Put it another way, you can make a page out of web components without using a framework, but you are not going to convert a React page with that approach.
by ZLStas | 2026-02-20 12:41:18+00:00
Yes, I use Claude — both the chat and Claude Code. Projects are great for layering context, but my concern with storing full books is that they eat up a huge chunk of the context window. I'd rather spend that budget on actual project context — the codebase, architecture decisions, domain specifics. That's where the distilled skill files come in: you get the core principles from the book in a compact, actionable form without burning through your context on hundreds of pages of text. At least that's how I see it
by spicyusername | 2026-02-20 12:41:22+00:00
I have no problem with AI music, but it's absolutely crazy to let labels pretend they're real people.

It should be required to include the AI model as a featured artist. Or maybe it's labeled like DJs, where the prompter is the artist.

As an aside, I think you're going to see a real resurgence of live music that let real artists showcase their real skills.
Show HN: A Self-Paced Exercise to Build a CLI Coding Agent from Scratch
by primaprashant | 2026-02-20 12:42:49+00:00
I ran a hands-on workshop in Tokyo where ~50 engineers built a CLI coding agent from scratch in Python. I've converted it into a self-paced exercise.

GitHub Repo: https://github.com/primaprashant/alduin

We start from a skeleton repo with a basic input loop and no LLM. Over seven phases, we add the Anthropic API, implement tools (read file, edit file, bash), and build the core agent loop.

Each phase has hints and a reference commit if you get stuck.
by Soenke_Cramme | 2026-02-20 12:43:11+00:00
Hi HN,
I built AgentBouncr because I couldn't find a governance layer for AI agents that actually enforces rules at runtime, rather than just observing what happened after the fact.
The problem: AI agents call tools autonomously. Most frameworks (LangChain, CrewAI, Vercel AI SDK) focus on making agents capable — but none of them answer "what is this agent allowed to do?" with deterministic enforcement.
AgentBouncr sits between the agent and its tools. Every tool call goes through a policy check before execution. Every decision is logged in a tamper-evident audit trail (SHA-256 hash chain). If something goes wrong, a kill switch stops all agent actions in <100ms.
Core components:

Permission Layer — agents can only use tools their policy allows
Policy Engine — JSON-based rules with conditions, rate limits, approval workflows
Audit Trail — append-only, hash-chained, W3C Trace Context
Injection Detection — pattern-based, bilingual (EN/DE), configurable
Kill Switch — deterministic, works even when the LLM API is down

Tech: TypeScript, 1,264 tests (671 framework + 593 enterprise), SQLite default (zero config), PostgreSQL for production. Vendor-agnostic — works with any agent framework.
The core framework is Source-Available (Elastic License v2) — you can use it, modify it, embed it. The enterprise layer (dashboard, API server, compliance reports) is commercial.
I built this as a solo founder. The EU AI Act (enforcement starts August 2026) was the initial motivation, but the governance gap exists globally.

Site: https://agentbouncr.com
Code: https://github.com/agentbouncr/agentbouncr
npm: npm install @agentbouncr/core

Happy to answer any questions about the architecture, licensing decisions, or the EU AI Act angle.
by freakynit | 2026-02-20 12:43:44+00:00
A related argument I raised a few days back on HN:

What's the moat with with these giant data-centers that are being built with 100's of billions of dollars on nvidia chips?

If such chips can be built so easily, and offer this insane level of performance at 10x efficiency, then one thing is 100% sure: more such startups are coming... and with that, an entire new ecosystem.
by hunterpayne | 2026-02-20 12:44:55+00:00
Let me put your mind at ease, the version of US politics you think is happening is just a mirage. As in it doesn't exist. Real US politics doesn't take place in the media anymore. Its all just propaganda now. Trump is a terrible statesman, but he is nothing like what is described by the media nor anything you mentioned in any real way nor are current events in any way unique or different from how the US functions normally. Its just that now it seems to be OK to call an ICE facility holding people to be deported (something that exists in almost every country) is now called a concentration camp in the media (and even in this thread). But Obama, Clinton and Bush deported about the same number of people as Trump. So please believe me, as someone who actually lives in the US, you are just watching a scripted reality show from another universe, not actual life in the US.
by primaprashant | 2026-02-20 12:45:03+00:00
I ran this live in Tokyo with ~50 engineers. The biggest "aha" moment was Phase 4, when the agent loop closes and the LLM starts chaining tool calls autonomously. People go from "I'm building a chatbot" to "oh, this is an agent".

Also, there have been plenty of "build a coding agent in 200 lines" posts on HN in the past year, and they're great for seeing the final picture. I created this simple structured exercise so we start from an empty loop and build each piece ourself, phase by phase. So instead of just reading the implementation, I hope more people try the implementation themselves.

These are the 7 phases of implementation:

1. LLM in the loop: replace the canned response with an actual LLM call
2. Read file tool: implement the tool + pass its schema to the LLM + detect tool use in the response
3. Tool execution: execute the tool the LLM requested and display the result
4. Agent loop: the inner loop where tool results go back to the LLM until no more tool calls
5. Edit file tool: create and edit files
6. Bash tool: execute shell commands with user confirmation
7. Memory: use the agent to build the agent, add AGENTS.md support for persistent memory across sessions

Feedback and PRs welcome. Happy to answer any questions.
Show HN: Remote-OpenCode – Control your AI coding assistant from Discord
by remocode | 2026-02-20 12:45:20+00:00
Hi HN,

I built remote-opencode, a Discord bot that runs on your dev machine and lets you use your local OpenCode CLI from anywhere (phone/tablet/another laptop).

It streams output back into Discord threads, supports queuing follow-ups, and can spin up per-task git worktrees with a PR button.

Repo & Demo: https://github.com/RoundTable02/remote-opencode
by marcyb5st | 2026-02-20 12:45:22+00:00
Oracle debt holders are sweating profusely right now I imagine. How does OpenAI gets 300B$ to pay Oracle [1] when nVidia has to be convinced to shell out "just" 30B for actually purchasing nVidia hardware.

[1] https://www.ft.com/content/90aa74a5-b39d-4131-a138-367726cb1...
by mikebelanger | 2026-02-20 12:45:31+00:00
I lean towards vanilla javascript and webcomponents myself, and eschew large frameworks in favor of lighter, or in some cases, no framework at all.

That said, this and many other webcomponent articles mischaracterize usage cases of webcomponents:

1. Being "Framework-free"

Frameworks can mean anything from something massive like NextJS, all the way to something very lightweight like enhance.dev or something more UI-focused like shoelace. To suggest being completely free of any kind of framework might give some benefits, depending on what kind of framework you're free of. But there's still some main benefits of frameworks, such as enforcing consistent conventions and patterns across a codebase. To be fair, the article does mention frameworks have a place further down the article, and gets close to articulating one of the main benefits of frameworks:

"If you’re building something that will be maintained by developers who expect framework patterns, web components might create friction."

In a team, any pattern is better than no pattern. Frameworks are a great way of enforcing a pattern. An absence of a pattern with or without webcomponents will create friction, or just general spaghetti code.

2. Webcomponents and the shadow DOM go together

For whatever reason, most webcomponent tutorials start with rendering things in their shadow DOM, not the main DOM. While the idea of encapsulating styles sounds safer, it does mean parts of your page render after your main page, which can lead to DOM elements "flashing" unstyled content. To me, this janky UX negates any benefit of being able to encapsulate styles. Besides, if you're at a point where styles are leaking onto eachother, your project has other issues to solve. The Shadow DOM does have its use, but IMO it's overstated:

https://enhance.dev/blog/posts/2023-11-10-head-toward-the-li...
by aurareturn | 2026-02-20 12:45:49+00:00
We are both wrong.

First, it is likely one chip for llama 8B q3 with 1k context size. This could fit into around 3GB of SRAM which is about the theoretical maximum for TSMC N6 reticle limit.

Second, their plan is to etch larger models across multiple connected chips. It’s physically impossible to run bigger models otherwise since 3GB SRAM is about the max you can have on an 850mm2 chip.

followed by a frontier-class large language model running inference across a collection of HC cards by year-end under its HC2 architecture

https://mlq.ai/news/taalas-secures-169m-funding-to-develop-a...
by ben_w | 2026-02-20 12:45:51+00:00
The entire reason the paperclip optimiser example exists is to demonstrate that AI is both likely to muck around in general direction in unpredictable ways, and that this is bad.

Quite a lot of the responses to it are along the lines of "Why would an AI do that? Common sense says that's not what anyone would mean!", as if bug-free software is the only kind of software.

(Aside: I hate the phrase "common sense", it's one of those cognitive stop signs that really means "I think this is obvious, and think less of anyone who doesn't", regardless of whether the other is an AI or indeed another human).
by remocode | 2026-02-20 12:46:13+00:00
I mostly wanted a “send a task now, check results later” flow when I’m away from my desk. With Discord already on my phone, this gives me a lightweight remote control for my existing OpenCode setup:

Start a session from Discord, watch real-time progress in a thread, and keep iterating in the same place.
If I send more instructions while it’s busy, they queue up and run sequentially.
For longer changes, it can create an isolated git worktree/branch per task, and there’s a one-click “create PR” action when it’s ready.
There’s also a passthrough mode so you can just type normally in the thread (less painful on mobile).

Quick start is basically:

- npm install -g remote-opencode

- remote-opencode setup

- remote-opencode start

Safety note: this runs locally on your machine. If you’re using it in any shared Discord server, you’ll want to enable the allowlist so only specific Discord user IDs can control it.

Would love feedback on the UX (Discord as the “remote terminal”) and the safety defaults / guardrails.
by gchadwick | 2026-02-20 12:46:16+00:00
This is an interesting piece of hardware though when they go multi-chip for larger models the speed will no doubt suffer.

They'll also be severely limited on context length as it needs to sit in SRAM. Looks like the current one tops out at 6144 tokens which I presume is a whole chips worth. You'd also have to dedicate a chip to a whole user as there's likely only enough SRAM for one user's worth of context. I wonder how much time it takes them to swap users in/out? I wouldn't be surprised if this chip is severely underutilized (can't use it all when running decode as you have to run token by token with one users and then idle time as you swap users in/out).

Maybe a more realistic deployment would have chips for linear layers and chips for attention? You could batch users through the shared weight chips and then provision more or less attention chips as you want which would be per user (or shared amongst a small group 2-4 users).
by retsibsi | 2026-02-20 12:47:16+00:00
Phrases like "actual understanding", "true intelligence" etc. are not conducive to productive discussion unless you take the trouble to define what you mean by them (which ~nobody ever does). They're highly ambiguous and it's never clear what specific claims they do or don't imply when used by any given person.

But I think this specific claim is clearly wrong, if taken at face value:

> They just regurgitate text compressed in their memory

They're clearly capable of producing novel utterances, so they can't just be doing that. (Unless we're dealing with a very loose definition of "regurgitate", in which case it's probably best to use a different word if we want to understand each other.)
by kgeist | 2026-02-20 12:47:26+00:00
8b models are great at converting unstructured data to a structured format. Say, you want to transcribe all your customer calls and get a list of issues they discussed most often. Currently with the larger models it takes me hours.

A chatbot which tells you various fun facts is not the only use case for LLMs. They're language models first and foremost, so they're good at language processing tasks (where they don't "hallucinate" as much).

Their ability to memorize various facts (with some "hallucinations") is an interesting side effect which is now abused to make them into "AI agents" and what not but they're just general-purpose language processing machines at their core.
by TacticalCoder | 2026-02-20 12:47:58+00:00
> There has never been a leftist government in the US. You seem a bit lost.

I'll give you three examples of the dems sliding left.

Biden did make sure all the borders were wide open and american forklifts, operated by americans, have been used to facilitate the mass migration of millions and millions of non-US citizens into the US.

Under the same government there have been politicians passing laws so that there'd be tampons in men's restrooms.

And you now have a mayor in NYC explaining publicly, to americans on US soil, that it's time to "look at the life of the prophet Muhammad" (I encourage everyone to go and buy a quran and go read it to actually learn about the muhammad but this may make want you to switch from democrat to republican).

I understand that people who vote democrats don't want to be called leftists but I don't think anyone disputes that dems have been slanting towards the left more and more.

Democrats having no issues with a politician lecturing them as to how they should look at the life of the prophet of islam makes me think something serious is going on.

I'm not sure who is lost here.
by mhl47 | 2026-02-20 12:48:12+00:00
The fact that the outputs are probabilities is not important. What is important is how that output is computed.

You could imagine that it is possible to learn certain algorithms/ heuristics that "intelligence" is comprised of. No matter what you output. Training for optimal compression of tasks /taking actions -> could lead to intelligence being the best solution.

This is far from a formal argument but so is the stubborn reiteration off "it's just probabilities" or "it's just compression". Because this "just" thing is getting more an more capable of solving tasks that are surely not in the training data exactly like this.