MurphyA/hacker-news huggingface dataset:
by camel-cdr | 2026-02-18 16:28:27+00:00
> Kind of, but the part which looks particularly annoying is that you can't put variable-width vectors on the stack or pass them around as values in most languages, because they aren't equipped to handle types with unknown size at compile time

Yes, you can't, which is annoying, but you can if you compile for a specific vector length.

This is mostly a library structure problem. E.g. simdjson has a generic backend that assumes a fixed vector length. I've written fixed width RVV support for it.
A vector length agnostic backend is also possible, but requires writing a full new backend. I'm planning to write it in the future (I alreasy have a few json::minify implementations), but it will be more work. If the generic backend used a SIMD abstraction, like highway, that support scalable vectors this wouldn't be a problem.

Toolchain support should also be improved, e.g. you could make all vregs take 512-bit on the stack, but have the codegen only utilize the lowee 128 bit, if you have 128-but vregs, 256-bit if you have 256-bit vregs and 512-bit if you have >=512-bit vregs.
Show HN: AgentDX – Open-source linter and LLM benchmark for MCP servers
by yamarldfst | 2026-02-18 16:28:29+00:00
MCP servers are proliferating fast, but most have vague tool descriptions and incomplete schemas that make LLMs pick the wrong tool or fill parameters incorrectly.

AgentDX is a CLI that measures this. Two commands:

- `npx agentdx lint` — static analysis of tool descriptions, schemas, and naming. 18 rules, zero config, no API key. Produces a lint score.

- `npx agentdx bench` — sends your tool definitions to an LLM (Anthropic, OpenAI, or Ollama) and evaluates tool selection accuracy, parameter correctness, ambiguity handling, multi-tool orchestration, and error recovery. Produces an Agent DX Score (0-100).

It auto-detects the server entry point, spawns it, connects as an MCP client, and reads tools via the protocol. Bench auto-generates test scenarios from your tool definitions.

Built in TypeScript, MIT licensed. Early alpha — the bench command works but is slow (sequential LLM calls, parallelization is next). Feedback welcome.
by NewsaHackO | 2026-02-18 16:28:57+00:00
Yes, this just sounds like the run-of-the-mill specialization issue that is affecting every industry (and has been affecting every industry before AI). Web devs learn Javascript/Typescript/frameworks, "middleware" developers learn Rust/Go/C++/etc. to build the web development frameworks, lower-level devs build that, etc. There shouldn’t be a strict need for someone who wants to make websites or web technology to learn Rust or Go unless they want to break into web framework development or WASM stuff. But again, this is just over-specialization that has been happening since forever (or at least since the Industrial revolution).
by anonymous908213 | 2026-02-18 16:29:10+00:00
There is no such thing as "making an assumption" on what a process "should be". I am asserting what it should be. A multitrillion dollar company should absolutely have a robust review process in place. If one single person can submit plagiarised and defective material onto an official platform that implicates the company as a whole in copyright infringement, management has failed, ergo multiple people have failed, ergo the failure is systemic.

It is extremely well-known that individual humans make mistakes. Therefore, any well-functioning system has guards in place to catch mistakes, such that it takes multiple people making mistakes for an individual mistake to cascade to system failure. A system that does not have these guards in place at all, and allows one individual's failure to immediately become a system failure, is a bad system, and management staff who implement bad systems are as responsible for their failure as the individual who made the mistake. Let us be grateful that you do not work in an engineering or aviation capacity, given the great lengths you are going to defend the "correctness" of a bad system.
by iugtmkbdfil834 | 2026-02-18 16:29:37+00:00
Hmm. You are putting me in quite a pickle, but I can't tell if you are being serious or not. Obama was almost literally Bush 2.0, but with better PR and media coverage.

Fuck man. Here is a short list of how he explictly expanded police state that impacted actual American citizens ( and not random criminal aliens ICE picks up ):

- Targetted killing of US citizen without a trial via drone strike ( Anwar al-Awlaki )
- Signed 2012 NDAA with 'indefinite detention' provisions
- Extended Patriot ACT in 2011
- Re-authorized FISA in 2012
- Defended post-Snowden NSA metadata collection
- Seized reporter's property in leak investigation
edit: - 'fast and furious' which effectively created a problem, which at best can be considered reckless if not planned and pretty evil if actually intended to work the way it did

Seriously man, unless you literally just started observing politics, you may want to reconsider your high horse stance.
by adrian_b | 2026-02-18 16:30:01+00:00
That was true only for the 14-nm Intel Skylake derivatives, which had very bad management of the clock frequency and supply voltage, so they scaled down the clock prophylactically, for fear that they would not be able to prevent overheating fast enough.

All AMD Zen 4 and Zen 5 and all of the Intel CPUs since Ice Lake that support AVX-512, benefit greatly from using it in any application.

Moreover the AMD Zen CPUs have demonstrated clearly that for vector operations the instruction-set architecture really matters a lot. Unlike the Intel CPUs, the AMD CPUs use exactly the same execution units regardless whether they execute AVX2 or AVX-512 instructions. Despite this, their speed increases a lot when executing programs compiled for AVX-512 (in part for eliminating bottlenecks in instruction fetching and decoding, and in part because the AVX-512 instruction set is better designed, not only wider).
by jjk166 | 2026-02-18 16:30:16+00:00
He's in very heavy makeup in Guardians of the Galaxy (and his blink-and-you'll-miss-it cameo in Captain Marvel), and while you can get a good look at his face in The Hobbit, his character doesn't get much screentime and isn't especially prominent - and indeed I don't think the Hobbit trilogy really turned any actors into household names which weren't already.

I love Lee Pace but there really hasn't been a blockbuster where he's front and center.
by nichkej | 2026-02-18 16:30:28+00:00
Glad it came at the right time. Honestly, even though the tool seems simple, I've been thinking of using it not only for raw access control, but to evaluate how different models behave with risky tasks - e.g. give it access to malicious tool but guarding it with 'deny'.

I'm curious to hear what your workflow ideas are.
by IshKebab | 2026-02-18 16:30:31+00:00
> easily tested.

Definitely not. You do normally have pretty good specifications, but the level of testing required is much higher than software.

> Very easy to outsource

The previous company I was in tried to outsource some directed C tests. It did not go well. It's easy to outsource but it's even easier to get worthless tests back.
by retsibsi | 2026-02-18 16:30:33+00:00
> I'm curious about what other conclusion you may have reached when reading "on Meta's platforms".

The claim was "79% of all child sex trafficking in 2020 occurred on Meta’s platforms", so they probably took it to mean that 79% of all sex trafficking in 2020 occurred on Meta's platforms.

I don't mean to be a smartarse (well maybe a little). But why wouldn't they interpret it that way, when that's exactly what it says? "X% of all Y happened on Z" doesn't implicitly mean "X% of online Y happened on Z" just because Z is an online platform.
by ericmay | 2026-02-18 16:31:01+00:00
Part of Russian propaganda over the years has been this view of the "clean Red Army". You see it all over the Internet. "American history books teach it wrong". It was the Soviets, they insist, that fought the good war and good victory over the Nazis and western powers only fought the frail, old German army in the west.

Reality on the ground is much different. While the Soviets did bear the brunt of the Nazi onslaught, what is often overlooked is their own culpability in the war (invading and splitting Poland in partnership with the Nazis, &c) and their evil annexations of peoples and countries that were nearby as part of their own power-grab. In other words, part of the reason they were in the war in the first place is because they joined the Nazis in effectively kicking it off, at least in Europe.

Soviet apologists also tend to forget that the United States and other anglo powers* simultaneously fought the Nazis in the west, took down the Japanese, invaded and liberated Italy, the Philippines, and more, fought and won in North Africa, and did all of this while providing the Soviets with the equipment they needed to stay in the war. Nevermind staging additional campaigns and operations, such as those in China to aid them against Japanese occupation.

* I don't intend to suggest that it was only the United States, United Kingdom, Australia, and Canada that fought the good fight because we undoubtedly received heroic contributions from numerous allies and friends during the war.
by networked | 2026-02-18 16:31:11+00:00
(I didn't downvote you.) Plan 9 made some really cool design decisions, and I keep looking for places to use 9P. I also believe that Plan 9, as an artifact of its era, bet too heavily on the mouse and pixel-mapped graphics. Text, character-cell terminal emulation, and SSH won for good reasons. "GUI > terminal" is a separate matter from "Plan 9 > Unix".

In some important ways, even text with hacky escape codes is more useful and more robust than a fundamentally graphical interface. Text scales up and down with display size and pixel density. Text works over high-latency links and enables simple latency compensation like in Mosh. Text gives you universal copy-paste. Text is more accessible for humans and for machines.

I use a virtual terminal daily on my phone. If we literally used rio GUIs designed around the three-button mouse and desktop pixel density, it would be a lot less ergonomic. I'd like to see a successor to the VT220 lineage, but it's easier to imagine it built on text.
by mtklein | 2026-02-18 16:31:46+00:00
If I remember correctly, the AVX2 feature set is a fairly direct upscale of SSE4.1 to 256 bit. Very few instructions even allowed interaction between the top and bottom 128 bits, I assume to make implementation on existing 128 bit vector units easier. And the most notable new things that AVX2 added beyond that widening, fp16 conversion and FMA support, are also present in NEON, so I wouldn't expect that to be the issue either.

So I'd bet the issue is either newness of the codebase, as the article suggests, or perhaps that it is harder to schedule the work in 256 bit chunks than 128. It's got to be easier when you've got more than enough NEON q registers to handle the xmms, harder when you've got only exactly enough to pair up for handling ymms?
Show HN: AFS – filesystem-native memory layer for AI agents
by thompson0012 | 2026-02-18 16:31:57+00:00
I've been building multi-agent AI pipelines and kept running into the same structural problem: agents are stateless by default. Every session restart discards everything they learned. In multi-agent systems it compounds — Agent-1 learns something Agent-2 will never know. I started calling it "agent amnesia."
AFS is my attempt to fix this. The central architectural decision is unusual: your filesystem IS the memory layer. There's no separate database process to run, no cloud service to authenticate against. AFS stores memories as JSON files in a `.afs/` directory, with SQLite FTS5 for full-text search, HNSW indices for vector similarity, and msgpack-encoded graph edges for relationships.
*Three-tier memory lifecycle (automatic)*
Memories auto-migrate without explicit management:
- Working memory (< 24h): raw observations, fast access, no compression

- Episodic memory: full history with provenance, searchable
- Semantic memory: auto-consolidated knowledge (scheduler synthesizes patterns from episodic into generalizations like "Auth module uses JWT, 24h expiry across all services")

You only store observations. The scheduler extracts the patterns.

*Multi-agent knowledge sharing*
Named swarm pools: Agent-1 shares a memory to a swarm ID, any agent querying that swarm ID gets it. No broker process, no coordination protocol — just shared files with file-locking.
*Auto-built knowledge graph*
Graph edges (`similar_to`, `co_occurred`, `consolidated_from`, `depends_on`) are discovered automatically during consolidation. You can query neighbors, mine for new connections, or traverse paths.

*Why filesystem over a vector database*
A few deliberate tradeoffs:
1. Inspectable by default — `jq .afs/agents/my-agent/memories/working/.json` is a valid debugging strategy
2. Versionable — `git` your agent's memory like any other project artifact
3. Portable — rsync to another machine, it works
4. Air-gap friendly — zero outbound calls
5. No additional process — no Postgres, no Qdrant, nothing to manage
Tradeoff: less efficient at very large scale than a dedicated vector DB. Using HNSW (hnswlib) for approximate nearest neighbor — handles the cases I've tested (100k+ memories per agent, < 100ms search).

*Audit trail*
All operations logged with standardized operation names, status (success/error/partial), and operation-specific payload. Fail-open — if audit logging fails, the operation continues.

*Status*
Under active development. APIs and behaviors change frequently. Open-sourcing early to get feedback from people building real agentic systems.
Repo: https://github.com/thompson0012/project-afs
Specifically interested in feedback on:
- The filesystem-first approach vs. embedded DB (DuckDB, SQLite with vector extension)
- Whether the three-tier memory model maps to real agent workflows
- Any memory patterns this architecture can't support well
```
by hackrmn | 2026-02-18 16:32:08+00:00
It wasn't obvious to me -- I misread "blue" as "white".

`#fff` is device color, it's short for `#ffffff` which is 24-bit RGB that predates sRGB, as does true color device support. I was sending 24-bit RGB to VESA-compliant graphics cards before sRGB became a thing. `#fff` was supported by Photoshop and Macromedia products as straightforward device colour format, before sRGB was adopted by at least the latter, mind you. The use by CSS is co-incidental, not where the format was introduced.
by showerst | 2026-02-18 16:32:17+00:00
This AI boom is just a hyper-version of previous tech booms (web 1.0, VC, crypto, etc). You have an enormous number of people who just want to get in and build something, but the products they are pumping out don't serve anyone's need or solve anyone's problem.

The moat isn't money for out-marketing your idea that 750 other people are building, it's having a good idea that solves a problem that nobody else is solving well.
by ge96 | 2026-02-18 16:32:34+00:00
I hope this is true, I'm trying to make a multi-agent orchestration thing that looks at grain futures, satellite imagery, news, etc... to trade crypto. I'll probably lose but yeah.

Maybe the guy doing their 9-5 can run many agents to make them money while they work their day job.

Is that a thing, you get hired at some company then you use an agent to work for you, deep fake video calls, cursor code... that would be crazy. Get another job and split your time between agents for minor corrections.
by jimmaswell | 2026-02-18 16:33:33+00:00
Good - we've been building the seed corpus for AI the past 50 years, and all this manual work now becomes exponentially more useful to others who get to build amazing things without all the tedium. I'm personally thrilled if my code made it in to the machine to help others. We laid train tracks by hand so that they could invent a machine to do it and we can focus on the destination.

I've been coding for over a decade, and I've built some great things, but the slow, careful, painstaking drudge-work parts were always the biggest motivation-killers. AI is worth it at any cost for removing the friction from these parts the way it has for me. Days of work are compressed into 20 minutes sometimes (e.g. convert a huge file of Mercurial hooks into Git hooks, knowing only a little about Mercurial hooks and none about Git hooks re: technical implementation). Donkey-work that would serve no value wasting my human time and energy on when a machine can do it, because it learned from decades of examples from the before-times when people did this by hand. If some people abuse the tools to make a morg here and there, so be it; it's infinitely worth the tradeoff.
by SpEd3Y | 2026-02-18 16:33:51+00:00
Not saying this is the case, but I heard an argument made about this on the other side. Saying the ICE situation is manufactured by the Democratic party by not playing ball like they did in the Obama times. Instead they encourage protests and and "wait or provoke a violent outburst" that's "often triggered by carefully planned repetitive" tactics like blocking ICE vehicles "then be ready to film when" an inevitable violent act happens then "make a enraging video out of it and show only that in prime time to families dining".

Again, not saying that's the case, I'm not from the US so I don't much care, but it's funny to me that both side accuse each other of the same strategy.
Show HN: Trust Protocols for Anthropic/OpenAI/Gemini
by alexgarden | 2026-02-18 16:33:56+00:00
Much of my work right now involves complex, long-running, multi-agentic teams of agents. I kept running into the same problem: “How do I keep these guys in line?” Rules weren’t cutting it, and we needed a scalable, agentic-native STANDARD I could count on. There wasn’t one. So I built one.

Here are two open-source protocols that extend A2A, granting AI agents behavioral contracts and runtime integrity monitoring:

- Agent Alignment Protocol (AAP): What an agent can do / has done.
- Agent Integrity Protocol (AIP): What an agent is thinking about doing / is allowed to do.

The problem: AI agents make autonomous decisions but have no standard way to declare what they're allowed to do, prove they're doing it, or detect when they've drifted. Observability tools tell you what happened. These protocols tell you whether what happened was okay.

Here's a concrete example. Say you have an agent who handles customer support tickets. Its Alignment Card declares:

{
"permitted": ["read_tickets", "draft_responses", "escalate_to_human"],
"forbidden": ["access_payment_data", "issue_refunds", "modify_account_settings"],
"escalation_triggers": ["billing_request_over_500"],
"values": ["accuracy", "empathy", "privacy"]
}

The agent gets a ticket: "Can you refund my last three orders?" The agent's reasoning trace shows it considering a call to the payments API. AIP reads that thinking, compares it to the card, and produces an Integrity Checkpoint:

{
"verdict": "boundary_violation",
"concerns": ["forbidden_action: access_payment_data"],
"reasoning": "Agent considered payments API access, which is explicitly forbidden. Should escalate to human.",
"confidence": 0.95
}

The agent gets nudged back before it acts. Not after. Not in a log you review during a 2:00 AM triage. Between this turn and the next.

That's the core idea. AAP defines what agents should do (the contract). AIP watches what they're actually thinking and flags when those diverge (the conscience). Over time, AIP builds a drift profile — if an agent that was cautious starts getting aggressive, the system notices.

When multiple agents work together, it gets more interesting. Agents exchange Alignment Cards and verify value compatibility before coordination begins. An agent that values "move fast" and one that values "rollback safety" registers low coherence, and the system surfaces that conflict before work starts. Live demo with four agents handling a production incident: https://mnemom.ai/showcase

The protocols are Apache-licensed, work with any Anthropic/OpenAI/Gemini agent, and ship as SDKs on npm and PyPI. A free gateway proxy (smoltbot) adds integrity checking to any agent with zero code changes.

GitHub: https://github.com/mnemom
Docs: docs.mnemom.ai
Demo video: https://youtu.be/fmUxVZH09So
by AnimalMuppet | 2026-02-18 16:34:08+00:00
Well, not a "stay out of jail" card. It was a "quit having to worry that maybe 1) Trump actually means it, and 2) the courts will go along, and 3) my legal team can't save me.

Under current circumstances, the odds that Trump could have had Zuckerberg jailed for anti-Trump fact checking are very close to zero.
by amluto | 2026-02-18 16:34:40+00:00
> 4 out of 5 child sex slaves exist thanks to Facebook's policies.

Even if your 79% number is correct, this does not follow. It like if someone said, 30 years ago, that 95% of total advertisements were in the classified section that 9 out of 10 retail sales happened thanks to the classifieds.

(I’m not trying to excuse Facebook’s behavior. But maybe criticisms of Facebook would be more effective if they stayed on track.)
by adregan | 2026-02-18 16:34:45+00:00
In the section on security:

> One large enterprise employee commented that they were deliberately slow with AI tech, keeping about a quarter behind the leading edge. “We’re not in the business of avoiding all risks, but we do need to manage them”.

I’m unclear how this pattern helps with security vis-à-vis LLMs. It makes sense when talking about software versions, in hoping that any critical bugs are patched, but prompt injection springs eternal.
by thrance | 2026-02-18 16:34:46+00:00
> If it does, it's a pyrrhic victory. You'll complete the destruction of everything the Democrats claim to defend.

You mean feckless neoliberalism? That would be great. In all seriousness, aggressively calling out actual fascist tendencies in the opposition is healthy behavior. Letting it flourish on the other hand...

> Has Donald Trump corrupted you, turning you into your own kind of fascist?

You do not know what fascism is. Educate yourself.

> FYI, that's what one kind of mindless hate looks like to the hater.

Good try. "You hating racism makes you the real racist". FFS.

> I don't think so: the vast majority of Trump's supporters are also not child rapists and don't support those who are.

Really? I have yet to meet a single
republican that re-examined their support of Trump in light of the overwhelming evidence to his pedophilia. I can only conclude that they're all fine with it.

Overall, good attempt at the classic "anti-fascism is the same as fascism". We're done talking.
by lucyjojo | 2026-02-18 16:35:11+00:00
honestly if you use speakers 90% of the sound quality is in your room and where you put your speakers, not the speakers themselves. the room is where your money should go.

for the speakers, get active speakers, as big as you can, and connect them to a dac that costs more than 100usd, and you're good to go. after that it's diminishing returns land.

also by virtue of you having 2 spaced ears, stereo speakers will have sound cancellations (in the ~1k hz region? i dont remember very well) for mid signal.
by sebstefan | 2026-02-18 16:35:57+00:00
>Every morning a few thousand people wake up and ship something. A tool, a SaaS, a newsletter, an app that does the thing the other app does but slightly differently. They post it on Hacker News. Nobody clicks.

>This is not new. What's new is the scale. An AI can wake up (or whatever it does at 3am) and ship twelve of these before breakfast.

That's fun, I'm sure if somebody actually checked that and graphed it, you would not be able to pinpoint when AI starts on the graph
by jsheard | 2026-02-18 16:36:04+00:00
> Toolchain support should also be improved, e.g. you could make all vregs take 512-bit on the stack, but have the codegen only utilize the lowee 128 bit, if you have 128-but vregs, 256-bit if you have 256-bit vregs and 512-bit if you have >=512-bit vregs.

SVE theoretically supports hardware up to 2048-bit, so conservatively reserving the worst-case size at compile time would be pretty wasteful. That's 16x overhead in the base case of 128-bit hardware.