MurphyA/hacker-news huggingface dataset:
by phyzix5761 | 2026-02-17 05:32:01+00:00
Interest rates are relatively high compared to what they were several years ago. When interest rates are low everyone and their dog gets hired because its cheap to do that. When interest rates are high companies need to be more selective and growth/risk taking decreases.

If we can somehow get inflation under control it will trigger lower interest rates and hiring will increase again. But the current, and possibly only, strategy is to stagnate wage growth and increase the number of people out of work so that the economy has less money circulating in order to reduce inflation.

I've lived through a few of these. Its definitely cyclical.
Show HN: CoolWulf AI – A personal AI assistant built in Go, optimized for macOS
by coolwulf | 2026-02-17 05:32:16+00:00
Hey HN,

I've been building CoolWulf AI (https://coolwulfai.com), a self-hosted personal AI assistant. After seeing OpenClaw blow up, I wanted to share what I've been working on — a different approach to the same problem.

*Why I built this:*

I tried OpenClaw and found the Node.js/TypeScript stack heavy for what's essentially a local agent. pnpm, Node 22+, React — lots of moving parts. I wanted something that's a single binary, zero runtime dependencies, and feels native on macOS. So I built it in Go.

*How it's different from OpenClaw:*

- *Single binary, no runtime needed.* Download, set your API key, run. No Node.js, no pnpm, no build step. One ~100 MB binary.
- *Built in Go.* Fast startup, low memory footprint, compiles to a native executable. No garbage collector pauses from a JS runtime sitting in the background.
- *macOS-native integrations.* Deep AppleScript-based control of Apple Notes, Reminders, Calendar, Terminal.app, and WeChat desktop. These aren't browser hacks — they use the native accessibility and scripting APIs.
- *WeChat support.* This was a big one for me. WeChat desktop on macOS is a native Cocoa/Qt app with a readable accessibility tree. CoolWulf can read messages, send messages, search contacts, and navigate chats — all via AX APIs and CGEvent. I haven't seen another AI agent do this.
- *Simpler setup.* Web-based first-time wizard. Configure your LLM provider, connect Gmail/Calendar via OAuth, enable messaging connectors — all from the browser. No terminal wizards, no YAML files.

*What it does:*

- 20+ LLM providers (OpenAI, Claude, Gemini, DeepSeek, Groq, Ollama, local models via vLLM/LM Studio)
- Messaging: WhatsApp, Teams, Telegram, Slack, WeChat
- Email: Gmail and Yahoo Mail with full OAuth
- Calendar: Google Calendar + Apple Calendar
- Browser automation: Chrome CDP + Playwright via MCP
- Task management: org-mode style with scheduled tasks, cron jobs, automatic execution
- Persistent memory: SQLite + vector embeddings for semantic search across conversations
- Background heartbeat: runs 24/7, monitors your systems, executes due tasks, sends alerts
- Web dashboard for chat, tasks, scheduled jobs, and settings

*Architecture choices:*

Go was the right call. The binary compiles in seconds, cross-compiles trivially, and the concurrency model (goroutines for heartbeat, browser sessions, connector polling) maps perfectly to an always-on agent. SQLite with vector extensions (sqlite-vec) gives us semantic memory without running a separate vector DB.

Try it: https://coolwulfai.com

Happy to answer questions about the Go implementation, WeChat automation, or the macOS accessibility approach.
by anon291 | 2026-02-17 05:32:26+00:00
I've seen this with several friends.

One of the issues with tech is that if you make $250k in a good year, you are taxed on that. Whereas if you're then unemployed the next year, you don't get anything back as if you had only made $120k. It should work that you can recuperate paid taxes if you're laid off so that those in volatile industries (which tech is) actually pay their average salary. The tax code is set upon the belief that income is consistent for individuals, when it is not today. This is just an example of things I've seen that seem unfair to me. It's crazy someone can go from making $600k and taxed to their teeth to making nothing for the next two years, and if they had instead made $200k per year, they would have ended up better off (not due to spending, just due to taxation).
by random3 | 2026-02-17 05:33:00+00:00
Thanks, both! Glad to get the explicit names for the things I'm "gesticulating" at. I haven't done any explicit reading on the topic, except for adjacent stuff like Analogia (Dyson), The coming wave (Suleyman) and saw talk by Terry Winograd that I thought was on point https://www.youtube.com/live/LcvYYXdXF8E.
I have and do want to read Superintelligence and will check out both Stiegler and Simondon.
by hellotomyrars | 2026-02-17 05:34:06+00:00
AI isn’t “from a different culture”. It doesn’t have culture. Any culture it does have is what it has sucked up from its training data and set in its weights.

There is no need to be “humane” to AI because it possess no humanity. It has no personhood at all. It can’t feel. You can’t be inhumane to something that is literally incapable of feeling.

A blade of grass has more humanity and is more deserving of respect than anything being referred to as AI does.

Aliens might not be received well but it’s going to depend a lot on how they show up.

AI is a “revolution” where the promise is that nobody will have to do meaningless work anymore ( I guess).

The only problem is right now basically everyone has to do work meaningful or “meaningless” because the dominant thinking requires it for human survival. Weird how most people aren’t happy for the thing that is pitched to take away the meager scraps they get under the current regime.
by al_borland | 2026-02-17 05:34:09+00:00
I’m sure there are some exceptional 5th graders doing amazing things. The number that will keep that same interest into adulthood is exceptionally low. Kids also need a chance to be kids. Expecting them to be heads down working on their career ambitions at 10 is dystopian.

It’s not about just getting hired. It’s about being effective once hired. I expect a senior to have preferences and opinions, informed by experience, on how things can and should run… while also being able to adapt to the local culture. We should be able to debate ideas in real time without having to run to the LLM to read the next reply. If that’s all someone is bringing to the table, just tell the team to use an LLM during brainstorming sessions.
by kretaceous | 2026-02-17 05:34:26+00:00
Re: the lcm_expand(summaryID) tool

> Because expansion can recover arbitrarily large volumes of earlier conversation, this tool is restricted to sub-agents spawned via the Task tool; the main agent cannot call it directly. This restriction prevents uncontrolled context growth in the primary interaction loop.

What if the lcm_expand is called for a summary that has 1000s of messages that immediately floods the sub-agent's own context window?

Does lcm_expand only unroll one "layer" of the DAG and unrolls more if needed by another subagent?
by verdverm | 2026-02-17 05:35:19+00:00
Why do I want a bespoke language generated by an Ai, as compared to JSX + tailwind which I see as basically the same "html/css/js" without context switching (all in the same file), and something the Ai have seen significant amounts of during training?

If I use something bespoke, then I have to do in-context learning, so am I really saving tokens in the long-run? (before we even get to more frequent failures / hallucinations that come with the bespoke)
by applestone | 2026-02-17 05:35:46+00:00
about 2600 links, found by this method

https://www.ibtimes.co.uk/doj-epstein-files-hidden-videos-un...

if they don't work, try putting a .mov at the end, lots are movs but I made the link .mp4 for main ease of use (also maybe try jpeg, .avi, .heic)
by vasco | 2026-02-17 05:36:07+00:00
That last bit is not really how it works. I've been in a small company that law enforcement would routinely reach out to for help with solving crimes because they thought we'd have relevant data.

99% of requests are wild goose chases based on nothing. Like literally dumb requests that are not only irrelevant, the request wouldn't even get past that cops boss, much less a judge. But a cop can just ask whatever they want regardless of merit or relevance and it's up to you to say yes or no.

In those years we received two requests with warrants that made more sense but when I see "company denied to help" I understand why. Most cases it's a random cop fishing for private info that has nothing to do with anything. And when it's true, just get a warrant then.

Otherwise you're more likely to be jeopardizing innocent people's data than actually helping anyone.
by xvxvx | 2026-02-17 05:36:12+00:00
There’s an ever-growing movement of physical media collectors online. They’re interesting to watch because they seem to buy pretty much anything. $80 for a 4K release of super-flop Tank Girl? Sure.

It seems more of an obsession than simply buying the films you like. And they’re pretty defensive about it. One collector spent decades building a massive collection, and almost as long railing against streaming and claiming his physical collection would outlast Netflix… that was until his home burned down in the California wildfires last year.
by TazeTSchnitzel | 2026-02-17 05:36:21+00:00
Another example of tiny details being used to catch sex offenders is this story about marks on people's hands: https://www.wired.com/story/sue-black-forensics-hand-marking... / https://archive.is/89vOJ

It turns out that, even if all you can see is the assailant's hands, that may be enough to identify them.
by seddonm1 | 2026-02-17 05:36:37+00:00
I am applying differential/property based testing to all the side effects of functions (mutations) and return values. The rust code coverage is also used to steer the LLM as it finds discrepancies in side effects.

It is written up in my link - please bear in mind it is really hard to find the right level to communicate this level of detail at - so I'm happy to answer questions.
by coolwulf | 2026-02-17 05:37:32+00:00
Hey HN,

I've been building CoolWulf AI (https://coolwulfai.com), a self-hosted personal AI assistant. After seeing OpenClaw blow up, I wanted to share what I've been working on — a different approach to the same problem.

*Why I built this:*

I tried OpenClaw and found the Node.js/TypeScript stack heavy for what's essentially a local agent. pnpm, Node 22+, React — lots of moving parts. I wanted something that's a single binary, zero runtime dependencies, and feels native on macOS. So I built it in Go.

*How it's different from OpenClaw:*

- *Single binary, no runtime needed.* Download, set your API key, run. No Node.js, no pnpm, no build step. One ~100 MB binary.
- *Built in Go.* Fast startup, low memory footprint, compiles to a native executable. No garbage collector pauses from a JS runtime sitting in the background.
- *macOS-native integrations.* Deep AppleScript-based control of Apple Notes, Reminders, Calendar, Terminal.app, and WeChat desktop. These aren't browser hacks — they use the native accessibility and scripting APIs.
- *WeChat support.* This was a big one for me. WeChat desktop on macOS is a native Cocoa/Qt app with a readable accessibility tree. CoolWulf can read messages, send messages, search contacts, and navigate chats — all via AX APIs and CGEvent. I haven't seen another AI agent do this.
- *Simpler setup.* Web-based first-time wizard. Configure your LLM provider, connect Gmail/Calendar via OAuth, enable messaging connectors — all from the browser. No terminal wizards, no YAML files.

*What it does:*

- 20+ LLM providers (OpenAI, Claude, Gemini, DeepSeek, Groq, Ollama, local models via vLLM/LM Studio)
- Messaging: WhatsApp, Teams, Telegram, Slack, WeChat
- Email: Gmail and Yahoo Mail with full OAuth
- Calendar: Google Calendar + Apple Calendar
- Browser automation: Chrome CDP + Playwright via MCP
- Task management: org-mode style with scheduled tasks, cron jobs, automatic execution
- Persistent memory: SQLite + vector embeddings for semantic search across conversations
- Background heartbeat: runs 24/7, monitors your systems, executes due tasks, sends alerts
- Web dashboard for chat, tasks, scheduled jobs, and settings

*Architecture choices:*

Go was the right call. The binary compiles in seconds, cross-compiles trivially, and the concurrency model (goroutines for heartbeat, browser sessions, connector polling) maps perfectly to an always-on agent. SQLite with vector extensions (sqlite-vec) gives us semantic memory without running a separate vector DB.

Try it: https://coolwulfai.com

Happy to answer questions about the Go implementation, WeChat automation, or the macOS accessibility approach.
by verdverm | 2026-02-17 05:38:06+00:00
You wouldn't really take an Ai image to the government for your id, would you? That sounds like a recipe for ending up in court.

I'm about to go get a new passport, I am planning to ask how they ensure images are not Ai generated, since the last time I went, they took the photo and didn't have me bring it in myself (what?!)
Smart-KNN: A production-focused, feature-weighted KNN optimized for CPU
by Jashwanth01 | 2026-02-17 05:38:08+00:00
Hi HN,

I’ve been working on SmartKNN, a nearest-neighbor system designed specifically for production deployment rather than academic experimentation.

The goal was not to slightly tweak classical KNN, but to restructure it into a deployable, latency-aware system while preserving interpretability.

What it does differently

Traditional KNN is simple and interpretable, but in practice it struggles with:

Inference latency as datasets grow

Equal treatment of all features

Fixed distance metrics

Unpredictable performance under load

SmartKNN addresses these issues through:

1. Learned Feature Weighting

Feature importance is learned automatically and incorporated into the distance computation. This reduces noise and improves neighbor quality without manual tuning.

2. Adaptive Distance Behavior

Distance computation adapts to learned feature relevance instead of relying on a fixed metric like plain Euclidean.

3. Backend Selection

SmartKNN supports both brute-force and approximate nearest-neighbor strategies.

Small datasets → brute-force

Larger datasets → approximate candidate retrieval

Approximate search is used only to retrieve candidates. Final prediction always uses the learned distance function.

4. CPU-Focused Design

The system is optimized for predictable CPU inference performance rather than GPU-heavy workflows. The focus is stable latency characteristics suitable for production workloads.

5. Unified API

Supports both classification and regression through a scikit-learn compatible interface.

Performance

On structured/tabular datasets with strong local structure, SmartKNN achieves competitive accuracy against tree-based models.

It does not aim to replace tree models or neural networks universally. It performs best where neighborhood structure is meaningful and interpretability is desired.

Limitations

- Requires dataset to remain in memory
- High-dimensional dense data can still challenge nearest-neighbor methods
- No online/incremental updates yet
- Backend preparation adds setup time for large datasets

Project Status

- Public release: 0.2.2
- Stable API
- Open source
- CPU-optimized core
Repository:
https://github.com/thatipamula-jashwanth/smart-knn
I’d appreciate feedback, especially from people who have deployed nearest-neighbor systems in production.

Thanks.

- Jashwanth
by siliconc0w | 2026-02-17 05:38:52+00:00
* Tariffs are hurting most real-world jobs - you don't know what your inputs will cost in 6-12 months and so can't plan

* Political Corruption - you don't know if your permit, M&A, or regulatory rule-change will go through without a bribe to the right person

* Tech, which makes up most of the market, is all in on AI - these companies are late stage and the AI narrative is the only growth story so the market doesn't reward them for investing in anything else

* Cheap globally accessible labor

* Lack of enforcement of anti-trust means stodgy uncompetitive markets with players that make their margin through rent-seeking rather than increasing production or quality of goods and services.

* Poor investments and corruption in our healthcare system make it really expensive to hire Americans

* Poor investments and corruption in education make many Americans unsuitable for high skilled work.
by ggm | 2026-02-17 05:38:54+00:00
I can think of a million reasons not to do this. Not the least of which is I strongly suspect buried in the government specified passport application T&C it says "please don't do this"

If they had said "in your browser" I might have played with it. If they had said "no data flows to back" I might have thought they had pre-empted the obvious question.
by toomuchtodo | 2026-02-17 05:38:54+00:00
“We walked back this specific grift.”

Democrats Push for Transparency on Venezuelan Oil Money Controlled by U.S. - https://www.nytimes.com/2026/02/11/us/venezuela-oil-money-de... | https://archive.today/pWvLH - February 11th, 2026

Trump’s Claim to Venezuelan Oil Money Draws Scrutiny in Congress - https://www.nytimes.com/2026/01/07/us/politics/trumps-claim-... | https://archive.today/xhNT9 - January 7th, 2026 (“President Trump’s declaration that he would personally control the proceeds from oil produced in Venezuela drew instant condemnation on Wednesday from Democrats in Congress who noted that the president had no constitutional authority for such an undertaking.”)
by meowface | 2026-02-17 05:40:08+00:00
AI for helping mitigate PTSD, or helping with the investigations?

Because the latter basically entails helping create a surveillance state. Which in theory could be an acceptable trade-off, but it seems disingenuous to say "AI companies have no financial incentives here" when the big issue is that AI companies would actually be helping to establish powerful dragnet surveillance capabilities. There would need to be a strong democratic process around this.
by ggm | 2026-02-17 05:41:07+00:00
In Australia although Post Offices are privatised franchises, their function as government agents remains. They are certified to take passport photos, which comply with our governments requirements (and I suspect some others but the legal reach here would obviously be modulated) and if you have your old passport no counter-signature is required.

If you e.g. had your photo taken in a government office like for a drivers licence, the question "is this really you" doesn't arise. In relation to all the other information "Is this really your name, DOB, birth certificate" they remain, but not the "is this image the person who applied here and now and signed the form"
by gravypod | 2026-02-17 05:42:14+00:00
> He’s also noticed the interview process getting longer as companies get “more picky,” he says. One recent company required eight rounds, and he still didn’t get the role.

No one can truely understand how grueling this is until they see this happen. My girlfriend recently had a hard time finding a new gig. Entry level office jobs are doing >7 rounds. Phone, recruiter, HR, manager, manager + team member, manager + skip level, ... etc.

Whats even worse is all the people in your life who are older can't understand this at all.

I tried to explain getting ghosted, ghost jobs, online applying, multi-round interviews to my grandma. It just does not make sense. It has never been like this, why is it like this now?
by eigenblake | 2026-02-17 05:42:37+00:00
Biggest limitation I see in this paper: the framing. Any time you have a lot of proprietary knowledge or you've just sorted out the right solution when it's not readily available from the model's parametric knowledge, that's when you should add a skill. Wrap it in a CLI that's easy to inspect. You don't need to store the whole help text of the skill either. The model can inspect it and its subcommands.

Reality doesn't force us to choose between skill or no skill, reality often doesn't give us a choice. You can either make a skill for your company's proprietary system or your model has to figure it out from scratch every time by searching wikis or reading code. If you use it right, skills are a compression mechanism. Instead of the process meaning your model needs to get all of theses files dynamically, it can simply statically run.

To steel-man the paper. It is worth looking at whether you should try to code something up first or try a skill first. And it may well be valid to say try first and if you can't work it out in 5 mins, install a skill. But there's a meta point of skills as software (where you deduplicate the effort of solving regressions).

For a reductio ad absurdum, If self-generated skills with no additional context _didn't_ eventually level off in performance, then we could reach AGI by making one big skill that keeps growing and solving harder and harder tasks, including improving the capability of its own skill-builder skill, all without embedding any signals from the environment or needing to interface with the real world at all.
by DSMan195276 | 2026-02-17 05:43:32+00:00
I agree it was a moderation issue, but for me it's Reddit that largely replaced my SO usage starting some years ago. Reddit is pretty similar to SO in design, but the more decentralized nature of the moderation means that questions rarely get "closed as duplicate" and answers tend to be more up-to-date as a result. There's not always a consensus answer and I'm often looking across multiple threads on the same thing, but that's still better than an outdated SO post.
by chc4 | 2026-02-17 05:44:08+00:00
Yeah, this is basically Sovereign Citizen-tier argumentation: through some magic of definitions and historical readings and arguing about commas, I prove that actually everyone is incorrect. That's not how programming languages work! If everyone for 10+ years has been developing compilers with some definition of undefined behavior, and all modern compilers use undefined behavior in order to drive optimization passes which depend on those invariants, there is no possible way to argue that they're wrong and you know the One True C Programming Language interpretation instead.

Moreover, compiler authors don't just go out maliciously trying to ruin programs through finding more and more torturous undefined behavior for fun: the vast majority of undefined behavior in C are things that if a compiler wasn't able to assume were upheld by the programmer would inhibit trivial optimizations that the programmer also expects the compiler to be able to do.