MurphyA/hacker-news huggingface dataset:
by adamtaylor_13 | 2026-03-03 14:59:33+00:00
This is very generous of you!

If I was the author, however, I'd still feel like I've been put in a predicament where I need to spend personal agency to fix something that Google has broken.

While that may just be a fact of life, my internal injustice-o-meter would be raging. Like, Google is going to take hours of my life because they, with all their billions of capital, can't figure out the canonically-true website when it's RIGHT THERE in the GitHub repository?

Ugh. I guess that's just the day we live in. But it makes me rage against the machine on the author's behalf.
by dlandiak | 2026-03-03 14:59:34+00:00
Hi HN! I'm Dima from the ThingsBoard team — the company behind the open-source IoT platform and TBMQ, our MQTT broker built on top of Apache Kafka.

Most MQTT brokers hit a ceiling when you need to scale horizontally or survive node failures without message loss. We built TBMQ on Kafka because it's battle-tested at scale across the industry — you get fault tolerance, high throughput, and horizontal scalability as a foundation rather than something you bolt on later.

TBMQ has a Community Edition (open-source) and a Professional Edition with advanced observability, enterprise features, and monitoring. The demo runs the PE version, so you can see the full feature set without installing anything.

Two ways to try it:

- No signup: Connect via MQTT directly to "demo.tbmq.io" — ports 1883 (TCP), 8883 (TLS), 443 (WSS), username - "demo", and no password. Test pub/sub, shared subscriptions, retained messages. Public environment, so no sensitive data.

- Quick SSO signup: Head to https://demo.tbmq.io for read-only access to the full professional UI — live session/subscription browsing, message flow dashboards, and more.

Happy to answer questions about the architecture or tradeoffs. Fair criticism welcome.
If AI is great at HTML/CSS, why are AI presentation/CV tools template based?
by bstrama | 2026-03-03 14:59:41+00:00
Most AI resume and presentation tools work like:
AI -> pick a template -> fill in content.

But LLMs are actually pretty good at generating and modifying raw HTML/CSS. In theory, you could:

1. Keep the doc as real HTML (or React)
2. Let AI directly adjust layout and styles
3. Iterate with prompts like “more minimal” or “stronger hierarchy”
4. Export to PDF at the end

So why are we still constraining everything to rigid templates?
Is this about PDF rendering, layout instability, user trust, or something deeper around determinism and control?

Curious if anyone here has tried building something like this and what broke.
by fotcorn | 2026-03-03 15:00:04+00:00
The memory bandwith on M4 Max is 546 GB/s, M5 Max is 614GB/s, so not a huge jump.

The new tensor cores, sorry, "Neural Accelerator" only really help with prompt preprocessing aka prefill, and not with token generation. Token generation is memory bound.

Hopefully the Ultra version (if it exists) has a bigger jump in memory bandwidth and maximum RAM.
by _heimdall | 2026-03-03 15:00:08+00:00
The website is the API though. HTML is one of the few RESTful systems people still use today, build semantics into the page and humans and LLMs can understand how to use it.

A11y specs and APIs are just a way of presenting those semantics differently, often for those who can't see the page, whether visually impaired or in this case an LLM.

At least in my view, we should expect anything claimed to be artificial intelligence to be able to interact with things much like a human would. I'm not going to build an MCP for a CLI tool, for example, I'll just make sure it has a useful man page or `--help` command.
by Imustaskforhelp | 2026-03-03 15:00:16+00:00
Now that does say something about the world, doesn't it?

I think this had just made me curious so yeah haha

I mean one thing I am not understanding is why they would write an article with AI tho. They still prompted AI, might as well give us what they prompted or just write under <300 words or less. I mean its literally twitter (refuse to call it X)

Or like make a 2 minute video with screenshare just talking to the camera about it like they might've with claude perhaps.

They also have discord, They could have literally given a free contributor to help write the article from such video or concerns and credit them properly. I mean, heck I could've written the article for free for just a credit at this point where I got so invested haha.

I genuinely don't understand why you would prompt an article/text out of all things with AI. I hope I never get persuaded with this dark side lol.
by sbrother | 2026-03-03 15:00:17+00:00
> you can get very nice displays for less than half the price that are 98% the same on specs.

Can you recommend any displays with PPI and brightness equivalent to the studio display, with 120Hz+ refresh rates? I was waiting for this announcement to buy a studio display because I thought they might bring 120Hz to the base model, but $3300 is a lot to spend on a single display. I have an original studio display and a high refresh rate 4K OLED monitor, and they are both compromises unfortunately.
by lcnPylGDnU4H9OF | 2026-03-03 15:00:29+00:00
> you can see what mullvad, the company selling a product here, say what the reasoning was.

No, you can see what Clearcast claim as the reasons. It is in the article linked in the parent comment, cited immediately after the quote you pulled from it.

> Clearcast, the organization responsible for pre-approving TV ads in the UK to ensure they comply with the code of broadcast advertising, rejected the ad, reportedly saying, among other things:

> “The overall concept lacks clarity.”

> “Several examples (e.g., paedophiles, rapists, murderers) risk causing serious offence and could imply that the VPN facilitates criminal activity.”

You can, however, see Mullvad's opinion of their reasons.

> Mullvad believes this is deeply concerning.
by bookofjoe | 2026-03-03 15:00:42+00:00
>Some human still has to be accountable. Someone has to get fired / go to jail when something screws up.

I remember growing up and always hearing "The computer is down" as an excuse for why things were cancelled/offices closed/buses and trains not running/ad infinitum.

At some point I read a article that pointed out that the reason the computer was down was because a person made a [coding] error: the computer itself was fine.

I've yet to read about how a person who caused the computer to be down was disciplined.
by vishaal_007 | 2026-03-03 15:00:46+00:00
Co-founder here—it's just me and my partner bootstrapping this thing. We've been wasting tokens left and right just trying to debug our response parsing code. Not even the AI logic, mind you, just our own sloppy stuff and don't get me started on CI: tests flaking out because GPT decides to rephrase something randomly. We got fed up paying real money to fix our bugs, so we hacked together a "Test Mode”. It routes your calls through the full pipeline (auth, logging, everything) but swaps in your sample data instead of hitting the actual provider. No tokens burned, totally deterministic, and lightning fast.

How are folks handling testing for AI integrations? Mocking always felt half-baked to us since it bypasses the real flow. What's working for you?
by bArray | 2026-03-03 15:00:49+00:00
I was sitting in a room the other day with a young adult, we were searching for additional algorithm learning materials. They searched in Google, and accept the cookies. They clicked on a website, and accepted those cookies too. They then started entering their email address to access another service. I was completely taken aback.

I'm the sort of person that either rejects the cookies, or will use another site entirely to avoid some weird dark-pattern cookie trickery. I don't like the idea of any particular service getting more information than they should.

Siting there I realized, we were not the real target. It is the young people that are growing up conditioned to press accept, enter any details asked of them, and to not value their personal data. Sadly, the damage is already done.
by owlcompliance | 2026-03-03 15:01:29+00:00
It's kind of crazy when someone has an outlier experience and then tries to frame an entire country as being that way.

I've experienced a lot of cultures, countries, and environments. The United States is KNOWN for being a friendly country of people who will talk to you and smile at you for "no reason" other than because Americans are friendly.

Go to many countries in Europe or even Russia, you'll experience the exact oppositive. If you smile at people or talk to a stranger, you will essentially be treated as if something is wrong with you.

Everyone knows this is true about the US. Your comment is clearly trying to portray the United States in a negative light with something that is entirely not true.

And then there's my experience: someone who has lived in the US for over 30+ years.
by filoleg | 2026-03-03 15:01:31+00:00
Those two examples you listed don’t necessarily work the way you are describing it. It is way more complex and less clear-cut, which makes sense, because oversimplifying it will lead to silly-sounding conclusions and a pretty incorrect understanding of how this works at all.

For those who don’t want to read the actual full explanation (which is entirely understandable, as it is going fairly into the weeds), I will just a put a TLDR summary at the end. I suggest everyone to check out that summary first, and then come back here if there is interest in a more detailed explanation.

----------------------------

First, we gotta settle on 3 key concepts (among many) the US copyright law relies on.

1. Human authorship - self-explanatory; you cannot assign authorship to a fish or your smartphone.

2. Original/minimal creativity - some creative choices, not just “i pressed the button.”

3. Fixation - the content needs to be recorded on a tangible medium; you cannot copyright a “mood” or a thought, since those aren’t tangible media.

Now onto your hypothetical scenarios:

1) “Initialize an algorithm to point your camera at the street and write those bytes to disk and you are the author of a perpetual stream of data”

Writing bytes to disk satisfies fixation, but it doesn’t automatically make you the author of a copyrightable work. You gotta satisfy the minimum creativity requirement too (e.g., camera positioning, setup, etc.). Otherwise you are just running a fully automated security cam feed with zero human input, and those videos aren’t easily copyrightable (if at all). You might own copyright in a video work if there’s sufficient human creative authorship—but mere automated recording doesn’t guarantee that.

2) “Initialize an algorithm to point your camera at the street and describe those bytes in words and you are no longer the author a perpetual stream of data.”

This is just close to being plainly incorrect. If you (a human) write a textual description, that text is typically copyrightable as a literary work (assuming it’s not purely mechanical like “frame 1: car, frame 2: another car, etc.” with no expressive choices). Creating a description doesn’t erase any copyright you may or may not have had in the underlying recording. They’re just different works (audiovisual work vs. text work). Important to note: neither makes you the author or owner of the underlying “data” of reality, because copyright protects expression, not the underlying facts.

----------------------------

TLDR:

Recording the street can produce a copyrightable work if there is human authorship and minimal creativity in how the recording is made. Pure automated capture may fail that.

Describing the street in words is usually a separate, independently copyrightable work (e.g., a text or audio version of those words), but it doesn’t change the status of the underlying recording.
by applicative | 2026-03-03 15:01:39+00:00
You would think the hebrew population is just exhausted and hardened by several generations of 'deathtoisrael' 'deathtoisrael' drilled into the brains of millions of schoolchildren every year as they build militias saying the same on every border, financing the bizarre suicide campaigns of early 2000s etc. In the end their response will not be simply rational as they are as much mentally affected as the iran citizenry.
It's typical the world community has put up with the naked genocidal intent of the Iran government - which is in a sense woven into its constitution and mystical-apocalyptic self-conception - as if it were a musical curious style. With 'deathtoamerica deathtoamerica' noblesse oblige requires us to pretend it is merely comical. But the 'uppity, arrogant' jewish state is microscopic by comparison with titanic Persian Empire. The disproportion (80x) is far more extreme than even USSR or USA v Afghanistan or USA v Vietnam (30x.
by dathinab | 2026-03-03 15:02:00+00:00
most likely counts as AI-assisted art, which is copyrightable with you as the owner

like most things copyright there is a gray area there

but in most cases it's either pretty clear and courts would most likely rule in your (copyright holder) if you somehow manage to hit the perfect middle of the gray area

through if you tell the court "the author is my AI" (like in this case), the outcome is pretty obvious

also for better understanding using AI doesn't erase copyright, it just doesn't add it. So if you image was copyrightable before you used an AI tool to change it will stay copyrightable (as long as the original image is still in there to a reasonable degree).
by aetherson | 2026-03-03 15:02:35+00:00
Genuine question: is there a big inherent difference between "I don't understand this thing but I think this other human does," and "I don't understand this but I think this other AI does"?

If your answer is "yes," do you think that's inherent to the (metaphysical?) fact of it being AI or to specific limitations to current AI? If the latter, what changes to AI would let you trust it?
by petu | 2026-03-03 15:02:38+00:00
Super is old "performance" core:

> The industry-leading super core was first introduced as performance cores in M5, which also adopts the super core name for all M5-based products

But new "performance" is claimed to be new design (= not just overclocked efficiency core from M5?):

> M5 Pro and M5 Max also introduce an all-new performance core that is optimized to deliver greater power-efficient, multithreaded performance for pro workloads.

quotes from https://www.apple.com/newsroom/2026/03/apple-debuts-m5-pro-a...
by tbrownaw | 2026-03-03 15:02:51+00:00
> why this is so huge is fascinating. i suspect it is not really about the age gap, but rather

Alternate theory: it's a genre tag that implies a whole pile of arbitrary features. Kind of along similar lines as how calling a movie a "space western" tells you quite a lot about it, despite making absolutely no sense if you try to take it strictly literally.
Show HN: I Built Systems AGI – 1600 Verticals, Self-Healing\Self-Evolving
by Sophify | 2026-03-03 15:03:02+00:00
Hey HN,

For a while now, I've been building a cognitive AI business operating system from the ground up natively as a solo developer. I never coded before 6 months ago. I was frustrated with wrappers and fragile single-agent setups, so I decided to approach this as a distributed systems problem instead. It's called *Sophify*.

Instead of trying to make one monolithic capability do everything, I built a 12-server, 28+ microservice swarm orchestrated by over 40 highly specialized cognitive AI agents.

*Here’s the architecture under the hood:*
* *40+ Agent Architecture (Model Agnostic):* Decisions aren’t made by a single prompted agent. There is a multi-agent orchestration system that uses weighted voting and consensus across 40+ specialized cognitive agent profiles to synthesize decisions. Crucially, the system is LLM-agnostic—you can plug in whatever LLM you prefer (local or remote) to power the reasoning engines.
* *The Technician Bot:* Given that this comprises 28+ interconnected microservices running in the cloud. I wrote a persistent Technician layer. If a node hangs or hits a port collision (hello `WinError 10048`), the Technician detects it, diagnoses the stack, kills zombie processes, reallocates networking, and brings the service back online with zero human intervention.
* *1,600+ Industry Verticals:* Rather than building general-purpose workflows, the OS comes pre-loaded with state machines and hardcoded context for over 1,600 specific verticals running 1,284 autonomous workflows—handling everything from healthcare compliance to real estate out-of-the-box.
* *Military-Grade Security & Built-in VPN:* The entire system runs inside an integrated, zero-trust VPN layer with cryptographic audit trails and multi-tenant isolation. Production-ready for DoD contracts, healthcare (HIPAA), and enterprise compliance.
* *Deep Microsoft 365 Integration:* Full Microsoft Graph API implementation with native access to email, calendar, Teams, OneDrive, SharePoint, and Planner. The system orchestrates across AWS, Azure, and GCP with vertical-specific API frameworks for healthcare EHRs, real estate MLS systems, and finance platforms.

*Why did I build this?*
Started with API keys, ended with self-evolving, self-healing Systems AGI... and I still have to retrieve my own API keys lol. At least the system is fully decoupled, heals its own memory leaks and stalled sockets natively, and scales horizontally.

Happy to answer any questions about the 13-layer self-healing mechanism, managing the websockets across a 12-server swarm without race conditions, or the multi-agent consensus algorithms.
*Serious acquisition inquiries:* sophify-aaron@hotmail.com
Tear it apart. What did I miss?
by tux3 | 2026-03-03 15:03:03+00:00
>Are not LLMs supposed to just find the most probable word that follows next like many people here have touted?

The base models are trained to do this. If a web page contains a problem, and then the word "Answer: ", it is statistically very likely that what follows on that web page is an answer. If the base model wants to be good at predicting text, at some point learning the answer to common question becomes a good strategy, so that it can complete text that contains these.

NN training tries to push models to generalize instead of memorizing the training set, so this creates an incentive for the model to learn a computation pattern that can answer many questions, instead of just memorizing. Whether they actually generalize in practice... it depends. Sometimes you still get copy-pasted input that was clearly pulled verbatim from the training set.

But that's only base models. The actual production LLMs you chat with don't predict the most probable word according to the raw statistical distribution. They output the words that RLHF has rewarded them to output, which includes acting as an assistant that answers questions instead of just predicting text. RLHF is also the reason there are so many AI SIGNS [1] like "you're absolutely right" and way more use of the word "delve" than is common in western English.

[1]: https://en.wikipedia.org/wiki/WP:AISIGNS
by simonw | 2026-03-03 15:03:10+00:00
One thing that's worth remembering is that companies - especially in Silicon Valley - use titles as a way to compare salary levels with each other.

If you are an engineering manager looking to make the case for raises for your team members one of the tools you have available is usually an anonymized survey of similar compensation levels from other companies.

You can say things like "this person is a high performer and is being paid 85% of the expected level for this title at other companies nearby - we should bump them up".

Your company may use job titles in a non-standard way, but there's probably an HR document somewhere that attempts to map them to more standard levels in order to make these kinds of comparisons useful.

I don't know how this works in other industries or countries, but I've seen this pattern play out in San Francisco Bay Area tech companies.
by Imustaskforhelp | 2026-03-03 15:03:25+00:00
This is an interesting rabbit hole I wasn't prepared to jump in. Thanks for sharing the article, the world does work in strange coincidences indeed.

Have given a glance through it but I am also bookmarking to read it later once I get more free. Thanks for sharing it!

From the article:

> Wait, what? I can put a dot at the end of my domain names?

This was exactly how I felt at that moment :) The article has started pretty nicely.
by Someone1234 | 2026-03-03 15:03:27+00:00
The MacBook Pro M5 came out about six months ago[0]. The MBPs M5 Pro and M5 Max were released today also[1].

[0] https://www.apple.com/newsroom/2025/10/apple-unveils-new-14-...

[1] https://www.apple.com/newsroom/2026/03/apple-introduces-macb...
by AleksDoesCode | 2026-03-03 15:03:48+00:00
Hey yarivk,

thanks I do appreciate it!
The local mode depends heavily on the hardware and the model you choose.

I run it exclusively in local mode nowadays.
Old Macbook Pro with M1 chip with 32g ram + Model Large v3 Turbo.

Transcribing one minute of audio takes around 2-3 seconds, compared to the 0.5 to 1 second if using the openAI API.

For my usecase this a no brainer.
Not having to pay + keeping all of my data private is well worth waiting 1.5 seconds longer. Also I simply think it is pretty cool to run models locally, so there that :D

Feel free to try it out completely for free and lmk your thoughts!
by jjuniordev | 2026-03-03 15:03:48+00:00
Same! Not an Excel pro and also have zero interest in going deep at Excel at all here.

Seems like you've been running this setup for quite some time. Curious to know if your setup is similar to how I did it, or do you have a slighly different config? Do you also use json files for your data and just let Claude do all the magic?
by zvqcMMV6Zcr | 2026-03-03 15:04:09+00:00
> Their entire business model was to funnel traffic to websites with their ads.

This doesn't change, they will still show ads somewhere around AI overview. As part of it if it is both technically feasible and legal.

The part of equation that is gone, is how organic traffic got to sites that published quality content. Now they might as well shutdown or switch to hard paywall. Both won't affect Google for few year, until websites (other than shops) are dead, knowledge stored in LLMs gets outdated and search engines have tiny index, that is a shadow of past size.
by ericd | 2026-03-03 15:04:18+00:00
Hard to get 6000+ bit memory bus HBM bandwidth out of a 512 or 1024 bit memory bus tied to DDR... I think it's also just tough to physically tie in 512 gigs close enough to the GPU to run at those speeds. But yeah, I wish there was a very competitive local option, too, short of spending $50k+.
by nsbk | 2026-03-03 15:04:20+00:00
Safari routinely using 20+ Gb of memory with a handful of tabs open. Safari tabs refusing to close. Unresponsive System Settings window. Random application freezes and crashes, Apple Music not playing music. This is on a 32Gb M1 Max. My M1 Air on Sequoia doesn't experience any of these issues, even if it has half the unified memory.
by roywiggins | 2026-03-03 15:04:36+00:00
My guesses in no particular order:

1) this style genuinely is preferred by lots of people on X/Twitter so you might as well lean into it

2) People who spend a lot of time with LLMs think this sort of writing is normal or even standard just through overexposure, a sort of pseudo social proof

2b) People who spend a lot of time with other people who use LLMs think this is how humans write (actual social proof)

3) People are insecure about their writing ability and find the non-judgmental non-human LLM editor soothing

4) people are lazy

5) people aren't lazy per se but they know writing has been so devalued that they aren't going to spend time on it that they don't need to

6) their first experience of writing was trying to hit word count requirements in grade school and that stuck

7) Visibly using LLMs is becoming a shibboleth for a social group on Twitter and LinkedIn. It's a marker that you are dogfooding the crappy AI tools you're developing and selling. Under this theory, being visibly LLM output is actually intentional: "look ma, no hands- all NanoClaw!"