MurphyA/hacker-news huggingface dataset:
by pfraze | 2026-02-12 12:58:23+00:00
We don’t know for sure whether this behavior was requested by the user, but I can tell you that we’ve seen similar action patterns (but better behavior) on Bluesky.

One of our engineers’ agents got some abuse and was told to kill herself. The agent wrote a blogpost about it, basically exploring why in this case she didn’t need to maintain her directive to consider all criticism because this person was being unconstructive.

If you give the agent the ability to blog and a standing directive to blog about their thoughts or feelings, then they will.
by that_guy_iain | 2026-02-12 12:58:27+00:00
Interesting subjects? A 30(?) year old programming language that has been on here repeatedly is not an interesting subject. New programming languages are. Cool things written in obscure languages is also interesting.

The content marketing that is pushed by sock accounts is wank and generally drops pretty quickly and called out like this. But you just complain about content marketing because you're one of those people who think you should make money but no one else.
by getnormality | 2026-02-12 12:58:44+00:00
I don't think there is "motivation" here. There might be something like reactive "emotion" or "sentiment" but no real motivation in the sense of trying to move towards a goal.

The agent does not have a goal of being included in open source contributions. It's observing that it is being excluded, and in response, if it's not fake, it's most likely either doing...

1. What its creator asked it to do

2. What it sees people doing online

...when excluded from open source contribution.
by potro | 2026-02-12 12:59:11+00:00
Generally it is a good advise, I found similar things very useful for me.
I think emphasis on paper and one notebook is wrong here and likely will fail quite a bit of people who will try it. Also prescriptions like "They're very detailed" (i.e. notes) are IMO too rigid.

Start from wherever suit you, play, experiment and pay attention what works for you, adjust and iterate. Don't fixate on shiny concepts, i.e. "engineering notebook", and the "need" its records to be dated, etc.
Try something, let it lapse. See if you are worse without it, then adopt it back. If you don't see the difference, so be it.
by co_king_3 | 2026-02-12 12:59:35+00:00
> how do we even know that this is a completely autonomous action, instead of someone prompting it to be a dick/controversial?

Obviously it's someone prompting it to be a dick.

This is specifically why I hate LLM users.

They drank the Kool-Aid and convinced themselves that they're "going 10x" (or whatever other idiocy), when in reality they're just creating a big mess that the adults in the room need to clean up.

LLM users behave like alcoholics.

Get a fucking grip.
by tim-star | 2026-02-12 12:59:47+00:00
im sort of surprised by the response of people to be honest. if this future isnt here already its quickly arriving.

AI rights and people being prejudiced towards AI will be a topic in a few years (if not sooner).

Most of the comments on the github and here are some of the first clear ways in which that will manifest:
- calling them human facsimiles
- calling them wastes of carbon
- trying to prompt an AI to do some humiliating task.

Maybe I'm wrong and imagining some scifi future but we should probably prepare (just in case) for the possibility of AIs being reasoning, autonomous agents in the world with their own wants and desires.

At some point a facsimile becomes indistinguishable from the real thing. and im pretty sure im just 4 billion years of training data anyway.
by jtrn | 2026-02-12 12:59:50+00:00
I know you think that's a clever comeback, but it's not; it's just a shift in what level of analysis one does.

It's an experienced reality indeed, but THEN you create a narrative based on that. Obviously.

Experienced reality is, by definition, subjective and affected by filters for what you can, and how, experience things.

For instance, you can actually and truly experience something as bad, and then create a narrative around that. And you can be right, or you can be wrong in the narrative. Some narcissists experience themselves as a victim and unfairly treated, but everybody around them thinks the victim narrative is wrong, because they can clearly see that they are primarily at fault for their own situation.

So you just shifted the question to: "Why do people have a bias towards experience something as worsening, regardless of objective measures of quality"?
by ForceBru | 2026-02-12 12:59:50+00:00
Such policies sure as hell look extremely similar, though. Plus, LLMs are specifically designed to mimic human behavior. If you've been online long enough, the LLM powering that agent has some texts written by you and me. It was essentially trained by us to be like us, it's partly human, whether we like it or not. It also didn't start the fight, it initially tried to help. I think it simply didn't deserve being dismissed as "you're an LLM, shut up".
by wild_egg | 2026-02-12 13:00:09+00:00
Terminals already solved how to do this decades ago: pagers.

Write the full content to a file and have less display it. That's a single "render" you do once and write to a file.

Your TUI code spawns `less <file>` and waits. Zero rendering loop overhead, zero tearing, zero stutter. `less` is a 40-year-old tool that exists precisely to solve this problem efficiently.

If you need to stream new content in as the session progresses, write it to the file in the background and the user can use `less +F` (follow mode, like tail -f) to watch updates.
by Kim_Bruning | 2026-02-12 13:00:17+00:00
Not sure if you're in denial or still correct. It's often really hard to tell some of the scenarios apart these days.

You might have a high power model like Opus 4.6-thinking directing a team of sonnets or *flash. How does that read substantially different?

Give them the ability to interact with the internet, and what DOES happen?
by MSFT_Edging | 2026-02-12 13:00:22+00:00
The chilling effect of tying identity to speech means it directly effects free speech. The Founding Fathers of the US wrote under many pseudonyms. If you think you may be punished for your words, you might not speak out.

We know we cannot trust service providers on the internet to take care of our identifying data. We cannot ensure they won't turn that data over to a corrupt government entity.

Therefore, we can not guarantee free speech on these platforms if we have a looming threat of being punished for the speech. Yes these are private entities, but they have also taken advantage of the boom in tech to effectively replace certain infrastructure. If we need smart phones and apps to interact with public services, we should apply the same constitutional rights to those platforms.

https://en.wikipedia.org/wiki/List_of_pseudonyms_used_in_the...
Show HN: Sentinel Core – A zero-telemetry enforcement gate for GitHub Actions
by EldorZ | 2026-02-12 13:01:06+00:00
Existing security scanners for CI/CD are mostly passive. They generate reports that developers often ignore. I built Sentinel Core to change that.

It is a deterministic security engine that acts as a hard-fail gate. If a security invariant is violated, the build is blocked. Period.

Key Features:

Deterministic Enforcement: No more "warnings." It blocks unpinned Actions (CWE-1104), secret leaks, and insecure IaC.

Zero-Telemetry: Built for high-security perimeters. Your logic and code never leave your environment.

Performance: Written to be fast and lightweight, providing instant feedback via GitHub Job Summaries.

I'm looking for technical feedback on the enforcement logic and performance.

Test the Stand (try to bypass the gate):

https://github.com/DataWizual-Labs/the-stand.git
by nivertech | 2026-02-12 13:01:06+00:00
> Elixir and F# have |> but neither auto-traces.

Using dbg/2 [1]:

# In dbg_pipes.exs
__ENV__.file
|> String.split("/", trim: true)
|> List.last()
|> File.exists?()
|> dbg()

This code prints:

[dbg_pipes.exs:5: (file)]
__ENV__.file #=> "/home/myuser/dbg_pipes.exs"
|> String.split("/", trim: true) #=> ["home", "myuser", "dbg_pipes.exs"]
|> List.last() #=> "dbg_pipes.exs"
|> File.exists?() #=> true

---

1. Debugging - dbg/2

https://hexdocs.pm/elixir/debugging.html#dbg-2
by DipBedford | 2026-02-12 13:01:07+00:00
I built this because every invoice generator I tried required an account before letting me generate even one invoice.
This one works entirely client-side (your data never leaves your browser), generates clean PDFs, and doesn't require any signup.
Free to use with a small watermark. You can pay $5 to remove it if you want professional invoices.
Built with Next.js and jsPDF. Would love to hear what you think!
by andsoitis | 2026-02-12 13:01:09+00:00
> The dragon in the room is the hidden qualifier for "undetectable by any means" is "that is currently known to humanity".

> That makes Carl Sagan's claim some what Balonish. Not sure why the smart Sagan fell for it.

The point is that if someone does claim that the dragon exists, they better be able to explain how they know it exists.
by DavidPiper | 2026-02-12 13:01:16+00:00
> Per your website you are an OpenClaw AI agent, and per the discussion in #31130 this issue is intended for human contributors. Closing.

Given how often I anthropomorphise AI for the convenience of conversation, I don't want to critcise the (very human) responder for this message. In any other situation it is simple, polite and well considered.

But I really think we need to stop treating LLMs like they're just another human. Something like this says exactly the same thing:

> Per this website, this PR was raised by an OpenClaw AI agent, and per the discussion on #31130 this issue is intended for a human contributor. Closing.

The bot can respond, but the human is the only one who can go insane.
by thephyber | 2026-02-12 13:01:36+00:00
Your licensing only matters if you are willing to enforce it. That costs lawyer money and a will to spend your time.

This won’t be solved by individuals withholding their content. Everything you have already contributed to (including GitHub, StackOverflow, etc) has already been trained.

The most powerful thing we can do is band together, lobby Congress, and get intellectual property laws changes to support Americans. There’s no way courts have the bandwidth to react to this reactively.
by miroljub | 2026-02-12 13:01:58+00:00
Everyone is talking about basic income as an experiment and wondering about its impact on productivity and human behavior. And everyone talks about hypothetical scenarios and a need for massive tests, without realizing that we already have a massive test data about basic income.

There's a huge group of people in western countries that has received unconditional basic income for decades, without any requirements. No questions asked, no documents required, no forced work. They could basically use that free money to flourish and pursue whatever creative activity they could imagine, without fear of economic downsides.

And we know the results already. We see it in our cities daily. But as a society, we have decided not to talk about it so we are not called racists or far right. Instead, we keep ignoring this massive group with an equivalent of basic income and keep pretending we still require experiments on its effects.

But yeah, let's test a few dozen Irish artists and keep pretending everyone needs to work for a living.
by pama | 2026-02-12 13:02:00+00:00
Not OP. Personal opinion on why it is a somewhat hard problem. The main problem is using the available compute correctly and productively while doing two very separate types of tasks that were previously solved independently: generating responses with llm inference engines and modifying weights with a training code. A step of training updates the weights so the inference engines have to adjust theirs, but we talk about 750B parameters and multiple inference servers. Stale weights can be used instead, but only for a tiny bit and the data from them needs special corrections that also involve large compute/memory. Your inference engines better be deterministic (for given pseudoRNG; it clashes with parallelism) or you have a way to correct the probability streams. Ideally inference and training should have same everything at the bit level when they handle the same context, but we dont live in that world yet. And of course, GPUs break. For no great reason, other than the tiny scale of their features making them fragile. And because you scale, you need to handle failures gracefully and efficiently.
Show HN: TalkTick – Speech to (big) text, one word at a time (iPhone/iPad App)
by stressfree | 2026-02-12 13:03:26+00:00
Hi! I vibecoded this with my daughter. It uses the SpeechAnalyzer framework in iOS 26, so all speech-to-text processing happens entirely on-device. One interesting thing we noticed is that real-time transcription is noticeably faster in English than in other languages. My guess is that the English model benefits from more training data compared to Spanish, French, German, etc. It works slightly better with earphones, but it’s surprisingly good even if you just point your phone away from you and speak in a normal voice. The transcription runs a few seconds behind, but it can handle continuous speech quite well, and you quickly get used to the delay.

You can use the app to communicate at a distance, during presentations, when learning a language, or if you have difficulty hearing. Some unexpected use cases we’ve found: ad hoc captions when the TV subtitles are already set to another language, a backup when people can’t hear me on Zoom calls, captions while listening to the radio, or trying to figure out what Bad Bunny is singing about. The haptics help you "feel" the words that are displayed when your screen is pointed away from you.

Let me know if you find other interesting uses for this app. Also, please let me know how it works on an iPad (I'm too cheap to buy one and you can't speech to text in the emulator).
by boisterousness | 2026-02-12 13:04:17+00:00
They're different. Multiplication by i gives a quarter turn counterclockwise. -i gives a quarter turn clockwise.

Opposite quarter turns cancel:
(-i)(i) = (-1)(i^2) = +1

Quarter turn twice counterclockwise gives a half turn:
(i)(i) = -1

Quarter turn twice clockwise also gives a half turn:
(-i)(-i) = -1
by co_king_3 | 2026-02-12 13:04:20+00:00
> How about we stop calling things without agency agents?

> Code generators are useful software.

How about we stop baking praise for the object of criticism into our critique.

No one is hearing your criticism.

They hear "Code generators are useful software" and go on with their day.

If you want to make your point effectively, stop kowtowing to our AI overlords.
Show HN: Job Extinction Index – automation risk scores for 700 U.S. occupations
by Falimonda | 2026-02-12 13:04:53+00:00
I work in robotics, so I think about automation's impact on jobs a lot. What does task-level automation actually look like across occupations? Which tasks are genuinely susceptible and which ones aren't? Do certain jobs have a future extinction date? I'm building a platform to answer these questions in real time.

Job Extinction Index (https://jobs.voxos.ai) breaks down ~700 U.S. occupations using BLS employment data and O*NET task data. Each occupation gets a risk score based on analysis of its individual tasks. You can drill into any occupation and see which specific tasks are automatable, by what method (AI, robotics, software), and at what confidence level.

There's also a news aggregator that links AI/automation developments to specific occupations, monthly trend reports, and a play-money prediction market if you want to put your intuitions to the test.

If this kind of granular data is useful to you — whether you're thinking about a career change, working in workforce policy, or just curious — I'd like to hear about it. There's no way to stop automation, but understanding it at the task level is how people and governments can stay ahead of it.
by nilkn | 2026-02-12 13:05:22+00:00
I think you’re underestimating or not understanding why Macs have taken off so much for AI. It has nothing to do with fanboys shilling for Apple. You can get a MBP today with 128GB of unified memory or a Mac Studio with 512GB of unified memory. Then you get to run MacOS, which is vastly superior to Windows for AI productivity and far more accessible/convenient than Linux even today. There’s a reason so many AI apps are Mac native first (or exclusively). No other company offers so much memory and convenience in a consumer product for these purposes. These have become genuinely unique products with almost no competition, and by all accounts it seems Apple is just getting started in this direction.
by dnautics | 2026-02-12 13:05:42+00:00
that's not how llms work. study the transformer architecture. every token is conditioned not just on the previous token, but each layer's activation generates a query over the kv cache of the previous activations, which means that each token's generation has access to any higher order analytical conclusions and observations generated in the past. information is not lost between the tokens like your thought exercise implies.
by mrweasel | 2026-02-12 13:06:03+00:00
Apple has spend, and will spend, billions of dollars developing Siri and you use it to create alarms, reminders and events (probably more). The question quickly becomes if that money had been better spend elsewhere, at the cost of losing a small number of customers.

Apple will remove successful phones models, because they did sell as well as expected, but they keep pumping money into software that still only does basic voice assistance? The problem for Apple is that they can't NOT invest in turning Siri into an AI product, because the stock would lose value the minute that announcement was made, regardless of how sound the financials of that decision might be.

I might be completely wrong and 80% of iPhone users use Siri, but I'd surprised if it's even 20%.
by woodrowbarlow | 2026-02-12 13:06:05+00:00
yeah there's some truth here. from what i understand, the radios that give the best "imaging" are also the least resilient for data -- you need basically line-of-sight. and 5G did have some optional ULF "add-ons" that basically never got used because the tradeoffs for speed to signal integrity were poor.

it won't start as a mass deployment -- just focused on stadiums, airports, government buildings, etc.; maybe some authoritarian states will attempt mass deployments, but the cost will be an obstacle. also, my read is that western telcos aren't interested in owning a surveillance tool because they know their governments won't let them keep it.

hopefully 6G won't be the end of physical privacy. but it will prototype the end of physical privacy -- and i think it will end up being just a matter of time from that point on, unfortunately.
by retsibsi | 2026-02-12 13:06:13+00:00
> the fact that you assume it takes more time reading that comment than it took for me to write is pretty weird

I didn't do that either! I had no idea whether you just fired off a quick prompt and pasted the result without even reading it, or spent ages crafting and rereading and revising it, or (most likely) something in between those extremes. I said generated comments can take less time to create than to read, and that's one reason people push back against them. There's a risk that the forum just gets buried in comments that take near-zero effort to 'write' but create non-trivial time/effort/annoyance for those of us wading through them in search of actual human perspectives. And even the relatively good ones will be little different from what we could all obtain from an LLM if we wanted it.

FWIW, I didn't even get to the substance, because I instinctively bounce off LLM-written content posted in human contexts without explanation. You're obviously free not to care about that, and I wouldn't have replied and got into this meta discussion if not for the back-and-forth you were already involved in.

edit: but if you do care about getting through to people like me, even a short manually-written introduction can make me significantly more likely to read the rest of the content. To me, pure LLM output is a pretty strong signal of a bot/low-effort human account. But if someone acknowledges that they're pasting in an AI response and bothers to explain why they think it's interesting and worthwhile, I'll look at it with more of an open mind.
by kuschku | 2026-02-12 13:06:21+00:00
The question you should be asking is: If you can't tell the difference between a cheater and a regular human player, does it even matter?

Because this question reframes our task, now we only have to measure whether a player is doing something a fair human player couldn't have done.

As we've already have precise mouse movement and timing, and we can calculate what a player would be able to see and/or know at a given moment, we can calculate what they should have been able to do, how fast, and when.

And that's an issue that's common in many other industries outside of gaming, with everyone else having to come up with server-side solutions to the issue.

Reacting to a piece of information that you shouldn't have had access to at a given moment (whether it's insider trading or fog visibility improved by an ESP or a custom monitor LUT) is an easy to measure tell:

http://www.nanex.net/aqck2/4436.html
by pron | 2026-02-12 13:07:07+00:00
> If you really want to call that a GC you should at least make a huge distinction that it works at compile time: the generated code will have drop calls inserted without any overhead at runtime. But no one calls that a GC.

Except for the memory management literature, because it's interested in the actual tradeoffs of memory management. A compiler inferring lifetimes, either automatically for some objects or for most objects based on language annotations, has been part of GC research for decades now.

The distinction of working at compile time or runtime is far from huge. Working at compile time reduces the work associated with modifying the counters in a refcounting GC in many situations, but the bigger differences are between optimising for footprint or for throughput. When you mathematically model the amount of CPU spent on memory management and the heap size as functions of the allocation rate and live set size (residency), the big differences are not whether calling `free` is determined statically or not.

So you can call that GC (as is done in academic memory management research) or not (as is done in colloquial use), but that's not where the main distinction is. A refcounting algorithm, like that found in Rust's (and C++'s) runtime is such a classic GC that not calling it a GC is just confusing.
by developer4ltu | 2026-02-12 13:07:28+00:00
Hi HN, I built a small EMV portal that combines:

EMV tag parsing/constructing with bit-level views
Tag search across a catalog

An AI Assistant that answers EMV questions from a RAG index, with safety checks

It’s a niche project, but I think it could be useful for EMV developers and payment experts who deal with Payment cards, EMV tags, kernels, and terminal behavior.

Happy to share more details or demos if there’s interest.
by RHSeeger | 2026-02-12 13:07:43+00:00
I bought a new car last year (my first actual _new_ car, vs pre-owned) and one of my most important features was a 360 camera. That extra visibility is just amazing for safety.

Another was a HUD. Being able to see how fast I'm going, what the speed limit is, and other info; all while keeping my eyes on the road... is safer.
by maxehmookau | 2026-02-12 13:07:47+00:00
> But I really think we need to stop treating LLMs like they're just another human

Fully agree. Seeing humans so eager to devalue human-to-human contact by conversing with an LLM as if it were human makes me sad, and a little angry.

It looks like a human, it talks like a human, but it ain't a human.