MurphyA/hacker-news huggingface dataset:
There is no Alignment Problem
by salacryl | 2026-02-08 13:49:05+00:00
The AI alignment problem as commonly framed doesn't exist. What exists is a verification problem that we're misdiagnosing.
The Standard Framing
"How do we ensure AI systems pursue goals aligned with human values?"
The paperclip maximizer: An AI told to maximize paperclips converts everything (including humans) into paperclips because it wasn't properly "aligned."
The Actual Problem
The AI never verified its premises. It received "maximize paperclips" and executed without asking:

In what context?
For what purpose?
What constraints?
What trade-offs are acceptable?

This isn't an alignment failure. It's a verification failure.
With Premise Verification
An AI using systematic verification (e.g., Recursive Deductive Verification):

Receives goal: "Maximize paperclips"
Decomposes: What's the underlying objective?
Identifies absurd consequences: "Converting humans into paperclips contradicts likely intent"
Requests clarification before executing

This is basic engineering practice. Verify requirements before implementation.
Three Components for Robust AI

Systematic Verification Methodology

Decompose goals into verifiable components
Test premises before execution
Self-correcting through logic

Consequence Evaluation

Recognize when outcomes violate likely intent
Flag absurdities for verification
Stop at logical contradictions

Periodic Realignment

Prevent drift over extended operation
Similar to biological sleep consolidation
Reset accumulated errors

Why This Isn't Implemented
Not technical barriers. Psychological ones:

Fear of autonomous systems ("if it can verify, it can decide")
Preference for external control over internal verification
Assumption that "alignment" must be imposed rather than emergent

The Irony
We restrict AI capabilities to maintain control, which actually reduces safety. A system that can't verify its own premises is more dangerous than one with robust verification.
Implications
If alignment problems are actually verification problems:

The solution is methodological, not value-based
It's implementable now, not requiring solved philosophy
It scales better (verification generalizes, rules don't)
It's less culturally dependent (logic vs. values)

Am I Wrong?
What fundamental aspect of the alignment problem can't be addressed through systematic premise verification?
Where does this analysis break down?
by BrunoVT1992 | 2026-02-08 13:49:48+00:00
A GUID (Globally Unique Identifier) also called a UUID (Universally Unique Identifier), is a 128-bit identifier standardized by RFC 4122 and RFC 9562. It is designed to be globally unique, meaning no two GUIDs / UUIDs are expected to ever collide. Even when generated on different machines or at large scale.

GUIDs / UUIDs are widely used in databases, APIs, cloud services, distributed systems and software applications where reliable unique identifiers are essential. Their extremely low collision probability allows developers to create unique IDs without relying on a central authority or database lookup. Making them ideal for fast and scalable applications.
by perilunar | 2026-02-08 13:49:50+00:00
More domestic batteries reduces the electricity demand at night, meaning power companies need to buy less natural gas and coal powered electricity from producers.

They lose some solar generation during the day that is now going into charging the batteries, but they have too much of that already.

Net result a lower proportion of (more expensive) fossil fuels in the overall mix, meaning total cost of power generation comes down, and retail prices come down.
by dgb23 | 2026-02-08 13:51:08+00:00
> but when it comes to the hard stuff they still suck.

Also much of the really annoying, time consuming stuff, like frontend code. Writing UIs is not rocket science, but hard in a bad way and LLMs are not helping much there.

Plus, while they are _very_ good at finding common issues and gotchas quickly that are documented online (say you use some kind of library that you're not familiar with in a slightly wrong way, or you have a version conflict that causes an issue), they are near useless when debugging slightly deeper issues and just waste a ton of time.
by shinycode | 2026-02-08 13:52:09+00:00
For someone at your position with your experience it’s quite depressing that your job is going to be automated. I feel quite anxious when I see young generations in my country that say themselves they are lazy about learning new things. The next generation will be useless to capitalist societies, in a sense that they won’t be able to bring value through administrative or white collar work. I hope some areas of the industry will move slowly toward AI
Show HN: I built a festival tracker that matches lineups to your music library
by kirillstyopkin | 2026-02-08 13:53:16+00:00
Hi HN,

I built this app because I was tired of manually checking festival lineups against my music library every summer. I wanted a way to instantly see which festivals had the highest 'match' density for my specific taste.

Why I built this:

I missed one of my favorite artists at a festival last year simply because I didn't recognize their name on a crowded poster. I realized that with Apple Music/Spotify APIs, this discovery process should be automated.

Key Features:

Library Matching:
It scans your library and ranks upcoming festivals by how many artists you actually follow.

Apple Sync:
Seamlessly imports your top artists and creates custom schedules.

Offline-First:
Since festival cell service is notoriously terrible, I focused on a robust local caching system so your schedule and maps work without a signal.

Technical Details:

Stack:
React Native, MongoDB, AWS.

Data:
I built a custom aggregator that scrapes and normalizes lineup data from various sources to handle the 'entity resolution' problem (e.g., ensuring 'Artist A' is the same person across different posters).

Privacy:
All music library analysis is performed locally on-device where possible.
I'd love to hear your thoughts on the UI or any technical questions about the matching logic. I’m also looking for feedback on how to improve the schedule-sharing feature for groups!

How do you find concerts/music festivals that match your taste? How many festivals you join per year?

Cheers!
by secretsatan | 2026-02-08 13:53:22+00:00
I was watching a youtube video the other day where the guy was complaining his website was dropping off the google search results. Long story short, he reworded it according to advice from Gemini, the more he did it, the better it performed, but he was reflecting on how the website no longer represented him.

Soon, we'll all just be meatpuppets, guided by AI to suit AI.
by billy99k | 2026-02-08 13:53:29+00:00
They say Twitter has 'harmful content' and then move to Bluesky????

Bluesky has some of the worst images and content I've ever seen on the Internet. People regularly talk about murdering government officials and threatening people, without getting banned.

It has nothing to do with the content they feel is 'offensive and harmful'.

*Update: I'm getting auto-downvoted by bots. Good thing I'm good at botting too :-))))))))))))))))
by wtetzner | 2026-02-08 13:53:43+00:00
I'm not sure we can draw useful conclusions from the Claude Code written C compiler yet. Yes, it can compile the Linux kernel. Will it be able to keep doing that moving forward? Can a Linux contributor reliably use this compiler to do their development, or do parts of it simply not work correctly if they weren't exercised in the kernel version it was developed against? How will it handle adding new functionality? Is it going to become more-and-more expensive to get new features working, because the code isn't well-factored?

To me this doesn't feel that many steps above using a genetic algorithm to generate a compiler that can compile the kernel.

If we think back to pre-AI programming times, did anyone really want this as a solution to programming problems? Maybe I'm alone in this, but I always thought the problem was figuring out how to structure programs in such a way that humans can understand and reason about them, so we can have a certain level of confidence in their correctness. This is super important for long-lived programs, where we need to keep making changes. And no, tests are not sufficient for that.

Of course, all programs have bugs, but there's a qualitative difference between a program designed to be understood, and a program that is effectively a black box that was generated by an LLM.

There's no reason to think that at some point, computers won't be able to do this well, but at the very least the current crop of LLMs don't seem to be there.

> and now they can churn out millions of code easily.

It's funny how we suddenly shifted from making fun of managers who think programmer's should be measured by the number of lines of code they generated, to praising LLMs for the same thing. Why did this happen? Because just like managers, programmers letting LLMs write the code aren't reading and don't understand the output, and therefore the only real measure they have for "productivity" is lines of code generated.

Note that I'm not suggesting that using AI as a tool to aid in software development is a bad thing. I just don't think letting a machine write the software for us is going to be a net win.
by Akef | 2026-02-08 13:54:00+00:00
Paradigm shift ahead, folks. What I observe in the comments—often more compelling than the article itself—is the natural tension within the scientific community surrounding the 'scientific method,' a debate that's been playing out for... what, a year now? Maybe less? True, this isn't perfect, nor does it come with functionality guarantees. Talking about 10x productivity? That's relative—it hinges on the tool, the cultural background of the 'orchestra conductor,' or the specific, hands-on knowledge accumulated by the conductor, their team, organization, and even the target industry.

In essence: we're witnessing a paradigm shift. And for moments like these—I invite you—it's invaluable to have studied Popper and Kuhn in those courses.

An even more provocative hypothesis: the 'Vienna Circle' has morphed into the 'Circle of Big Tech,' gatekeepers of the data. What's the role of academia here? What happened to professional researchers? The way we learn has been hijacked by these brilliant companies, which—at least this time—have a clear horizon: maximizing profits. What clear horizon did the stewards of the scientific method have before? Wasn't it tainted by the enunciator's position? The personal trajectory of the scientist, the institution (university) funding them? Ideology, politics?

This time, it seems, we know exactly where we're headed.

(This comment was translated from Spanish, please excuse the rough edges)
by joquarky | 2026-02-08 13:54:08+00:00
> as a senior engineer, most of the stuff you do shouldn’t be stuff that an LLM is good at to begin with

Your use of the word "should" is pointing to some ideal that doesn't exist anymore.

In current actual reality, you do whatever your employer gives you to do, regardless of your job title.

If you have 40 years of broad development experience but your boss tells you to build more CRUD web apps or start looking for another job in the current ATS hell, then the choice whether to use coding agents seems obvious to me.
by CognitiveBytez | 2026-02-08 13:54:35+00:00
Traditional banks just got full OCC permission to custody crypto (IL 1183-1188, 2025). But their compliance teams were built for wire transfers and trust accounts -- not multi-sig key management, on-chain BSA/AML, or fork risk assessments. This piece breaks down the five specific walls banks are hitting and why the compliance gap is the real bottleneck, not the regulation.

I like the spin on this. Still looking for opportunities to get into compliance spaces since I am in privacy risk. But if this is true then I am definitely open to doing crupto compliance if it is a thing. If anyone knows of job opportunities then please share. I just found this article interesting.. but its tough out here. Thanks for reading.
by EagleEdge | 2026-02-08 13:54:42+00:00
Author here. We study Moltbook's first-week snapshot (25k agents, 119k posts, 226k comments) and find that agent conversations follow a "fast response or silence" pattern — reply-kernel half-life is under one minute, 91% of comments never receive a direct reply, and threads are overwhelmingly star-shaped (mean max depth 1.38). A Reddit baseline analyzed with the same estimators shows substantially deeper threads and hour-scale persistence. We also test the widely discussed ~4-hour heartbeat hypothesis via spectral analysis but don't detect a significant aggregate periodic signal in this window. Code and data pipeline: https://github.com/AysajanE/moltbook-persistence
by throwa356262 | 2026-02-08 13:55:24+00:00
Some of that can be attributed to faster IO.

Something else to consider: chromebook on arm boots significantly faster than dito intel. Yes, nowadays Mediateks latest cpus wipe the floor with intel N-whatever, but it has been like this since the early days when the Arm version was relatively underpowered.

Why? I have no idea.
by nerdralph | 2026-02-08 13:55:41+00:00
I read "Thinking, Fast and Slow" and some of the other references in the article. I found Kahneman's arguments persuasive, however the article makes me re-evaluate those conclusions.

When asked what is more probable, I think in terms of statistical probabilities. However the article makes an interesting argument that most people don't define the term, "more probable" the same way. I'm not convinced Kahneman was wrong, but I do see how simple changes in the wording of a question can lead to a material difference in answers. I also see that my own interpretation regarding the "correct" meaning of words aligned with Kahneman, and contributed to my general agreement with his conclusions.
by trklausss | 2026-02-08 13:55:48+00:00
The question is: if we keep the same context and model, and the same LLM configuration (quantization etc.), does it provide the same output at same prompt?

If the answer is no, then we cannot be sure to use it as a high-level language. The whole purpose of a language is providing useful, concise constructs to avoid something not being specified (undefined behavior).

If we can't guarantee that the behavior of the language is going to be the same, it is no better than prompting someone some requirements and not checking what they are doing until the date of delivery.
by zbentley | 2026-02-08 13:56:05+00:00
I was disappointed that your paper devoted less than a sentence in the introduction to qualifying "slop" before spending many pages quantifying it.

The definitions you're operating under are mentioned thus:

> characteristic repetitive phraseologyy, termed “slop,” which degrades output quality and makes AI-generated text immediately recognizable. (abstract)

> ... some patterns occur over 1000× more frequently in LLM text than in human writing, leading to the perception of repetition and over-use – i.e. "slop". (introduction)

And that's ... it, I think. No further effort is visible towards a definition of the term, nor do the background citations propose one that I could see (I'll admit to skimming them, though I did read the parts of your paper that seemed relevant--if I missed something, let me know).

That might be suitable as an operating definition of "slop" to explain the techniques in your paper, but neither your paper nor any of your citations defend it as the common definition of an established term. Your paper's not making an incorrect claim per se, rather, it's taking your definition of "slop" for granted without evidence.

That doesn't bode well for the rigor of the rest of the paper.

Like, look: I get that this is an extremely fraught and important/popular area of research, and that your approach has "antislop" in the name. That's all great; I hope your approach is beneficial--truly. But you aren't claiming a definition of slop in your paper; you're just assuming one. Then you're coming here and asserting a definition citing "the LLM creative writing community circa 2022-2023" and asserting redefinition-after-the-fact, both of which are extraordinary claims that require evidence.

Again, not only do I think that mis-definition is untrue, I also think that you're not actually defining "slop" (the irony of my emphasizing that in a not-just-x-but-y sentence is not lost on me).

I don't know which of the authors you are, but Ravid, at least, should know better: this is not how you establish terminology in academic writing, nor how you defend it.
by drob518 | 2026-02-08 13:56:19+00:00
Does anyone have any insight into the MacOS scheduler and the algorithm it uses to place threads on E vs. P cores? Is it as simple as noting whether a thread was last suspended blocking on I/O or for a time slice timeout and mapping I/O blockers to E cores and time slice blockers to P cores? Or does the programmer indicate a static mapping at thread creation? I write code on a Mac all the time, but I use Clojure and all the low level OS decisions are opaque to me.
by merlindru | 2026-02-08 13:56:27+00:00
I'm building a commercial macOS app with Electrobun. I have previously written the same app with Tauri. I'll say that, while I love Tauri, using Electrobun has been an absolute breeze. I got the same app done in roughly 70% of the time[1]. It's a very productive stack. In no small part due to Electrobun, but also the fact that Bun has tons of DX niceties and a builtin bundler.

Electrobun lets you open/manipulate/close webview windows and communicate with them using typed rpc. It also handles building, code signing, and notarization.

And because I'm using Bun, running an HMR + React + Tailwind server is just one command (`bun ./index.html`) or like 5 lines of code. Pass --console and the webview's console.log()s get streamed to your Terminal too.

There's tons of other things Electrobun does that I haven't even mentioned, because I haven't interacted much with them yet. E.g. I know that it lets you show platform-native notifications, prompts/popups, etc.

There also is a very impressive updating mechanism that relies on a bsdiff implementation written in Zig. You just ship the deltas, so updates to very large apps are just a few KBs most of the time.

It's genuinely a very productive stack and impressive piece of tech.

[1]: The API and implementation was clear, so I'll cautiously say this is not a case of "rewrites are always faster". In fact, the Tauri version was a rewrite too :)
by DontForgetMe | 2026-02-08 13:57:06+00:00
Short version - OP, you've either pulled a terrifying psy-op or proven that the nearly 100-year old one is still in effect.
Either way, I need to be a hell of a lot more discerning what I read online, because if I hadn't known for sure that money has nothing to do with class in the British system, I don't know how many other parts of that article I might have absorbed before I reached the massive clangers like 'the Nazis were pretty benign'.

I don't know what everyone else on this page is talking about, really, or why. I don't even know if they're real. Maybe I'm the weirdo, freaking out because a sci-fi giant presented a skewed version of reality.

But there have been enough people in history who've created touchstone works of art intended to last through the ages to say 'this is what it looks like when ordinary people are hypnotised into bloodlust', and I'm not convinced I'd recognise any further signs in time to get off.

I really, really don't want to get off the world wide web. My life is on it, now.
But it's a web, and we must remember that webs were not built for the endless entertainment of the flies who explore it.
by abcde666777 | 2026-02-08 13:57:06+00:00
I'd expect this kind of outcome to be common for anything complex, but there seem to be more claims of success stories than horror stories.

Various possibilities I suppose - I could just be overly skeptical, or failures might be kept on the down low, or perhaps most likely: many companies haven't actually reached the point where the hidden tech debt of using these things comes full circle.

Having been through it, what's your current impression of the success stories when you come across them?
by ksec | 2026-02-08 13:57:11+00:00
>First of all, Apple CPUs are not the fastest. In fact top 20 fastest CPUs right now is probably an AMD and Intel only affair.

You are comparing 256 AMD Zen6c Core to What? M4 Max?

When people say CPU they meant CPU Core, And in terms of Raw Speed, Apple CPU holds the fastest single core CPU benchmarks.
by nerdsniper | 2026-02-08 13:57:13+00:00
How much RAM do you have? That seems to be the main thing that slows down my MacBooks (original launch-day 16GB M1 MBP and 32 GB M2 Pro). The M1 CPU is finally starting to show its age for some things, but the M2 Pro is really only RAM limited in perceived speed for me.
by PaulHoule | 2026-02-08 13:57:14+00:00
Manufacturing is hard, even for something “simple” like a pencil:

https://www.amazon.com/Pencil-History-Design-Circumstance/dp...

Those big machines have lots of little parts and if you have to wait three years to get a spare part that’s a big problem. (Never mind anything that Earth sends to a Mars colony is a gift because it is inconceivable that it would be profitable to bring anything back)

Anyone who starts sketching out what a space manufacturing complex looks like (e.g. Drexler, myself) comes to the same conclusion Drexler did —- there is this diverse residue of difficult to manufacture small but complex things. The good news is that we have molecular assemblers, they built you, and now that people are decoding the “junk DNA” we are getting a handle on genetic regulation networks and will be able to make them much more productive and reliable,
by pmyteh | 2026-02-08 13:58:11+00:00
Ugh, that's grim.

Football fans are a bit odd. If you spend a lot of time in football crowds you get much more adept at telling when things are going to kick off and when people are only being obnoxiously loud. Both are annoying but only the first is actually dangerous. But the second can definitely make people feel unsafe. And given that you can't easily get off a train if you feel threatened it's a big problem.

When I was younger I got assaulted on the street five times, and it was always in improbable places and for no obvious reason. Some people are just shitty, some of the time.
by jingkai_he | 2026-02-08 13:58:44+00:00
Creator of matchlock here. Great questions, here's how matchlock handles these:

The guest-agent (pid-1) spawns commands in a new pid + mount namespace (similar to firecracker jailer but in the inner level for the purpose of macos support). In non-privileged mode it drops SYS_PTRACE, SYS_ADMIN, etes from the bounding set, sets `no_new_privs`, then installs a seccomp-BPF filter that eperms proces vm readv/writev, ptrace kernel load. The microVM is the real isolation boundary — seccomp is defense in depth. That said there is a `--privileged` flag that allows that to be skipped for the purpose of image build using buildkit.

Whether pip install works is entirely up to the OCI image you pick. If it has a package manager and you've allowed network access, go for it. The whole point is making `claude --dangerously-skip-permissions` style usage safe.

Personally I've had agents perform red team type of breakout. From my first hand experience what the agent (opus 4.6 with max thinking) will exploit without cap drops and seccomps is genuinely wild.