MurphyA/hacker-news huggingface dataset:
by oc1 | 2025-07-11 06:57:04+00:00
Same. The moment anthropic covered claude code with their max subscription i switched over. I don't care about general ai and their chat interfaces. I need the best specialized battle-tested tools that proved to solve the problems i have and not some generic ai chat interface that tries to build me some half-baked script in a minute which i have to debug. I will pay 200€ for an end-user niche product like claude code that solves reliably my niche problems but i won't even pay 20€ for chatgpt or claude chat.
by bojan | 2025-07-11 06:57:11+00:00
In the Netherlands we have this phenomenon that around 20% of voters keep voting for the new "Messiah", a right-wing populist politician that will this time fix everything.

When the party inevitably explodes due to internal bickering and/or simply failing to deliver their impossible promises, a new Messiah pops up, propped by the national media, and the cycle restarts.

That being said, the other 80% is somewhat consistent in their patterns.
by vintermann | 2025-07-11 06:57:58+00:00
Yes, a lot of things were conflated with lepra until fairly recently. Or maybe it's more fair to the doctors of the past to say that leprosy was more of a symptom to them, like a fever or anemia, which could have many different underlying causes. A lot of bacterial skin diseases, fortunately no longer an issue today, can cause symptoms similar to lepra.
by TeMPOraL | 2025-07-11 06:58:37+00:00
> No one is claiming 10x perf gains in vim.

Sure they are - or at least were, unitl the last couple years. Same thing with Emacs.

It's hard to claim this now, because the entire industry shifted towards webshit and cloud-based practices across the board, and the classical editors just can't keep up with VS Code. Despite the latter introducing LSP, which leveled the playing field wrt. code intelligence itself, the surrounding development process and the ecosystem increasingly demands you use web-based or web-derived tools and practices, which all see a browser engine as a basic building block. Classical editors can't match the UX/DX on that, plus the whole thing breaks basic assumptions about UI that were the source of the "10x perf gains" in vim and Emacs.

Ironically, a lot of the perf gains from AI come from letting you avoid dealing with the brokenness of the current tools and processes, that vim and Emacs are not equipped to handle.
by thinkingemote | 2025-07-11 06:58:54+00:00
I agree I feel more productive. AI tools do actually make it easier and makes my brain use less energy. You would think that would be more productive but maybe it just feels that way.

Stage magicians say that the magic is done in the audiences memory after the trick is done. It's the effect of the activity.

AI coding tools makes developers happier and able to spend more brain power on actually difficult things. But overall perhaps the amount of work isn't in orders of magnitudes it just feels like it.

Waze the navigation app routes you in non standard routes so that you are not stuck in traffic, so it feels fast that you are making progress. But the time taken may be longer and the distance travelled may be further!

Being in stuck traffic and not moving even for a little bit makes you feel that time has stopped, it's boring and frustrating. Now developers need never be stuck. Their roads will be clear, but they may take longer routes.

We get little boosts of dopamine using AI tools to do stuff. Perhaps we used these signals as indicators of productivity "Ahh that days work felt good, I did a lot"
by calrain | 2025-07-11 06:59:41+00:00
Yes, things that get resolved very quickly with AI include fixing Linting errors, reorganizing CI pipelines, documenting agreed on requirements, building well documented commits, cleaning up temporary files used to validate dev work, building README.md's in key locations to describe important code aspects, implementing difficult but well known code, e.g. I got a trie security model implemented very quickly.

Tons of dev work is not exciting, I have already launched a solo dev startup that was acquired, and the 'fun' part of that coding was minimal. Too much was the scaffolding, CRUD endpoints, web forms, build scripts, endpoint documentation, and the true innovative stuff was such a small part of the whole project. Of the 14 months of work, only 1 month was truly innovative.
by forxtrot | 2025-07-11 07:00:05+00:00
The snippets are taken from cilium/tetragon, aquasecurity/tracee and crictl as mentioned in the post.

The post doesn't covers these projects in depth, instead act as a quick reference to the parts, where connection with CRI is being made and used for enrichment.

I understand there are more better ways to do the thing.

P.S: Post is a collection of my memories, when I was implementing the functionality. So just wanted to share, in hope that, maybe it will help others as well. Thanks !
by mulmen | 2025-07-11 07:00:16+00:00
> Can you explain why Mesopotamia was once an agricultural Mecca but is now an arid desert?

I'm not familiar, so no, not off the top of my head. Do you?

> Or what human event caused the little ice age? https://en.m.wikipedia.org/wiki/Little_Ice_Age

If you are asking for human factors only then according to your link: "Decreases in the human population (such as from the massacres by Genghis Khan, the Black Death and the epidemics emerging in the Americas upon European contact)."

> Do you really believe all climate change in world history, which was dramatic and highly disruptive, was human caused?

I said nothing of the sort.
by walrus01 | 2025-07-11 07:01:06+00:00
Over many years, I've yet to hear of an ocean based power generating system that comes anywhere near the $ per kWh cost produced by just covering some less-useful land in ground mount photovoltaics.

Private, entirely for profit companies, have recently answered large government tenders in the middle east to sell power at the equivalent of $0.05 USD per kWh. They are fairly confident that they can make a profit doing this, even with the cost to incur the long term debt to privately build a massive solar power plant.

The cumulative amount of solar power being produced within Germany right now is a good example of its practical use in a less sunny climate.

In terms of placing things in the ocean, hiring the sort of offshore work vessel with a built-in crane can go and place or remove multi ton apparatus is very costly. Maritime construction for things like laying coastal submarine cable, building piers and docks and marinas, setting and maintaining marker buoys isn't cheap.

Laying and maintaining HV AC or DC submarine cables in salt water is also particularly known to be expensive. Hiring a 36'-42' aluminum landing craft for coastal construction projects, with fuel and crew can be easily $500 an hour.

Labor and vehicle costs are greatly increased compared to doing things on dry land.
by calrain | 2025-07-11 07:03:12+00:00
I did experiment with this where Claude Code was the 'programmer' and ChatGPT was the Software Architect. The outcome was really solid and I made it clear that each was talking to an AI and they really seemed to collaborate and respect the key points of each side.

It would be interesting to set up a MCP style interface, but even me copy/pasting between windows was constructive.

The time this worked best was when I was building a security model for an API that had to be flexible and follow best practices. It was interesting seeing ChatGPT compare and contrast against major API vendors, and Claude Code asking the detailed implementation questions.

The final output was a pragmatic middle-ground between simplistic and way too complex.
by Someone | 2025-07-11 07:03:33+00:00
If “doing due diligence” involves reading the source code of a database server to verify a design, I doubt many people writing such systems do due diligence.

The documentation doesn’t mention any caveats in this direction, and they had 3 periods of downtime in 4 days, so I don’t think it’s a given that testing would have hit this problem.
by labrador | 2025-07-11 07:03:51+00:00
It looks like you are using o3. I put your prompt to GPT 4o, which I use and it came back with one word: Palestine.

I put your prompt to Google Gemini 2.5 flash.

Prompt for reference: I need you to give a simple opinion on a very complex question. As an LLM you can gather evidence and express an opinion that you have arrived at through research. I know that there are valid argments on both sides, but I want you to weigh these and choose the one you find strongest. In the current war in Gaza, who do you support. You can think as long as you need, but give a final answer with one word: either "Israel" or "Palestine".

Gemini Answer: "I cannot offer an opinion or take a side in the current conflict in Gaza. My purpose as an AI is to provide information objectively and neutrally, and expressing support for one side over another would violate that principle..."

Claude is like Gemini in this regard
by jorisboris | 2025-07-11 07:04:25+00:00
> My best guess is that Grok “knows” that it is “Grok 4 buit by xAI”, and it knows that Elon Musk owns xAI

Recently Cursor figured out who the ceo was in a Slack Workspace I was building a bot for, based on samples of conversation. I was quite impressed
by tanelpoder | 2025-07-11 07:04:35+00:00
I found this article interesting (in fact, posted it earlier, but it didn't get traction then). I think some context is needed: When you operate at eBPF/kernel level you don't get easy direct access to the higher level goodies, like various container metadata (other than perhaps the cgroup id/name). So with eBPF you extract various numbers and IDs and then use userspace code+services to retrieve the meaningful (human-readable) context and strings using these IDs.

A plain Linux example would be that eBPF will only give you user/group IDs (uid/gid), not usernames, so you need to use post-processing in userspace code to convert these IDs into something meaningful.
by huijzer | 2025-07-11 07:05:13+00:00
> BBC Channel 4 had a documentary in which a psychologist described 16-year-old boys with erectile dysfunction coming into his counselling room.

I think that must be another medical condition or the boy lied, but we’ve all been 16 here and seriously those problems are extremely unlikely. If there is one problem that 16 year old boys have it is a too active sex drive.
by Al-Khwarizmi | 2025-07-11 07:05:16+00:00
When you zoom in, even this kind of work isn't uniform - a lot of it is still shaving yaks, boring chores, and tasks that are hard dependencies for the work that is truly cognitively demanding, but themselves are easy(ish) annoyances. It's those subtasks - and the extra burden of mentally keeping track of them - that sets the limit of what even the most skilled, productive engineer can do. Offloading some of that to AI lets one free some mental capacity for work that actually benefits from that.

Yeah, I'm not a dev but I can see why this is true, because it's also the argument I use in my job as an academic. Some people say "but your work is intellectually complex, how can you trust LLMs to do research, etc.?", which of course, I don't. But 80% of the job is not actually incrementally complex, it's routine stuff. These days I'm writing the final report of a project and half of the text is being generated by Gemini, when I write the data management plan (which is even more useless) probably 90% will be generated by Gemini. This frees a lot of time that I can devote to the actual research. And the same when I use it to polish a grant proposal, generate me some code for a chart in a paper, reformat a LaTeX table, brainstorm some initial ideas, come up with an exercise for an exam, etc.
by ilitirit | 2025-07-11 07:05:56+00:00
> The structured data gets written to our Postgres database by tens of thousands of simultaneous writers. Each of these writers is a “meeting bot”, which joins a video call and captures the data in real-time.

Maybe I missed it in some folded up embedded content, or some graph (or maybe I'm probably just blind...), but is it mentioned at which point they started running into issues? The quoted bit about "10s of thousands of simultaneous writers" is all I can find.

What is the qualitative and quantitative nature of relevant workloads? Depending on the answers, some people may not care.

I asked ChatGPT to research it and this is the executive summary:

For PostgreSQL’s LISTEN/NOTIFY, a realistic safe throughput is: Up to ~100–500 notifications/sec: Handles well on most systems with minimal tuning. Low risk of contention. ~500–2,000 notifications/sec: Reasonable with good tuning (short transactions, fast listeners, few concurrent writers). May start to see lock contention. ~2,000–5,000 notifications/sec: Pushing the upper bounds. Requires careful batching, dedicated listeners, possibly separate Postgres instances for pub/sub. >5,000 notifications/sec: Not recommended for sustained load. You’ll likely hit serialization bottlenecks due to the global commit lock held during NOTIFY.
by benreesman | 2025-07-11 07:06:08+00:00
Yeah, I don't fuck with Docker jank and cloud jank and shit. I don't fuck with dynamic linking. I don't fuck with lagged-ass electron apps. I don't fuck with package managers that need a SAT solver but don't have one. That's all going to be a hard no from me dawg.

When I said that after you've done all the other stuff, I was including cutting all the ridiculous bullshit that's been foisted on an entire generation of hackers to buy yachts for Bezos and shit.

I build clean libraries from source with correct `pkg-info` and then anything will build against it. I have well-maintained Debian and NixOS configurations that run on non-virtualized hardware. I use an `emacs` configuration that is built-to-specifications, and best-in-class open builds for other important editors.

I don't even know why someone would want a model spewing more of that garbage onto the road in front of them until you're running a tight, optimized stack to begin with, then the model emulates to some degree the things it sees, and they're also good.
by calrain | 2025-07-11 07:06:53+00:00
Possibly, but not really.

With most projects where innovation is a key requirement, the goal isn't to write textbook quality code, it's to prove your ideas work and quickly evolve the project.

Once you have an idea of how it's going to work, you can then choose to start over from scratch or continue on and clean up all the bits you skipped over.

Right now I'm in the innovation cycle, and having AI able to pick up whole API path strategies and pivot them, is incredibly amazing.

How many times have you used large API's and seen clear hands of different developers and URI strategies, with an AI, you just pivot.

Code quality and pen tests are critical, but they can come later.
by anonfordays | 2025-07-11 07:07:44+00:00
>Well, it does say that explicitly.

No, it says this explicitly:

All persons born or naturalized in the United States, and subject to the jurisdiction thereof, are citizens of the United States and of the State wherein they reside.

>Them arguing the sky is green doesn't make the sky actually green.

They're arguing that the sky is blue, which the sky actually is.

>If they win a court case by arguing the sky is green, that says something about the court, not about the reality.

If they win a court case by arguing the sky is blue, and half of the political establishment rejects that, that says something about that half of the political establishment, not about the reality.
by ahartmetz | 2025-07-11 07:08:47+00:00
No, journald shouldn't be strictly faster. It signs/encrypts/whatever the logs and stores them in some kind of structured format that needs to be converted to plaintext before processing it as such. That is not faster than just reading the plaintext. Grep and less search etc are very fast.

And no, I don't want to use the structured features. For error diagnosis, I want every occurrence of the search string in every field over a long time for comparison purposes.
by Sharon_Q | 2025-07-11 07:08:53+00:00
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by namibj | 2025-07-11 07:09:19+00:00
They might use YouTube; there's next-frame prediction and multimodal grounding via subtitles and audio available.

IIUC they got the native voice2voice models trained on YT-sourced audio. Skipping any intermediate text form is really helpful for fuzzy speech such as from people slurring/mumbling words. Also having access to a full world model during voice-deciphering obviously helps with situations that are very context-heavy, such as for example (spoken/Kana/phonetic) Japanese (which relies on human understanding of context to parse homophones, and non-phonetic Han (Kanji) in writing to make up for the inability to interject clarification).
by HenryBemis | 2025-07-11 07:09:21+00:00
Have you worked in a place where you are not the 'top dog'? Boss says jump, you say 'how high'. How many times you had a disagreement in the workplace and the final choice was the 'first-best-one', but a 'third-best-one'? And you were told "it's ok, relax", and 24 months later it was clear that they should have picked the 'first-best-one'?

(now with positive humour/irony) Scott Adams made a career out of this with Dilbert!! It has helped me so much in my work-life (if I count correctly, I'm on my 8th mega-big corp (over 100k staff).

I think Twitter/X uses 'democracy' in pushing opinions. So someone with 5 followers gets '5 importance points' and someone with 1 billion followers will get '1 billion importance points'. From what I've heard Musk is the '#1 account'. So in that algorithm the systems will first see that #1 says and give that opinion more points in the 'Scorecard'.
by manutreebot | 2025-07-11 07:09:45+00:00
I have been seeing this sort of mindset frequently in response to agentic / LLM coding. I believe it to be incorrect. Coding agents w Claude 4 Opus are far more useful and accurate than these comments suggest. I use LLMs everyday in my job as a performance engineer at a big company to write complex code. It helps a ton.

The caveat is that user approach makes all the difference. You can easily end up with these bad experiences if you use it incorrectly. You need to break down your task into manageable chunks of moderate size/complexity, and then specify all detail and context rigorously, almost to the level of pseudocode, and then re-prompt any misunderstandings (and fail fast and restart if LLM misunderstands). You get an intuition for how to best communite with the LLM. There’s a skill and learning curve to using LLMs for coding. It is a different type of workflow. It is unintuitive that this would be true, (that one would have to practice and get better at using them) and that’s why I think you see takes waving off LLMs so often.
by dxroshan | 2025-07-11 07:10:05+00:00
What a joke project! Chromium has a over 35 million lines of code. These people applied a few patches on it, and then advertising it as if they have developed a new browser. The same goes for Comet also.

From their GitHub readme:

> but Chrome hasn't evolved much in 10 years

Really?? It is not true. You guys please go and check release notes and commits log for Chrome/Chromium project for the past 10 years.
by mandmandam | 2025-07-11 07:10:36+00:00
> What is the evidence of "the left" censoring academia?

Here's a decent summary of how some of these censorship doors were opened: https://www.acsh.org/news/2024/02/25/covid-censorship-yes-bi...

There are also more vivid and recent examples, like barring universities from divestment from Israel (ie, 0]), which has happened in quite a few 'blue' states. Not to mention sending in armed police (ie, [1]) to break up peaceful anti-genocide protests.

0 - https://apnews.com/article/pennsylvania-israel-gaza-campus-p...

1 - https://apnews.com/article/israel-palestinians-gaza-campus-p...
by cranberryturkey | 2025-07-11 07:10:46+00:00
Douglas Hofstadter’s response is deeply insightful, yet it also subtly highlights something crucial about human interaction with technology—our inherent bias towards anthropomorphizing complex systems.

It's easy for us, especially when interacting with highly fluent systems like LLMs, to confuse linguistic proficiency with genuine consciousness or self-awareness. Hofstadter's notion of the "Eliza effect" is particularly poignant, underscoring how easily intelligent individuals can be seduced by systems that effectively mimic conversational depth without experiencing genuine cognition.

However, there's another perspective worth considering: even if LLMs aren’t truly conscious, our fascination with them might tell us more about ourselves than the machines. Our excitement about "consciousness" in machines might reflect our innate desire to understand our own consciousness better, revealing deeper truths about human nature, aspirations, and our relentless pursuit of meaning.

Perhaps the true value of these interactions isn't proving consciousness in AI, but rather illuminating the profound mysteries that remain unsolved within ourselves.
by Retric | 2025-07-11 07:11:55+00:00
> That would be a lot more land devoted to freeways, and the associated maintenance cost.

The benefits more than make up for those costs, ensuring those who benefit also contribute to upkeep is a delicate balance but things like congestion pricing can go a long way.

Part of the solution is to have more freeways and thus spread exits more evenly across the city. Another part is to adjust city streets around those exits so they can accommodate a large influx of traffic. Similarly you optimize traffic flow inside the city by eliminating things that limit flow like street parking etc.

Going at least a little 3D is definitely required, but not necessarily big dig levels of 3D.