MurphyA/hacker-news huggingface dataset:
by simonw | 2025-08-24 00:58:47+00:00
Almost every other comment in this thread is people complaining this is too complex and over-engineered.

I had the opposite reaction when I read this post: I thought it was a very neat, clean and effective way to solve this particular problem - one that took advantage of an excellent stack of software - Caddy, Docker, uv, Plausible, Coolify - and used them all to their advantage.

Ignoring caching (which it sounds like the author is going to fix anyway, see their other comments) this is an excellent Dockerfile!

FROM ghcr.io/astral-sh/uv:debian AS build WORKDIR /src COPY . . RUN uv python install 3.13 RUN uv run --no-dev sus FROM caddy:alpine COPY Caddyfile /etc/caddy/Caddyfile COPY --from=build /src/output /srv/

8 lines is all it takes. Nice. And the author then did us the favor of writing up a detailed explanation of every one of them. I learned a few useful new trick from this, particularly around using Caddy with Plausible.

This one didn't strike me as over-engineering: I saw it as someone who has thought extremely carefully about their stack, figured out a lightweight pattern that uses each of the tools in that stack as effectively as possible and then documented their setup in the perfect amount of detail.
by richardw | 2025-08-24 00:59:16+00:00
We didn’t use the DBA’s for this but my last few teams, we got good at DB’s, performance etc. DBA’s were too general and they kept the lights on, but for real performance you should get one or two people who know what they’re doing for your applications. Or learn. I took on juniors who are now fantastic.

For the first decade I wanted nothing to do with DB’s aside from places to store data. One day I saw a few things that made a massive difference and then went wild on learning how to speed things up. It’s fantastic and because few devs know this stuff well, it becomes a superpower. You wouldn’t believe what you can squeeze out of modern SQL DB’s and hardware, without touching any kind of optimised solutions. Which I love too but that’s a different post.

Maybe ask the DBA’s a few questions and see if that triggers any interest for you. Look at query plans and how many rows are processed for a query. How many columns. What is being locked. Can you remove locks when you’re just running a query and how much does that speed things up. There are queries for all sorts of metrics, eg which indexes are huge but never used. The DB can often suggest indexes, but don’t just use add the suggestions. Use them as a starting point to reason about your own. Try get down to low millisecond queries for really frequent stuff, because it’ll make them fast and means less time locking the DB, less RAM, less temp table storage.

All my other skills have aged. Fundamental database knowledge lasts.
by sarchertech | 2025-08-24 00:59:38+00:00
>This reads like somebody who doesn't have a lot of knowledge/experience with other religious texts.

It's been a while, but I've taken a class on Dharmic religions, and another on Middle Eastern Religions (mostly Islam, Judaism, and Coptic Orthodox Church). I've also read a fair amount about most of the other largish world religions.

>ahimsa [1] - avoiding actions which cause undue suffering to any living being and that even includes animals.

Avoiding causing undue suffering is a huge step away from the commandment to actively love all people including your enemies.
by spacecadet | 2025-08-24 00:59:56+00:00
Many years ago one of our cats got out, she was gone for 3 weeks, we tracked her down using 6 game cameras. Long story short, I have 200,000 images of "wild life"... Last year I used a VLM to catalog all of the images by generating detailed descriptions. I was able to find images of our cat in 3 searches, the same images we used to identify her originally, which took hours each day combing through thousands of images.
by crooked-v | 2025-08-24 01:00:28+00:00
Here's a 2019 article that took a two-minute search to find: https://www.newsweek.com/colorado-schools-issuing-buckets-ki...

> Parents and teachers in a Colorado school district were surprised by some new additions to the list of necessary back-to-school supplies—including kitty litter, buckets and trash bags.

> The products are part of Jefferson County's "Emergency Go Bucket," a way for students to relieve themselves in the event of a prolonged lockdown because of an active shooter.
by SpecialistK | 2025-08-24 01:00:34+00:00
It's a cool concept, but let's be honest: it's what the author thinks are good regulations. And it only ever can be, because policy is subjective.

I happen to agree with almost all of them, and most doubt is the devil in the details. The efficiency one, for example - if efficiency in an appliance comes at the expense of longevity (ie, it uses less materials or R&D is put into power use over anything else) then that may be a net negative. And the GDPR, a great regulation for customer data, has had the side effect of putting cookie law banners everywhere which makes the web more frustrating.

And I hate to say it, because it's my own weird ick, but I will forgo eating if the only utensils are wood. Simply cannot handle the feeling of it against my teeth and tongue. Thank God there are newer compostable single use utensils becoming common.
by onetimeusename | 2025-08-24 01:01:00+00:00
I don't think that's the point of legacy admissions. I think it's purpose is exactly what the grandparent said which is to cultivate a network of people.

The problem with saying legacy preference is to take the place of higher performing non-legacy candidates is that legacy admits generally perform above average at least at Harvard although it's probably true elsewhere. See here[1]: The average SAT score among legacy students was 1543, while it was 1515 for non-legacy students.

So it could still be for replacing higher performing non-legacies meaning Harvard targeted and rejected a bunch of people with even higher SAT scores than the legacies but I don't find that very convincing.

[1] (https://features.thecrimson.com/2023/freshman-survey/academi...)
by ortusdux | 2025-08-24 01:01:00+00:00
I looked into line cameras for a project. I think their main application is in quality control of food on conveyer belts. There are plenty of automated sorting systems that can become a bottleneck. One of the units I speced out could record an 8k pixel line at up to 40kfps.

https://youtu.be/E_I9kxHEYYM
by glitchc | 2025-08-24 01:01:16+00:00
We don't know if AGI is even possible outside of a biological construct yet. This is key. Can we land on AGI without some clear indication of possibility (aka Chappie style)? Possibly, but the likelihood is low. Quite low. It's essentially groping in the dark.

A good contrast is quantum computing. We know that's possible, even feasible, and now are trying to overcome the engineering hurdles. And people still think that's vaporware.
by didibus | 2025-08-24 01:03:58+00:00
The full interview is all in the link. But specifically the bad news was:

> But the bad news is, when you're interrupted, you don't immediately go back to the task you were doing before you were interrupted. There are about two intervening tasks before you go back to your original task, so it takes more effort to reorient back to the original task. Also, interruptions change the physical environment. For example, someone has asked you for information and you have opened new windows on your desktop, or people have given you papers that are now arranged on your desk. So often the physical layout of your environment has changed, and it's harder to reconstruct where you were. So there's a cognitive cost to an interruption.
by dinobones | 2025-08-24 01:04:14+00:00
Nah,this sounds like a modern remix of Japan’s Fifth Generation Computing project. They thought that by building large databases and with Prolog they would bring upon an AI renaissance.

Just hand waving some “distributed architecture” and trying to duct tape modules together won’t get us any closer to AGI.

The building blocks themselves, the foundation, has to be much better.

Arguably the only building block that LLMs have contributed is that we have better user intent understanding now; a computer can just read text and extract intent from it much better than before. But besides that, the reasoning/search/“memory” are the same building blocks of old, they look very similar to techniques of the past, and that’s because they’re limited by information theory / computer science, not by today’s hardware or systems.
by levitate | 2025-08-24 01:04:43+00:00
"AGI needs to update beliefs when contradicted by new evidence" is a great idea, however, the article's approach of building better memory databases (basically fancier RAG) doesn't seem enable this. Beliefs and facts are built into LLMs at a very low layer during training. I wonder how they think they can force an LLM to pull from the memory bank instead of the training data.
by therobots927 | 2025-08-24 01:04:43+00:00
The problem is that if it's an engineering problem then further advancement will rely on step function discoveries like the transformer. There's no telling when that next breakthrough will come or how many will be needed to achieve AGI.

In the meantime I guess all the AI companies will just keep burning compute to get marginal improvements. Sounds like a solid plan! The craziest thing about all of this is that ML researchers should know better!! Anyone with extensive experience training models small or large knows that additional training data offers asymptotic improvements.
by potato3732842 | 2025-08-24 01:04:44+00:00
>Video emerging from the scene shows the helicopters slowly approaching a landing zone.

Bringing police tactics to an infantry fight will get you dead every time. Helicopters have always been sitting ducks dependent largely upon tactics to survive in even the most slightly unfriendly airspace.

It really is a marvel of modern technology that you can have a decent shot at defending yourself from a helicopter with something that costs under $1k and fits in a briefcase.
by TimorousBestie | 2025-08-24 01:05:50+00:00
> The US President, likely motivated by a desire to own the libs and punch environmentalists in the face, plans to pour $4T into nuclear, making him an unintended climate change warrior, some say the greatest ever.

All that cash and he’s only asking for 5 GW of improvements to existing reactors and ten “new large reactors.” So what, 20 GW total? By 2030.

That doesn’t come close to satisfying an AI power consumption estimate of 68 GW by 2027 and 327 GW by 2030. [1]

[1] https://www.rand.org/pubs/research_reports/RRA3572-1.html
by qwerpy | 2025-08-24 01:06:13+00:00
Same. For years now I've vaguely bucketed leisure activities into "empty" and "wholesome" in the same vein as caloric intake. Empty: mindlessly following a YouTube/Instagram/Tiktok algorithmic feed, modern games that are more slot machines than games, drinking alone. Wholesome variants: intentionally reading/watching high quality content, playing offline or 2-4 player coop games, socializing with friends in person.

Knowing is just the first part of the war though. If you don't constantly stay mindful of what kind leisure is taking up your time, the vastly more addictive nature of empty calorie leisure will win. And how many people even bother trying to resist, let alone win most of their battles?
by DaSHacka | 2025-08-24 01:06:16+00:00
Only criminals need to modify their car.

Now accept our integrated telemetry gathering that reports directly to LexisNexis so insurance companies can raise your rates [0].

Surely you understand, think of the children!

[0] https://www.nytimes.com/2024/03/11/technology/carmakers-driv...
by bicx | 2025-08-24 01:06:39+00:00
My wife and I are unable to have children due to health reasons, and we decided not to adopt after years of hardship. Now, we’re in a better place, and I’m nearing my 40s. My brother has 2 young kids, and my parents help take care of the kids during the week. They are literal neighbors and walk back and forth between their houses.

Meanwhile, my wife and I have moved from our hometown, lived in SF for a while (focusing on career), sold normal possessions to live and travel in an RV for a year, and now we live on a gulf coast island. It’s been a great adventure these past years, but there is a deep feeling that there isn’t much of a purpose in what we do.

Raising kids seems to answer this for some, but other parents seem to become genuinely disgusted with it over time (unfortunately for the kids). From an evolutionary perspective, a feeling of purpose from raising children makes total sense. But, that doesn’t mean I must lean into all evolutionarily baked-in tendencies as a form of true meaning.

I think the hard truth is that if we want meaning, we have to be honest that there is no unquestionable source of meaning in life. That also goes counter to the idea that we are individually special or have a destiny, which is also a hard pill to swallow for many (particularly in the Western world). However, it does open up our lives as a canvas on which we can paint our own vision of meaning and purpose.
by zmmmmm | 2025-08-24 01:07:08+00:00
I had to dig through to see the details of what database was really in play here, and sure enough, it's a wrapper around a key-value store (RocksDB). So while I'll confess I know little about RocksDB it does sound an awful lot like they threw out a mature relational database engine with built in optimization and now are in the process of paying the price for that by manually optimizing each query (against a key-value store no less, which probably fundamentally limits what optimizations can be done in any general way).

Would be curious if any RocksDB knowledgeable people have a different analysis.
by FridayoLeary | 2025-08-24 01:07:35+00:00
I was always mystified about the value of Tesla stocks. The pe is still absurdly high and the market cap is bigger then probably all the big manufacturers combined. It's obvious that people are investing in musk as a person. But there has to be a correction sooner or later. Tesla has value as a car company, but their first mover advantage is dwindling. Add to that musks politics and it's not surprising that the executives are reading the writing on the wall.
by LarsKrimi | 2025-08-24 01:08:08+00:00
Hmm I didn't hear about this. Would mandating daily ketamine use for my cofounders improve our chances for success?

I believe most LLM's should at least be able to produce the same level of paranoid, *-pilled populist nonsense as in this investor letter. But it's just coming up with the ideas that's hard
by andy99 | 2025-08-24 01:08:09+00:00
If you believe the bitter lesson, all the handwavy "engineering" is better done with more data. Someone likely would have written the same thing as this 8 years ago about what it would take to get current LLM performance.

So I don't buy the engineering angle, I also don't think LLMs will scale up to AGI as imagined by Asimov or any of the usual sci-fi tropes. There is something more fundamental missing, as in missing science, not missing engineering.
by ACCount37 | 2025-08-24 01:08:58+00:00
I do not think that "climate change accelerationism" is a defensible position.

We are fighting climate change not to feel good about ourselves, but to prevent those higher-degree impacts from happening in the first place.

What's worse is that climate change has a considerable momentum. If you resolve to hit +2C before taking climate action, then even stopping all GHG emissions instantly would leave you with another ~+1C that would trickle in over time. In reality, there is no fucking way to obliterate all GHG emissions overnight.

Geoengineering solves a lot, but it doesn't delete all of the problems outright. Unless you commit to some truly unhinged methods. Which might not be the worst idea, really - but then every problem we have with making geoengineering happen apples at least tenfold.
by Waterluvian | 2025-08-24 01:11:34+00:00
Almost all my employers and managers have been very understanding about this. But one of my favourites was a manager earlier in my career who picked up that I was anxious about my work hours and ethic. To paraphrase, he said, “the company isn’t paying you to solve problems M-F 9-5. It’s paying you for when you solve them in the shower or on a walk or when you’re putting your kid to bed, and then come into work and implement the solution.”

I’ve thought about this for years as I tune my work life balance. I’ve never felt like I’m wrongly bringing work home with me that way. It’s always felt like an incredible optimization where my job gives me these puzzles I get to carry with me and work on when I’m bored or my ADHD addled brain screams for stimulation.
by airstrike | 2025-08-24 01:13:35+00:00
it is objectively a potential reason in the universe of reasons, but you're 100% free to believe whatever you want, even if it's wrong

and the fact that multiple people upvoted my comment at a minimum suggests others also believe it to be a possible explanation

i have no idea why you've chosen this particular hill to die on, when neither of us stands to profit from this protracted exchange
by throwaway346434 | 2025-08-24 01:13:43+00:00
From: https://ics.uci.edu/~gmark/CHI2005.pdf (sample size: 1x company, n=24, lots of limitations discussed at end of paper)

"When people did resume work on the same day, it took an average length of time of 25 min. 26 sec (sd=54 min. 48 sec.). This may seem like a relatively short amount of time, but it is also important to consider that before resuming work, our informants worked in an average of 2.26 (sd=2.79) working spheres. Thus, people’s attention was directed to multiple other topics before resuming work. This was reported by informants as being very detrimental. In some cases, the physical or desktop environment is restructured, which makes it more difficult to rely on cues to reorient one to their interrupted task. For example, a blinking cursor at the end of the last typed word can enable one to immediately reorient to that document, whereas if other windows have been opened, it can be hard to remember even which document had been worked on."

And "We found a trend that showed more externally interrupted working spheres are resumed on the same day (53.3%) compared to internally interrupted working spheres (47.6%), X2 (1)=2.97, p<.09. Externally interrupted working spheres are resumed on the average in a shorter time (22 min. 37 sec., sd=53 min. 52 sec.) than internally interrupted working spheres, (29 min. 1 sec., sd=55 min. 43 sec.), t(987)=1.92, p<.055."

So no, it does not say 23 minutes and 15 seconds in that paper.

But to say: "the paper never goes into details regarding the recovery time between finishing the interruption and getting back to the original task." is flat out incomplete, because they are reading the followup paper to the original work in isolation; and haven't considered that a number of reports summarized the findings of that (22 m 37s) as "about 23 minutes". The way it is written implies the research is all wrong, rather than more accurately stating "I can't find the exact source of a quote but it's broadly 22-23 minutes, not 23m15s afaict".

There is also some irony in "ctrl+f", "23" being explained as the methodology for review on the topic of attention span for complex tasks...
by tredre3 | 2025-08-24 01:15:47+00:00
> For every 1KiB page you have, you're wasting 15KiB of memory.

Applications do not allocate memory through the kernel, though. There's a layer between the application code and the kernel, usually the libc or equivalent, that takes the page and fills it with smaller allocations. And most allocators out there usually request pretty big chunks at a time too, measured in megabytes/hundreds of pages.

So what you are saying might be technically true if you were to dispatch all mallocs to the kernel, it is not actually true in the real world.
by LargoLasskhyfv | 2025-08-24 01:16:21+00:00
Pfft.

Space Simon - BUSCHKRAFT RAVE - Industrial Techno - Psychedelic Trance

https://www.youtube.com/watch?v=wjBY9mvNT8M 59min21secs

Wir Feiern im Wald. Pack das Fleisch jetzt aus. Direkt auf den Grill! Feuer! Fleisch! Buschkraft!

In der schönen Natur, im Wald, da ist die Liebe!

Wir Ficken im Wald.

Gangbang im Gebüsch.

Ficken.

Der Zunder brennt! Das Feuer knistert! Rauch steigt auf, und wir sind drauf!

Feuer, Feuer, brenn!

Der Zunder brennt, das Feuer knistert. Rauch steigt auf, und wir sind drauf.

Feuer, Feuer, brenn!

Der Zunder brennt, das Feuer knistert. Rauch steigt auf. Und wir sind drauf.

Wir saufen im Wald.

Saufen...

Saufen...

Direkt aus der Flasche...

Saufen...

Hey Alter! Komm und bring mir mal die Wurst rüber.

Eine schöne, dicke Wurst!

Heiss und knackig, in meinen Mund!

Eine dicke, fette, lange, geile...

...deine Wurst.

Eine schöne, dicke Wurst.

Ganz heiss, und Tropfen fallen.

AAAA JAAA!

ICH - WILL - JETZT - MEINE - WURST!

Spritzend!

Tropfend!

Heiss!

Eine schöne, dicke Wurst.

Ganz heiss, und tropfend fein.

Wir buschkraften und ballern...

Tatschen...

BAALLEERN!

Tatschen...

BAALLEERN!

Tatschen und ballern...

Buschkraft und Ballern.

Klatschen.

Wir sind am Buschkraften und Ballern.

Feuer, Glut, Stahl...

Der Wald sieht Alles.

...blending over into something more oriental...

A little repetitive at times, but was funny nonetheless. Not as annoying as much other AI-stuff I've been stumbling over.

Swiss-made, apparently.
by krackers | 2025-08-24 01:16:59+00:00
This article seemed really basic, no insight other than "it learns the high dimensional manifold on which cat images lie, thus separating cats from non-cats" (not that simple explanations are bad, but Quanta articles seem to be getting more watered down over time).

The real question is whether we can get some insight as to how exactly it's able to do this. For convolution neural networks it turns out that you can isolate and study the behavior of individual circuits and try to understand what "traditional image processing" function they perform, and that gives some decent intuition: https://distill.pub/2020/circuits/ - CNNs become less mysterious when you break them down as being decomposed into "edge detectors, curve detectors, shape classifiers, etc."

For LLMs it's a bit harder, but anthropic did some research in this vein.
by nine_k | 2025-08-24 01:17:02+00:00
When Toyota, Honda, Mitsubishi, Hyundai, KIA, etc came, and Detroit turned into a zombie city, did it help?

Well, I can admit that Ford learned from Honda quite a bit, which could be readily seen in their Focus line. Is it their fault that consumers stubbornly want the likes of F-150 or Chevy Suburban, which are not even proper cars?
by bko | 2025-08-24 01:17:04+00:00
> I think the hard truth is that if we want meaning, we have to be honest that there is no unquestionable source of meaning in life.

I agree, but children are one possible source of meaning in life. I haven't found a compelling one for me personally besides that. I guess for some people it could be discovery. If you're on the frontier of some field or science that could have a big impact, perhaps that can give you meaning. Perhaps Nikola Tesla never felt the urge to marry or have children. But for us mere mortals that becomes harder. And today's map doesn't have many unchartered areas. Nearly every problem accessible to us is impossible or trivial.

I hope you find meaning and purpose in your life without kids. But you're also relatively young. I feel like my passion and interests wane over time. This holds for most people I know as well. And other fun things like adventure and living out of an RV becomes harder as well.