MurphyA/hacker-news huggingface dataset:
by ezekiel68 | 2025-06-14 15:35:40+00:00
I disagree with the other reply indicating something like this should not be used in production. For most of the history of practical disk IO, it was observed and assumed that disk reads would be relatively much faster than disk writes. It turns out that this assumption was based on other assumptions, such as that most reading and writing would be handled as "random IO" where a physical disk head accessing an actual spinning disk might need to move around at any given time to read or to update some data.

Riak (the inspiration for this project) and other projects came out at a time when software engineers were exploring how to make disk writes fast and potentially even faster than reads for practical applications. Some tradeoffs to achieve this goal could be enforcing all writes to be sequential ("log-structured" in riak, kafka, and cassandra parlance) and to embrace the model of "eventual consistency".

Eventual consistency is similar to how orders are processed at a cafe or fast-food restaurant. The cashier takes the order and passes it on to the barista or chef - we'll just say "kitchen". The kitchen might not know your order at that moment but it's right there nearby (equivalent in our case: in a RAM buffer ready for disk write). Once the kitchen has finished other orders ahead of yours (the sync interval is reached), it makes your order and delivers it to the counter (the data gets actually written to disk -- "committed" in DB talk).

The key point in this analogy is that the cashier station (system front end UI) doesn't wait around until your order gets made before taking other orders. It assumes all is well and your order will be served by the kitchen "soon enough".

When might these tradeoffs make sense for production systems? Answer: not all data is created equal. For example, if your system stores a steady stream of GPS coordinates from pakage delivery trucks so customers can know when a truck is near their house, it doesn't actually matter if one or two of the coordinates is not immediately available (or even gets lost). The same can go for backend system telemetry, showing CPU or RAM utilization. The trend is the main thing and it's not actually important in a particular real-time instant whether the dashboard chart shows the last 3 readings (since they have yet to be finally written to disk). In cases like these, "ACID" (traditional db term) guarantees not only are not requried, they get in the way of proper system design and implementation.
by Barrin92 | 2025-06-14 15:36:01+00:00
Is this one of those AI generated theses people try to submit as a joke? In Gen-Z slang this time?

". Adaptive systems are abstraction layers are polycomputers, and a policy simultaneously completes more than one task. When the environment changes state, a subset of tasks are completed. This is the cosmic ought from which goal-directed behaviour emerges (e.g. natural selection). “Simp-maxing” systems prefer simpler policies, and “w-maxing” systems choose weaker constraints on possible worlds[...]W-maxing generalises at 110 − 500% the rate of simp-maxing. I formalise how systems delegate adaptation down their stacks."

I skimmed through it but the entire thing is just gibberish:

"In biological systems that can support bioelectric signalling, cancer occurs when cells become disconnected from that informational structure. Bioelectricity can be seen as cognitive glue."

Every chapter title is a meme reference, no offense but how is this a Computer Science doctoral thesis?
by api | 2025-06-14 15:36:32+00:00
That’s one of the answers to how you could go to the stars: go sloooooow as in slow down your cognition and metabolism so the trip doesn’t take long.

Ents could fly to the stars no problem.

Makes me wonder if there might not be a bunch of star faring “slow life” out there that we don’t notice for the same reason a hummingbird doesn’t notice trees growing.
by margalabargala | 2025-06-14 15:36:51+00:00
> How much alcohol can a pregnant person drink? (Not too much, obviously, but is a glass of wine a couple of different days in the third trimester okay? Probably, but it varies a lot deoending on which country you're in.)

It's important to differentiate a low individual risk for you, vs what that means to a whole population.

You will easily find someone willing to say "oh I had two glasses of wine a week while pregnant and my kid was fine".

If everyone started drinking 2 glasses of wine a week in the third trimester, FAS rates will increase, and mean IQ score will dip. Will they dip by a lot? Probably not, but definitely not zero. So of course anyone in a position to make a society-wide recommendation, recommends "no alcohol".

Individual parents may look at data and say, that's a risk they're willing to take.
by at_a_remove | 2025-06-14 15:36:55+00:00
I have a fairly unusual genetic disorder, and quite rare to boot in this particular variant. The gold standard cocktail contains a medication which, while effective in dealing with one facet of the pain, absolutely turns down the dimmer switch on my mind in fairly particular ways. Gait is affected the next day, along with a mild aphasia. During the peak, however, I am dumb as a box of rocks. Math and spatial business seem fine. I can still program, however. Just do not talk to me, as communication is ... troublesome.

I usually skip this portion of the cocktail unless things are particularly bad. The disorder is progressive, so when it comes for my brain, well, that's when things are over. I do not have much going on for me in terms of personal value except for, well, solving problems.

A very close friend of mine has had two hospitalizations for gangrene, and the second one absolutely devastated his cognitive abilities. He has leveled off at about eighty-five percent of where he was before. If he is tired or feeling unwell, verbal perseveration begins.

My mother is fairly well-on in her years. She used to have a tremendous vocabulary, despite her very limited education. Now, she has begun to lose words and I end up "translating" for her because I know what she is getting at. She could do crosswords but refuses to, even the Monday selections, which are typically the easiest. Very recently, she has begun misplacing things. I had my suspicions, and during a routine head, neck, and brain imaging for something else, I checked out the results and, sure enough, some loss of volume in the right hippocampus.
by soramimo | 2025-06-14 15:37:00+00:00
FWIW, the energy use per capita in the USA (and other western countries) is lower than in the 1970's and has been steady/declining [1].

Granted, some of the energy intensive manufacturing was outsourced to China and other places, but then again there's also an increase in efficiency standards (e.g. vehicles, heating etc).

CO2 emissions per capita in Western countries (including the US) have peaked in the 1970s and are now roughly on pre-WW2 levels [2].

(note that I'm onboard with reducing waste etc, but the claim that consumption drives energy use is somewhat misleading)

[1] https://ourworldindata.org/grapher/per-capita-energy-use?tab...

[2] https://ourworldindata.org/grapher/co-emissions-per-capita
by perrygeo | 2025-06-14 15:37:05+00:00
> Large language models (LLMs) are powerful but static; they lack mechanisms to adapt their weights in response to new tasks

The learning and inference process are entirely separate, which is very confusing to people familiar with traditional notions of human intelligence. For humans, learning things and applying that knowledge in the real world is one integrated feedback process. Not so with LLMs, we train them, deploy them, and discard them for a new model that has "learned" slightly more. For an LLM, inference is the end of learning.

Probably the biggest misconception out there about AI. If you think LLMs are learning, it's easy to fantasize that AGI is right around the corner.
by keeda | 2025-06-14 15:37:08+00:00
Huh, interesting, I've never had good luck maintaining drafts on mobile devices so very early on I got into the habit of drafting them in something like a mail or notes app. Sometimes I still slip up and start writing drafts in an app itself and then lose them if I get distracted for a minute, though it's more often because apps are too aggressive in refreshing their feeds (the LinkedIn app being a prime example).
by kemotep | 2025-06-14 15:37:28+00:00
We could probably double our solar and battery capacity in the same time as it takes to build a Nuclear Power plant even with removing all the barriers.

I was excited for using mini-reactors in coal plants but then when I realized that former coal plants are too radioactive to safely operate a nuclear plant without extensive cleanup was when I realized nuclear was a dead end.

Nuclear container ships though.
Show HN: Cogio – offline-first macOS time tracker with SQLite
by masterpos | 2025-06-14 15:37:38+00:00
Hey everyone, I’ve been using this app I built for myself to track and analyze my time without needing an internet connection or paying for a subscription. I recently decided to polish it up and publish it as my first app on the store.

Would love to hear your thoughts, suggestions, or anything that could help me improve it.

Have a great day!
by metalman | 2025-06-14 15:38:03+00:00
"However honey isn't a trivial component to produce"....indeed it is not, apiaries were built on boats in roman times as a means to insure polenation for crops along water ways and increase honey production with an eye on shipping logistics to get it to the highest paying markets. there is cave art that depicts honey gathering from truely ancient times and it is impossible to think that humanities ancestors were not oportunistic honey gatherers, with the bee's wax having a multitude of good uses as well. the liklyhood is that honey and wax were sometimes scarce and sometimes in abundance, and sometimes popular as additives and loathed by others. there are various claims and evidence for the earliest deliberate fermentation, but a general agreement that fermentation is truely ancient, with some evidence to suggest that fermentation was the impetus for the first permanent settlements, and as (some) humans ability to metabolise alcohol is a recent genetic adaptation to produce the nessesary enzymes, we will get more evidence as to who, where and when that happened, or kept happening..... edit: my point(if I have one) is that it could be argued that grapes were first to be snuck in as an aduterant, with honey and other ingredients having much longer prior use
by detaro | 2025-06-14 15:38:04+00:00
To me the motivation seems more along the lines of "we build lots of different systems that deal in the same domains" (because they are deep in microservice land, have apps for all kinds of platforms, ...) "lets make sure they all use the same definition of the things". Do you think that doesn't make sense (because each of those should be considered their own domain?) or does something else give you your impression?
by beardyw | 2025-06-14 15:39:43+00:00
A few hundred years ago it was common for a death penalty to include grotesque tortures before the guilty party was actually dead, all lapped up by public crowds. We should be glad to some extent that we are shielded from this today, but it is not new.

Many movies today show ghastly injuries and death. Not sure whether the knowledge it is fictional makes it ok.
by surajrmal | 2025-06-14 15:40:22+00:00
Companies do exist to try and hammer Linux into a good desktop/laptop product. I would say that it's just not easy to do given the lack of vertical integration. Redhat centralizing everything into systemd has probably gone the longest way towards improving things. Of course that is odds with the perceived benefits of having many competing options to perform the job of any given piece of software.
by Keyframe | 2025-06-14 15:40:53+00:00
I don't doubt their yield out of GraphQL is great. Not something I'm having a need for though. I'm at the helm of the tech group at one part of dun&bradstreet so we have different challenges, unification across different borders being primary one. We manage, but the going gets tough sometimes. Described architecture of UDA certainly seems to be what it was designed to solve. I think our system is even at a perfect inflection point to adopt at least some of the principles described to provide a clear path forward to resolve some of those challenges we face; Not as a replacement, but more of as a control plane over our system. I can already see how we could avoid at least schema bloat, lowest common denominator fields and overall rigidity.

Of course, details on "Upper", PDM, and Sphere are well - missing, but at least I have concepts to focus on :)
by Rendello | 2025-06-14 15:41:08+00:00
When I modified the idealized algorithm to suit my needs a few years ago, I learned just how painful the boundary cases are. I realized I didn't want to ever touch SIMD string searching unless:

- I had a very specific use-case that I really needed SIMD for and was willing to really invest a lot in it; or

- The work had already been done for me in a generic sense and I could reap the fruits of that labour (ripgrep / Rust Regex, thanks for that by the way)
by brookst | 2025-06-14 15:42:04+00:00
I don’t entirely disagree, but that is still an intuition, not a proof that our interfaces should always work that way.

We used to ride animals with legs, which worked a lot like our legs do. Does that mean the wheel is wrong? We don’t have wheels, and they don’t occur in nature.

I don’t think Apple has invented the wheel, and I’m inclined to agree that leveraging our hardware acceleration makes sense. But I haven’t seen anything beyond blind assertion that of course it has to work that way.
by mkoubaa | 2025-06-14 15:44:57+00:00
A unique identifier for a movie is the same thing, like an ISBN number. What the label means in each area is going to be different. That said, some things like "director", "budget" are immutable properties of a movie but are absolutely irrelevant for the business areas and the duplication of these properties in different domains is fundamentally not that big of a deal
by porridgeraisin | 2025-06-14 15:45:08+00:00
I've actually seen this happen before. Most changes get deployed with a gradually enabled(% of users/cities/...) feature flag and then cleaned up later on. There is a slack notification from the central service which manages them that tells you how many rollouts are complete reminding you to clean them up. It escalates to SRE if you don't pay heed for long enough.

In the rollout duration, the combinatorial explosion of code paths is rather annoying to deal with. On the other hand, it does encourage not having too many things going on at once. If some of the changes affect business metrics, it will be hard to glean any insights if you have too many of them going on at once.
by canadiantim | 2025-06-14 15:45:08+00:00
You’re right that the experience of the smell of coffee is associated with a bunch of different molecules entering our nose and stimulating receptors there. These receptors then cause an electrochemical cascade of salts into the brain producing neural patterns which are associated with the experience of the smell of coffee. But this is all just association. The conscious experience of the smell of coffee, or red for that matter, is different than the associated electrochemical cascades in the brain. They’re very highly correlated but very importantly: these electrochemical cascades are just associated with qualia but are not qualia themselves. Only qualia is qualia, only red is red, though red, the smell of coffee, etc are very tightly correlated with brain processes. That’s the distinction between consciousness and the brain.
by miyuru | 2025-06-14 15:45:14+00:00
It did happen before LLMs, but there are well documented process to catch them. Google literally wrote the book on SRE best practices.

error handling is very basic, the only explanation these kind of bad code to get pushed to prod is LLMs and high trust on LLM automation.

they wont admit this publicly anyway, there is too much money invested on LLMs.
by evolve2k | 2025-06-14 15:45:51+00:00
Best activity I saw was say 10 front on pics of dogs faces. Print them out and for each image slice the image into vertical slices.

(The 10 original images are the training data)

Then you can make up dog faces by taking slices from each image. Then you can make sorta thinner dog faces (“beauty edits”) by just leaving out every second slice.

Nice practical analogy. Slice in one cow face cause the computer don’t know the difference (hallucinate), it’s mostly a thin dog but not fully some is just sliced in AI junk.

Also discuss how the final AI image is taken from the makers of the original images. Discuss ownership, it’s new but composite, etc.
by westurner | 2025-06-14 15:45:59+00:00
So, to your knowledge there is no factual inconsistency with what I have posted?

You have made an assumption that I didn't review the content that I prepared to post. You have alleged in ignorance and you have disrespectfully harassed without due process.

I did not waste your time with spammy unlabeled AI BS.

I have given my "review search results" time for free; and, in this case too, I have delivered value. You made this a waste of my time. You have caused me loss with such harassment. I have not caused you loss by posting such preliminary research (which checks out).

Did others in this thread identify and share alternative solutions for getting oxygen out of titanium? I believe it was fair to identify and share alternative solutions to the OT which I (re-) posted because this is an unsolved opportunity.

I believe it's fair and advisable to consult and clearly cite AI.

Why would people cite their use of AI? Isn't that what we want?

Which helped solved for the OT problem?

Given such behavior toward me in this forum, I should omit such insightful research (into "efficient and sustainable alternatives") to deny them such advantage.

This was interesting to me and worth spending my personal time on also because removing oxygen from graphene oxide wafers is also a billion dollar idea. Does "hydrogen plasma" solve for deoxidizing that too?
by mkoubaa | 2025-06-14 15:47:26+00:00
When translating from French to English, find someone that speaks both fluently and had domain expertise over the content being translated.

Don't find a linguist who understands grammatical structure and claims to be able to map the source language to some neutral intermediate structure and map that to the target language.

This is a fallacy I notice everywhere but I dont know how to name. Maybe the "Linguist translator" fallacy?
by briian | 2025-06-14 15:47:38+00:00
One thought I have from this is,

Are OpenAI funding research into neuroscience?

Artificial Neural Networks were somewhat based off of the human brain.

Some of the frameworks that made LLMs what they are today are too based of our understanding of how the brain works.

Obviously LLMs are somewhat black boxes at the moment.

But if we understood the brain better, would we not be able to imitate consciousness better? If there is a limit to throwing compute at LLMs, then understanding the brain could be the key to unlocking even more intelligence from them.
by moomin | 2025-06-14 15:48:20+00:00
Well, you’d need some model of index, for one. And I’m not sure how you’d construct that with uncountably many elements. Even ignoring that, a set containing n elements is different from a set containing n sets of one element each.

Not saying your formulation is wrong, just that there’s a fair amount of non-obvious work to get to the classic formulation.
by giantg2 | 2025-06-14 15:50:57+00:00
"I don't know whether this is a result of..."

The cause is pretty easy. Patients aren't treated like mysteries, they're treated like BAU Jira tickets - just get it done so you're on to the next one. The system is built to handle the 90%. If you fall into that other 10%, it won't work well for you. If you have provider companies and insurances pressing you to hit some metric, that's what you have to do. If you are concerned about malpractice, then you have to just read from the Epic system. No surprise we're in this situation.
by Hindol007 | 2025-06-14 15:51:36+00:00
Hi HN,

I got tired of how awkward it is to connect with like-minded devs online. LinkedIn feels too corporate, Discord is chaotic, and most platforms aren’t focused on helping people who just want to build together.

So I built *Campfire* — a lightweight tool where developers can:

- Sync their GitHub profile - Search for collaborators by stack or language - Optionally match with devs via a basic AI matcher - Skip resumes and “networking” in favor of shared projects

It’s still early (no monetization, no onboarding friction), but it’s live and working.

Would love your feedback — especially critical thoughts about direction, incentives, or how it could actually support real collaboration.

Here's the link if you're curious: https://campfire-8c27.onrender.com
by photonthug | 2025-06-14 15:52:06+00:00
IIT has always interested me, and after reading some of the detractors[1] I get that it has problems, but I still don't get the general lack of attention/interest or even awareness about it. It seems like a step in the right direction, establishing a viable middle ground somewhere between work in CS or neuroscience that measure and model but are far too reluctant to ever speculate or create a unifying theory, vs a more philosophical approach to theory of mind that always dives all the way into speculation.

[1] https://scottaaronson.blog/?p=1799
by actsasbuffoon | 2025-06-14 15:52:08+00:00
Oh, I don’t think we’re on the verge of super-intelligence. I don’t think LLMs are a pathway to super-intelligence, and I think most of the talk of super-intelligence right now is marketing fluff.

In terms of crossing an air gap, that really depends. For example, are you aware that researchers can pretty reliably figure out what someone typed just by the sound of the keys being pressed?

Or how about that team who developed a code analysis tool to detect errors, and they ran Tim-sort through it, and the tool said that Tim-sort had a bug where certain pathological inputs would cause it to crash? The researchers assumed their tool was incorrect because Tim-sort is so widely used (it’s the default sort algorithm in Python and Android, for example). But they decided to try it out to see what would happen, and sure enough, they could hard-crash the Python interpreter. No one realized this bug had been there the whole time.

Or various image codec bugs over the years that have allowed a device to be compromised just by viewing an image?

There are some weird bugs out there. Are we certain that there’s no way a computer could detect variances in the timings or voltages happening within it to act as a WiFi antenna or something like that? We’ve found some weird shit over the years! And a super-intelligence that’s vastly smarter than us is way more likely to find it than we are.

Basically, no, I don’t trust the air gap with a sufficiently advanced super intelligence. I think there are things we don’t know that we don’t know, and a super-intelligence would spot them way before we would. There are probably a hundred more Rowhammer attacks out there waiting to be discovered. Are we sure none of them could exchange data with a nearby device? I’m not.