MurphyA/hacker-news huggingface dataset:
by Scubabear68 | 2025-10-03 16:20:58+00:00
Object Relational Mapping (ORM) tools, which focus on mapping between code based objects and SQL tables, often suffer from what is called the N+1 problem.

A naive ORM setup will often end up doing a 1 query to get a list of object it needs, and then perform N queries, one per object, usually fetching each object individually by ID or key.

So for example, if you wanted to see “all TVs by Samsung” on a consumer site, it would do 1 query to figure out the set of items that match, and then if say 200 items matched, it would do 200 queries to get those individual items.

ORMs are better at avoiding it these days, depending on the ORM or language, but it still can happen.
by cbm-vic-20 | 2025-10-03 16:21:05+00:00
There's a common access pattern with object-relational mapping frameworks where an initial query will be used to get a list of ids, then an individual queries are emitted for each item to get the details of the items. For example, if you have a database table full of stories, and you want to see only the stories written by a certain author, it is common for a framework to have a function like

stories = get_stories(query)

which results in a SQL query like

SELECT id FROM stories WHERE author = ?

with the '?' being bound to some concrete value like "Jim".

Then, the framework will be used to do something like this

for id in stories { story = get_story_by_id(id) // do something with story }

which results in N SQL queries with

SELECT title, author, date, content FROM stories WHERE id = ?

and there's your N+1
Show HN: TruVideo – On-device detector for Sora, Veo and other GenAI videos
by sanjkris | 2025-10-03 16:21:26+00:00
Sora and Veo are making AI videos everywhere — but how do you know if they’re real?

TruVideo flags AI-generated images and videos on-device. Just point it at suspicious media on social platforms — everything runs locally for speed and privacy.

The model detects artifacts from diffusion, GANs, latent space methods, transformers, spatiotemporal transformers, NeRFs, and hybrid architectures.
by reaperducer | 2025-10-03 16:21:46+00:00
Some of the “AI startups” will be sold in fire sales for parts so investors can at least minimize losses and most of the rest will vaporize

Sometimes literally.

Every time a tech bubble pops, it's an opportunity to upgrade your work-from-home furniture cheap.

I've gotten some nice chairs and even have a nice coffee table that used to grace an office lobby in the old WaMu tower in Seattle.

I guess that makes me a home furnishings vulture.
by derektank | 2025-10-03 16:22:08+00:00
I was sort of inclined to agree coming into reading this (my understanding is that this is a prototype round, and other contractors have received awards, prior to a downselect round where one contractor will be selected for full production) but if it's true that, "We cannot control who sees what, we cannot see what users are doing," that seems like a bearish signal.

Access control and user level logging seem like kind of basic feature requirements for a military C2 system? And Lattice isn't a completely immature product either IIRC.
by fennecbutt | 2025-10-03 16:22:15+00:00
I honestly do not think that we should be training models to regurgitate training data anyway.

Humans do this to a minimum degree, but the things that we can recount from memory are simpler than the contents of an entire paper, as an example.

There's a reason we invented writing stuff down. And I do wonder if future models should be trying to optimise for rag with their training; train for reasoning and stringing coherent sentences together, sure, but with a focus on using that to connect hard data found in the context.

And who says models won't have massive or unbounded contexts in the future? Or that predicting a single token (or even a sub-sequence of tokens) still remains a one shot/synchronous activity?
by guerrilla | 2025-10-03 16:22:38+00:00
This rings true to me as someone who's overcome most of his social anxiety over the last few years. The last graph is particularly correct. It's about being authentic and being okay with people not liking you. This is especially useful in dating because then you stop being needy (which is unattractive) when you can let go of the outcome and just show someone who you are and if they reject you then you simply realize that they aren't the person you were looking for because you were looking for someone who likes you for who you are.

Is the person who wrote the post qualified to say this though? Like are these statements the result of scientific research or just his opinion like my opinion?
by chihuahua | 2025-10-03 16:22:52+00:00
And the best demonstration of Seattle's hapless "can't do" attitude is that they left the watertight doors open one day in 1990 and the bridge pontoons filled with water and the bridge sank. Back then, by some miracle the bridge was fixed in a few weeks, but today it would take 10 years.

When the light rail line was installed on the I-90 bridge, after the whole thing was done it was discovered that the rail ties were built incorrectly. This was in April 2023. Thousands of concrete ties had to be demolished and construction had to start over. Of course this took years. God forbid that someone should check the work along the way.

If Seattle was a Simpsons character, it would be Ralph Wiggum when he's grown up and has one foot permanently stuck in a bucket.
by bonestamp2 | 2025-10-03 16:22:57+00:00
There are some inference chips that are fundamentally different from GPUs. For example, one of the guys who designed Google's original TPU left and started a company (with some other engineers) called groq ai (not to be confused with grok ai). They make a chip that is quite different from a GPU and provides several advantages for inference over traditional GPUs:

https://www.cdotrends.com/story/3823/groq-ai-chip-delivers-b...
by ryandrake | 2025-10-03 16:23:00+00:00
It's incredible how consistently bad Set Top Box (and now some embedded-in-tv) products have been, going all the way back to the 90s. It's like every one of these STB manufacturers follows the same playbook: 1. Cut hardware performance down to the absolute bare minimum required to decode some insufficiently selected, average quality video. 2. Make interaction with a remote control as laggy and painful as possible, while also providing stupid [company specific] buttons on the remote that nobody uses. 3. Have no consistent design language or apparent UX research for the software's on-screen GUI, using misaligned clipart images and fixed-width shit-tier fonts for text. I used to even develop these boxes back in the day, and they've always been neglected engineering-wise, built by the lowest bidder so they are as cheap and fragile as humanly possible.
by enforzaguy | 2025-10-03 16:23:05+00:00
Hi HN,

I’ve been building Enforza, a centrally cloud-managed firewall/gateway platform. The idea came out of frustration with how expensive and complex cloud-native firewalls and NAT gateways have become.

Enforza is designed as the alternative to AWS/Azure/GCP’s equivalents:

- Deploy as a lightweight firewall/NAT gateway in your cloud or hybrid network - install an agent on a linux box. - Centrally managed from the cloud (no CLI gymnastics, no appliance sprawl) - Removes the data processing charges that come with native services - Typically saves teams up to 80% compared to AWS and Azure NAT Gateway/Firewalls

Launched MVP early in 2025, then rebuilt the platform from the ground up for scalability and with customer-requested features.

I’d love feedback from the HN community:

- Where are you still hitting pain with native cloud firewalls/NAT? - What would you expect a leaner alternative like this to absolutely get right? - Where do you think I should start advertising (Google PPC, Reddit etc)?

Happy to answer technical questions here — including deployment details, integration, or how the pricing model works.

— Neil (founder)
by jpalawaga | 2025-10-03 16:23:05+00:00
Even if you haven't. My partner is an iphone loyalist for years and was very disappointed that they removed the "open tabs" button out of safari. I (new to iPhone) had to show them the pinch-out gesture to show your tabs.

It's beyond unintuitive. At least in the latest OS release, they've stopped hiding the searchbar in the ridiculous 'scroll past the top of the list' idiom.

The verge also has this wonderful paywall which completely breaks safari scroll such that you can't show the toolbar. The only way to 'go back' once you're hit with the paywall is to know about the hidden 'swipe from the far side' gesture in safari (cumbersome given the size of phones).

I sometimes wonder if people actually use the devices they make.
by dustincoates | 2025-10-03 16:23:09+00:00
Not sure why this article didn't link to the original when citing it, but here's the link to the Scott Alexander blog: https://slatestarcodex.com/2014/04/23/friendship-is-counters...

And a follow up: https://slatestarcodex.com/2014/08/09/friendship-is-still-co...
by lumost | 2025-10-03 16:23:20+00:00
OpenAI has a reasonable path to reduce their costs by 10-100x over the next 5 years if they stop improving the models. That would make them an extremely profitable company with their only real risk being “local ai”. However customers have wanted their data in the cloud for years, local inference would likely just mean 0 cost tokens for OpenAI.

The challenge is the rest of the industry funding dead companies with billions of dollars on the off chance they replicate OpenAI’s success.
by Der_Einzige | 2025-10-03 16:23:33+00:00
I'm 99.999% sure that the claim of "all deep learning for Gemini on their own silicon" is not true.

Maybe if you restrict it similarly to the Deepseek paper to "Gemini uses TPU for the final successful training run and for scaled inference" you might be correct, but there's no way that GPUs aren't involved for at minimum comparability and more rapid iteration reasons during the extremely buggy and error prone point of getting to the final training run. Certainly the theoretical and algorithmic innovations that are often being done at Google and do make their way into Gemini also sometimes using Nvidia GPUs.

GCP has a lot of, likely on the order of at least 1 million GPUs in their fleet today (I'm likely underestimating). Some of that is used internally and is made available to their engineering staff. What constitutes "deep learning for gemini" is very up to interpretation.
by zdragnar | 2025-10-03 16:23:40+00:00
I think btown's sibling comment has it right. It's not even a prototype if it isn't demonstrating some aspect of its core capabilities.

Given this line from the article:

Despite the early September memo’s scathing critique, Leonel Garciga, Army chief information officer and Chiulli’s supervisor, said in a statement to Reuters that the report was part of a process that helped in “triaging cybersecurity vulnerabilities” and mitigating them.

and

Other deficiencies highlighted in the memo include the hosting of third-party applications that have not undergone Army security assessments. One application revealed 25 high-severity code vulnerabilities. Three additional applications under review each contain over 200 vulnerabilities requiring assessment, according to the document.

it seems like there was a SIGNIFICANT mismatch in expectations between the team delivering the prototype and the people receiving it. Everyone's time was wasted as a result.
by TIBlock | 2025-10-03 16:23:44+00:00
Full Stack Web Development - > Front End Developer / Back End Developer | Software Engineering | Software Development | IT Support | IT Operations: App Development, Enterprise Systems, and Technology Product Solutions

Remote: Yes

Willing to relocate: Open to opportunities worldwide

Technologies: PHP, Drupal, JavaScript, Python, React, TypeScript, Node.js, MySQL, PostgreSQL,

Resume: https://drive.google.com/file/d/1Uksw3wkkrPUmIRLO-6Rc6qp4tq8...

Email: TaylorBlocker@gmail.com

I’m a resourceful and reliable technology professional with over eight years of experience spanning applications development, IT operations, software engineering, and enterprise system support. I am a career technologist who believes that technology should deliver optimal experiences for end users while championing strategic goals for business. Whether I’m building clean, maintainable code, designing high-quality web applications, or troubleshooting system vulnerabilities, my focus is always on creating solutions that are scalable, efficient, and user-friendly.

I’ve built my career on a balance of technical depth and human connection. On the technical side, I thrive in environments where I can dive into code, analyze complex systems, and optimize processes. I’ve

succeeded in: - Reducing application latency from 30 seconds to under one second. - Maintaining more than 100 RESTful API endpoints. - Writing or updating over 500,000 lines of code that power everything from web applications to mobile platforms.

I’ve worked across industries and projects where adaptability and continuous learning were key. I’ve built expertise across cloud platforms (AWS, GCP), databases (MySQL, PostgreSQL), and frameworks (React, Node.js, Laravel, .NET, CodeIgniter, Express). I’m fluent in multiple programming languages, including JavaScript, Python, C#, HTML, CSS, and Typescript, and I’m comfortable navigating version control tools like Git and SourceTree. What excites me most is the challenge of problem-solving and the chance to deliver solutions that make a real difference for users and businesses alike.

I’m always experimenting with new programming techniques, sharpening my knowledge in full-stack development, and exploring ways to visualize data and optimize performance. For me, staying relevant in this industry means not only keeping up with the pace of change but staying curious enough to anticipate what’s next.

Colleagues have seen me as a collaborator and leader who’s approachable and friendly, yet willing to step up and guide a team with clarity and purpose. I take pride in fostering environments where people feel supported, where feedback flows openly, and where projects stay aligned to both technical best practices and organizational goals.

If you’re looking for someone who can bridge the gap between deep technical expertise and effective collaboration, while driving innovation and performance, I’d love to connect.
by archagon | 2025-10-03 16:23:59+00:00
What, the post where DHH implies that brown immigrants are rapists and criminals and that Britain is being invaded and needs to be cleansed? The one that paints five-time convicted criminal and fascist Tommy Fucking Robinson as some sort of folk hero? That man is a post away from shrieking about remigration for non-whites, just like many of his new-found allies already do.
by damnesian | 2025-10-03 16:24:00+00:00
> "I think we might be in the era where seeing is not believing."

This is what I'm concluding as well. I don't know if that means there will be a backlash that favors simpler communication- in person, old-school methods, private blogs or what have you- or there will be a faction of people who realize this and abstain while the rest of the world go down the mass hallucination rabbit hole of a severly dystopian Matrix.
by simonw | 2025-10-03 16:24:10+00:00
Often you can use joins to get the data in a single complex SQL query. Number of comments for a post is relatively straight-forward, but you can also do increasingly complex associated data fetches with modern databases.

In particular, JSON aggregations mean you can have a single query that does things like fetch a blog entry and the earliest 10 comments in a single go. I wrote up some patterns for doing that in SQLite and PostgreSQL here: https://github.com/simonw/til/blob/main/sqlite/related-rows-...

Here's an example PostgreSQL query that does this to fetch tags for posts: https://simonwillison.net/dashboard/json-agg-example

select blog_entry.id, title, slug, created, coalesce(json_agg(json_build_object(blog_tag.id, blog_tag.tag)) filter ( where blog_tag.tag is not null ), json_build_array()) as tags from blog_entry left join blog_entry_tags on blog_entry.id = blog_entry_tags.entry_id left join blog_tag on blog_entry_tags.tag_id = blog_tag.id group by blog_entry.id order by blog_entry.id desc

The alternative, more common path is the pattern that Django calls "prefetch_related". Effectively looks like this:

select id, title, created from posts order by created desc limit 20 -- Now extract the id values from that and run: select blog_entry.id, blog_tag.tag from blog_entry join blog_entry_tags on blog_entry.id = blog_entry_tags.entry_id join blog_tag on blog_entry_tags.tag_id = blog_tag.id where blog_entry.id in (?, ?, ?, ...) -- Now you can re-assemble the list of tags for -- each entry in your application logic

Once you have a list of e.g. 20 IDs you can run a bunch of cheap additional queries to fetch extra data about all 20 of those items.
by jajuuka | 2025-10-03 16:24:35+00:00
Yeah most companies want good PR for access. Apple takes this to the extreme where the first whiff of negatives things to say and you're cut off. Now you won't get invited to events or given devices early. So you'll have to wait until release and buy it yourself. Then take the time to review a device. By that point most people have already seen the other coverage and made up their mind. So you will get very little motion which translates to income.

These corporations have effectively built their own club of chosen mouthpieces who are willing to excuse negatives about a product to make money.
by pseudosavant | 2025-10-03 16:24:39+00:00
What is going on with AI right now could be a bubble just like there was the dotcom bubble. But it isn't like the internet went away after the dotcom burst. The largest companies in existence today are internet companies or have products that wouldn't make sense without the internet.

Sure, many of these "thin prompt wrapper around the OpenAI API" product "businesses" will all be gone within a few years. But AI? That is going to be here indefinitely.
by imiric | 2025-10-03 16:24:48+00:00
I think you're misunderstanding what a "wart" is. None of those examples are warts. They're the way those programs work, which you can easily understand by reading their documentation. Your point about `cat` is an example of misuse, and `cut` is needed because of the deliberate design decision to make text streams the universal interface, which has far greater benefits than forcing any specific separator.

A wart is not surprising or unintuitive behavior. It is a design quirk—a feature that sticks out from the program's overall design, usually meant to handle edge cases, or to preserve backwards compatibility. For example, some GNU programs like `grep` and `find` support a `POSIXLY_CORRECT` env var, which changes their interface and behavior.

My point is that the complexity of the software and its interface is directly proportional to the likelihood of it developing "warts". `find` is a much more complex program than `cut` or `uniq`, therefore it has developed warts.

Next time, please address the point of the comment you're replying to, instead of forcing some counterargument that happens to be wrong.
by lucb1e | 2025-10-03 16:25:23+00:00
Did anyone ever find out where those people were driving with such urgency, if indeed the town is like 6km start to finish? Felt a bit unresolved in the post

Is it just daily life, going 2km from work to home in a wind-protected vehicle (since the car won't be warm yet when your destination is on average like 4 minutes away; it can't be the heat aspect) as opposed to walking or, idk, ice skating or whatever it is you can do there (I presume not cycling or scootering due to slipperiness)?
by floxy | 2025-10-03 16:25:26+00:00
On a slightly different tangent, is anyone working on analog machine learning ASICs? Sub-threshold CMOS or something? I mean even at the research level? Using a handful of transistor for an analog multiplier. And get all of the crazy fascinating translinear stuff of Barrie Gilbert fame.

https://www.electronicdesign.com/technologies/analog/article...

https://www.analog.com/en/resources/analog-dialogue/articles...

http://madvlsi.olin.edu/bminch/talks/090402_atact.pdf
by dachrillz | 2025-10-03 16:25:39+00:00
Not OP, but when we tested it out it was painful to handle usb disks. The reason being that if you have two they get named sda/sdb randomly. We managed to overwrite the usb we were using to install talos since that one was named sda one boot and sdb the next. This lead ut to develop the “pullout technique” when installing…

This mostly only happened because it was a test cluster where we used usb disks, probably not a problem when one properly provisions.

Otherwise it was great! But it does feel akward not booting into an environment where you have a terminal at first
by gouggoug | 2025-10-03 16:25:42+00:00
> There's nothing inherently wrong with having per-env branches

There is when you stop thinking in terms of dev, staging and prod, and you realize that you might have thousands of different environments, all named differently.

Do you create a branch for each one of them?

Using the environment name as branch name is coupling your repository with the external infrastructure that's running your code. If that infrastructure changes, you need to change your repository. That in itself is a cue it's a bad idea to use branches this way.

Another issue with this pattern is that you can't know what's deployed at any given time in prod. Deploying the "production" branch might yield a different result 10 minutes from now, than it did 25 minutes ago. (add to the mix caching issues, and you have a great recipe for confusing and hard to debug issues)

If you use tags, which literally are meant for that, combined with semver (though not necessarily a requirement, but a strong recommendation), you decouple your code and the external environment.

You can now point your "dev" environment to "main", point staging to ">= v1.25.0" and "prod" to "v1.25.0", "dev-alice" to "v2.0.0", "dev-john" to "deadb33f".

When you deploy "v1.25.0" in prod, you _know_ it will deploy v1.25.0 and not commit deadb33f that so happened to have been merged to the "production" branch 30 seconds ago.
by argiopetech | 2025-10-03 16:25:46+00:00
I'm away from the computer at the moment, but I believe I'm on 0.1.3 [0].

Noting the release notes, it does have many animations already enabled (but I have some or all of them disabled through config).

I'm not recommending anyone run this in favor of newer versions, but it's working for me.

[0] https://github.com/YaLTeR/niri/releases/tag/v0.1.3
by potato3732842 | 2025-10-03 16:26:01+00:00
>What purpose outside abetting in avoiding a DUI is there for publishing a live map of DUI checkpoints?

When Churchill made that famous quip about the "average voter" he was talking about the kind of people who complain out of one side of their mouth about law enforcement going hard on a particular class of laws they don't like while stating out the other that anyone who doesn't want to submit to a papers-please stop on the pretext of catching people engaged in a fairly common misdemeanor that they do want to see hard enforcement on is abetting said misdemeanor.