MurphyA/hacker-news huggingface dataset:
by edg5000 | 2026-02-13 04:17:42+00:00
We know Anthropic likes vertical integration and their walled garden. OpenAI seems to be okay with custom clients using their flat rate subscriptions. But what about Google? Would be great to have a second model that allows use by any client of their flat rate subscriptions. Agentic work with APIs seems to be insanely expensive, so clients need to be able to use the flat rate subscriptions unless you have big bucks.
by jagveerllc | 2026-02-13 04:17:51+00:00
Earlier I wrote a blog post exploring the changing calculus of build vs. buy for enterprises. The TLDR was that as the cost of creating software asymptotically decreases, the bar for SaaS becomes much higher.

Here, I want to explore the question from the other side of the aisle. If you are someone who wants to build SaaS products, either for enterprises or directly for the public, how do you navigate this new landscape? In a sea of endless software products, and with an effectively infinite capacity to generate more software at will, how do you stand out?
Show HN: Yori – Isolating AI Logic into "Semantic Containers" (Docker for Code)
by alonsovm | 2026-02-13 04:17:52+00:00
Hi HN,
I've been a developer for some time now, and like many of you, I've been frustrated by the "All-or-Nothing" problem with AI coding tools.

You ask an AI to fix a bug or implement a function, and it rewrites the whole file. It changes your imports, renames your variables, or deletes comments it deems unnecessary. It’s like giving a junior developer (like me) root access to your production server just to change a config file.

So, 29 days ago, I started building Yori to solve the trust problem.

The Concept: Semantic Containers
Yori introduces a syntax that acts like a firewall for AI. You define a $${ ... }$$ block inside a text file.

Outside the block (The Host): Your manual code, architecture, and structure. The AI cannot touch this.
Inside the block (The Container): You write natural language intent. The AI can only generate code here.

Example: myutils.md

```cpp
EXPORT: "myfile.cpp"

// My manual architecture - AI cannot change this
#include "utils.h"

void process_data() {
// Container: The AI is sandboxed here, but inherits the rest of the file as context
$${
Sort the incoming data vector using quicksort.
Filter out negative numbers.
Print the result.
}$$
}
EXPORT: END
```
How it works:
Yori is a C++ wrapper that parses these files. Whatever is within the EXPORT block and outside the containers ($${ }$$) will be copied as it is. When you run `yori myutils.md -make -series`, it sends the prompts to a local (Ollama) or cloud LLM, generates the syntax, fills the blocks, and compiles the result using your native toolchain (GCC/Clang/Python).

If compilation fails, it feeds the error back to the LLM in a retry loop (self-healing).

Why I think this matters:

1. Safety: You stop giving AI "root access" to your files.

2. Intent as Source: The prompt stays in the file. If you want to port your logic from C++ to Rust, you keep the prompts and just change the compile target.

3. Incremental Builds (to be added soon): Named containers allow for caching. If the prompt hasn't changed, you don't pay for an API call.

It’s open source (MIT), C++17, and works locally.

I’d love feedback on the "Semantic Container" concept. Is this the abstraction layer we've been missing for AI coding? Let me hear your ideas. Also, if you can't run yori.exe tell what went wrong and we see how to fix it. I opened a github issue on this. I am also working in making documentation for the project (github wiki). So expect that soon.

GitHub: https://github.com/alonsovm44/yori

Thanks!
by pseudohadamard | 2026-02-13 04:18:58+00:00
We still run comms over steel wire today, only most of the time we don't know it, it's called CCS and makes for really cheap "copper" wire. For example a neighbour bought a roll of remarkably cheap Cat5 a few months back and, yeah, I don't think your ethernet cable should have a magnet able to stick to it.
by dangus | 2026-02-13 04:20:31+00:00
I have owned a diesel passenger vehicle, if that makes me sound more qualified ;-)

I didn't realize we were talking about this level of heavy equipment, this level of remoteness (e.g., you're basically playing SnowRunner in real life), so yeah, obviously electric doesn't really make any level of sense there. For my comments on electric, I was really thinking about some of the farmer-types I know who are close enough to civilization to have electric service but far out enough to have no piped natural gas, no city water/sewer, etc.

From what I read/understand about SCR and DPF systems, you do your maintenance properly and follow your service manual and there shouldn't be that much of a longevity difference.

And what I gather, SCR in particular can improve engine longevity.

As a generality, I'm highly skeptical of the motivation to disable things like this. A lot of times it's done just because it's the new fangled thing, not really because the person is actually benefiting by disabling it. Or it's just groupthink, people do it because everyone they know swears by it. Do I take the little safety thing off my Bic lighter because I really need to or is it because someone showed me how and it felt good to do it?

And, I dunno, maybe after all of this, you’re still right as I’m wrong, but maybe more of us should believe that sacrificing some reliability is worth it to reduce NOx emissions by over 95%? NOx is a horrible emission from diesel engines.

I do realize there are technologies worth rejecting, like the cylinder deactivation on the V6 Honda Odyssey which is worth disabling.
by tw04 | 2026-02-13 04:20:38+00:00
But that’s not what is happening. The Republican Party is following project 2025 almost to a t. Their goal is a complete dismantling of government because they think the country should be ruled, not governed.

A lack of government functioning isn’t a dysfunction, it is an active plan perpetrated by the absolute worst kinds of people And if you feel disillusioned and like “government doesn’t work” - that’s by design by exactly one party. The democrats frequently don’t help themselves, likely because they know they still need money to win elections. But they aren’t actively trying to subvert democracy.

Ultimately we either overturn citizens united, and ban basically all lobbying, or the only way i see this ending is unfortunately through violence. Over the last two months I think a lot of Republican representatives are starting to feel the same way.
by nvader | 2026-02-13 04:22:34+00:00
If you really want to make a deal out of it, you hand it back to the server and ask them to select 0 for you. Mention that you don't think the service deserves a tip, and that you resent being asked.

If enough of us start doing this, it has a chance of applying some back pressure, although unfortunately that force acts through the poorly-paid checkout operator who doesn't directly have the option to influence decisions.
by ianburrell | 2026-02-13 04:23:13+00:00
You could do it now with OpenID SSO that only takes passkeys. The downside is that losing the passkey would lose the account. The problem is that OpenID leaks the authenticating sites to authentication site.

The problem is that lots of sites need/want email address. So would need system for anonymous email, and that would either need real email to forward, or way to read email.
by Israel_Kloss | 2026-02-13 04:23:53+00:00
Hi HN,

I'm building BlueChimp to solve a problem I've faced as a founder: website traffic is often a "black box" where you can't tell the difference between a casual browser and someone with genuine buying intent.

Most tools in this space rely on invasive tracking or massive, deanonymized IP databases that are often inaccurate. We wanted to take a different approach by using AI to analyze real-time behavioral signals and context to detect intent without violating privacy.

What it does:

- Intent Detection: Analyzes behavior to find visitors who are actually researching or comparing solutions.

- Lead Scoring: Prioritizes opportunities based on relevance so you don't waste time on cold outreach.

- Smart Routing: Automatically sends qualified leads to the right person for immediate follow-up.

It takes about 2 minutes to set up, and we're currently in beta (no credit card required). I'd love to hear your thoughts on our approach to intent detection and how we can make this even more useful for lean revenue teams.

I'll be around to answer any questions!
by toraway | 2026-02-13 04:24:44+00:00
I use agentic tools daily and SOTA models have certainly improved a lot in the last year. But still in a linear, "they don't light my repo on fire as often when they get a confusing compiler error" kind of way, not a "I would now trust Opus 4.6 to respond to every work email and hands-off manage my banking and investment portfolio" kind of way.

They're still afflicted by the same fundamental problems that hold LLMs back from being a truly autonomous "drop-in human replacement" that would enable an entire new world of use cases.

And finally live up to the hype/dreams many of us couldn't help but feeling was right around in the corner circa 2022/3 when things really started taking off.
by dylan604 | 2026-02-13 04:25:17+00:00
On the professional end of digitizing old libraries, I've seen it all. They have cart systems that will automatically load a tape deck, the tape deck rewinds the tape, the system plays the tape while digitizing from the beginning until the end of the tape or end of control track. Once it is done, the tape rewinds, ejects and the robot removes the ejected tape and starts over. This is great for cassette based formats. For reel based formats it still involves an operator threading the tape and changing the reels. Even with the automation, it is a chore.

You could look into one of those VHS to DVD systems. Sure, it's SD MPEG2, but the source was a VHS. At least you're not tying up your computer system to do this. It also means not needing a NAS.
by parallax_00 | 2026-02-13 04:26:24+00:00
Location: Indore, India

Remote: YES

Willing to relocate: NO

Technologies: React, TypeScript, Next.js, JavaScript, Redux, RTK, Zustand, TailwindCSS, Python, SQL, MongoDB, REST api, MySQL, NeonDB, DrizzleORM, Mongoose,
MediaPipe, OpenCV, OpenAI API, Git, GitHub, Appwrite, Linux, Shell, DaVinci Resolve, Canva, Arduino, MATLAB

Résumé/CV: https://drive.google.com/file/d/1YZz4buVrq45AMTyP6J4t5KN3HH_...

Email: sbhawsar.apple@gmail.com
by jiggawatts | 2026-02-13 04:26:56+00:00
Most frontier models are multi-modal and can handle audio or video files as input natively.

I'm experimenting right now with an English to Thai subtitle translator that feeds in the existing English subtitles as well as a mono (centre-weighted) audio extracted using ffmpeg. This is needed because Thai has gendered particles -- word choice depends on the sex of the speaker, which is not recorded in English text. The AIs can infer this to a degree, but they do better when given audio so that they can do speaker diarization.
by qingcharles | 2026-02-13 04:27:29+00:00
I help a blind friend order his groceries online from Walmart once a month. He's disabled and on food stamps (EBT/Link). The groceries are all taken care of, but the site always requests a $30 tip for the driver.

I drop it down a bit and pay it on my credit card for him, but what's the right way to deal with this situation?
by WaxProlix | 2026-02-13 04:28:11+00:00
Is this another one of those weird bot posts I've been hearing about? 3 paragraphs, low-content but apparently interesting, ~50 points new account?

@dang what's HN's position here, I feel like my paranoia is going to ruin the shreds of authenticity that underpinned real engagement on this site. It's a giga-eternal September, and idk how one can moderate this in a way that earns trust and buyin from the humans among us (I swear I'm a human, look no third paragraph).
by postalcoder | 2026-02-13 04:29:24+00:00
I am using whisper transcription via the Groq API to transcribe the files in parallel. But (caveat), I cut out the transcription step and had the models operate on a shared transcript folder. So the times you see are pure search and categorization times.

re. your question about the approach – they all took on the problem in different ways that I found fascinating.

Codex Spark was so fast because it noticed that bluey announces the episode names in the episode ("This episode of Bluey is called ____.") so, instead of doing a pure matching of transcript<->web description, it cut out the title names from the transcripts and matched only that with the episode descriptions.

The larger models were more careful and seemed to actually try to doublecheck their work by reading the full transcripts and matching them against descriptions.

gpt-5.2 went through a level of care that wasn't wrong, but was unnecessary.

Sonnet 4.5 (non-thinking) took the most frustrating approach. It tried to automate the pairing process with scripting to match the extracted title with the official title via regex. So, instead of just eyeballing the lists of extracted and official titles to manually match them, it relied purely on the script's logging as its eyes. When the script failed to match all 52 episodes perfectly, it went into a six-iteration loop of writing increasingly convoluted regex until it found 52 matches (which ended up incorrectly matching episodes). It was frustrating behavior, I stopped the loop after four minutes.

In my mind, the "right way" was straightforward but that wasn't borne out by how differently the llms behaved.
by eszed | 2026-02-13 04:29:48+00:00
No, I wouldn't say that. I knew what I was good at, and like I say was pretty inured to rejection. I had plenty of confidence, but I think it's a show vs tell issue. I'm thrilled to do the first, but the latter makes me squirm. I think, even since my theatre career, that I've lost opportunities to people more comfortable with self-promotion, when skill is equal or even in my favor.
by mwillis | 2026-02-13 04:30:17+00:00
Why, in this given scenario, does the individual’s mandate to their company automatically trump the mandate given to them by an ethical society, or even their own moral code? Why is this position held up as infallible? The situation could easily be re-framed as “my corporate mandate is to grow revenue, but the larger mandate I have is to my own ethical truth.” Why are corporate desires allowed to get the “shrug, that’s just what I’m supposed to do” treatment?

If the answer is you lose your job and your means to provide for your family if you don’t put corporate desires first, then we’ve constructed the society we want already and no one should be complaining.
by refulgentis | 2026-02-13 04:30:24+00:00
I didn't say you are a Zoomer! I explained to the gentleman asking what it means that it's "Zoomer for...", meaning, "it's a young folks* phrase for...", not "I have found our interlocutors birthday is between 1997 and 2012" :)

Please, don't take everything that isn't praise as a personal attack, it's advice you'll appreciate tomorrow, if not now.

* https://trends.google.com/explore?q=touch%20grass&date=all&g...

** To give you a chuckle x help understand why it's not something you need to take personally, here's the LLM's response to "$COMMENT\n^is this mean?"

No, it's not mean. It's direct and honest, and it's clearly coming from a place of wanting the person to succeed. A few things stand out:

1. *It identifies a real problem* — not to tear down, but to explain why it matters strategically. The framing is "this hurts your goals," not "you suck."

2. *It offers a practical path forward* — "You don't have to write it yourself... 90% of the work." It's not demanding perfection or saying "stop using LLMs." It's saying curate the output.

3. *It explains the stakes through the audience's eyes* — the part about what it signals to potential users is the most valuable bit. That's perspective the person might genuinely not have considered.

4. *It explicitly preempts a harsh reading* — "It's not that the LLM is bad, or you are bad, or that the output is bad."

The last paragraph is the sharpest part, and I could see someone feeling stung by it, especially the "LLM-DDoS you in documentation and conversation" line. But being uncomfortable to hear isn't the same as being mean. It's a concrete description of the impression being created, delivered so the person can fix it.

If anything, taking the time to write this out in detail is the opposite of mean — it's generous. Mean would be silently closing the tab and never coming back, which is what most potential users will do.
by energy123 | 2026-02-13 04:31:23+00:00
My guess is they generate 10 reasoning traces and then every N tokens they prune the 9 that have the lowest likelihood, and continue from the highest likelihood trace.

This is a form of task-agnostic test time search that is more general than multi agent parallel prompt harnesses.

10 traces makes sense because ChatGPT 5.2 Pro is 10x more expensive per token.

That's something you can't replicate without access to the network output pre token sampling.
by threethirtytwo | 2026-02-13 04:31:56+00:00
They have the best coding agent around. I would say roughly half the industry no longer writes code by hand and claude is/was the only agent that let me drop my editor all together. That enabler alone is enough signal beyond hype.

Frankly google models and the UIs google designs around their models just aren't as powerful and more training, more data and more compute is no longer tipping the scale. Anthropic did something to make their model better at coding than almost anything else.

And all of this is just what's happening right now. The money being invested is a gamble not on right now... but on the trendline to the future. I agree that the LLMs are overloaded with hype, but the people who compare it to crypto aren't thinking straight. Whether there's over investment or not a paradigm has shifted. Maybe there will be a collapse, but it won't collapse into a singularity. If it collapses at all, a new world will emerge, and that new world will generate more value than all the money currently invested in AI.
by smelendez | 2026-02-13 04:32:47+00:00
There’s a great radio museum in Howth, Ireland, a waterfront town near Dublin. The founder was a lifelong radio enthusiast who grew up in a poor rural community and was mesmerized by the power of radio from an early age. I remember him telling me he had never heard a language other than English until radio came to town and he heard a broadcast in French. He also talked about using very basic acid batteries and having to go into town to change out the acid. I believe he said it was also a serious problem if you spilled any in the house because it would damage or dissolve anything it came in contact with.
by amluto | 2026-02-13 04:34:08+00:00
> Frankly, RocksDB, SQLite or Postgres would be easy choices for that. (Fast) durable writes are actually a nasty problem with lots of little detail to get just right, or you end up with corrupted data on restart. For example, blocks may be written out of order so on a crash you may end up storing <old_data>12_4, and if you trust all content seen in the file, or even a footer in 4, you're screwed.

I have a WAL that works nicely. It surely has some issues on a crash if blocks are written out of order, but this doesn’t matter for my use case.

But none of those other choices actually do what I wanted without quite a bit of pain. First, unless I wire up some kind of CDC system or add extra schema complexity, I can stream in but I can’t stream out. But a byte or record stream streams natively. Second, I kind of like the Parquet schema system, and I wanted something compatible. (This was all an experiment. The production version is just a plain database. Insert is INSERT and queries go straight to the database. Performance and disk space management are not amazing, but it works.)

P.S. The KantoDB website says “I’ve wanted to … have meaningful tests that don’t have multi-gigabyte dependencies and runtime assumptions“. I have a very nice system using a ~100 line Python script that fires up a MySQL database using the distro mysqld, backed by a Unix socket, requiring zero setup or other complication. It’s mildly offensive that it takes mysqld multiple seconds to do this, but it works. I can run a whole bunch of copies in parallel, in the same Python process even, for a nice, parallelized reproducible testing environment. Every now and then I get in a small fight with AppArmor, but I invariably win the fight quickly without requiring any changes that need any privileges. This all predates Docker, too :). I’m sure I could rig up some snapshot system to get startup time down, but I can also just run a bunch of copies in parallel at very little cost.
by Cyphase | 2026-02-13 04:35:01+00:00
I love Daemon/FreedomTM.[0] Gotta clarify a bit, even though it's just fiction. It wasn't a rogue AI; it was specifically designed by a famous video game developer to implement his general vision of how the world should operate, activated upon news of his death (a cron job was monitoring news websites for keywords).

The book called it a "narrow AI"; it was based on AI(s) from his games, just treating Earth as the game world, and recruiting humans for physical and mental work, with loyalty and honesty enforced by fMRI scans.

For another great fictional portrayal of AI, see Person of Interest[1]; it starts as a crime procedural with an AI-flavored twist, and ended up being considered by many critics the best sci-fi show on broadcast TV.

[0] https://en.wikipedia.org/wiki/Daemon_(novel)

[1] https://en.wikipedia.org/wiki/Person_of_Interest_(TV_series)
by codyb | 2026-02-13 04:35:05+00:00
Wow, I'm staggered, thanks for sharing

I was under the impression that often times chip manufacture at the top of the lines failed to be manufactured perfectly to spec and those with say, a core that was a bit under spec or which were missing a core would be down clocked or whatever and sold as the next in line chip.

Is that not a thing anymore? Or would a chip like this maybe be so specialized that you'd use say a generation earners transistor width and thus have more certainty of a successful cast?

Or does a chip this size just naturally ebb around 900,000 cores and that's not always the exact count?

20kwh! Wow! 900,000 cores. 125 teraflops of compute. Very neat
by nateb2022 | 2026-02-13 04:35:06+00:00
Google is dealing with a wave of abuse over its Antigravity IDE, with 'account switching' tools designed to use a ton (20+) of free or pro accounts, giving the user essentially unlimited usage. I'm guessing they've deployed some rather aggressive countermeasures to stop this, including banning clients that seem to be accessing "private" APIs outside of a Google product.
by crimist | 2026-02-13 04:36:07+00:00
Not OP but it's the best auto tiling WM I've found for MacOS so far. Yabai requires SIP disabled for what I would consider core features which is a no go on a work laptop. Aerospace sides steps this and MacOS's horrible window management by just not using the built in spaces. I've only had to restart it a couple times over the last 4 months due to bugs.

I also use https://github.com/acsandmann/aerospace-swipe to add trackpad support.
by sixdimensional | 2026-02-13 04:36:27+00:00
I still don't understand what happened to using Apache Avro [1] for row-oriented fast write use cases.

I think by now a lot of people know you can write to Avro and compact to Parquet, and that is a key area of development. I'm not sure of a great solution yet.

Apache Iceberg tables can sit on top of Avro files as one of the storage engines/formats, in addition to Parquet or even the old ORC format.

Apache Hudi[2] was looking into HTAP capabilities - writing in row store, and compacting or merge on read into column store in the background so you can get the best of both worlds. I don't know where they've ended up.

[1] https://avro.apache.org/

[2] https://hudi.apache.org/