MurphyA/hacker-news huggingface dataset:
by arcticbull | 2025-11-04 01:43:03+00:00
For what it's worth they cost a lot less than highways to maintain. Something like the 101 in the Bay Area costs about $40,000 per lane-mile per year, or about $240,000.

Trains are closer to $50-100,000 per mile per year.

If there's no money for the work it's a prioritization decision.
by StopDisinfo910 | 2025-11-04 01:44:20+00:00
I strongly condemn the October terrorist attack but I don’t see how someone can defend the morality of the IDF after the Gaza campaign.

We are talking of an army arbitrarily establishing no go zone in the middle of streets, not publishing them and then having snipers shoot down civilians crossing these imaginary lines including the ones coming to get back the corpses of their murdered family members. An army so blood thirsty they shot their own defenceless hostage who came in front of them with hands raised.

It’s pretty clear at that point that the IDF has absolutely no moral. This doesn’t in any way mean I support Hamas.
by 0xbadcafebee | 2025-11-04 01:45:03+00:00
It's clear that AI is useful. It's not yet clear how useful. Hype has always obscured real value, and nobody knows the real value until the hype cycle completes.

What is clear, is that we have strapped a rocket to our asses, fueled with cash and speculation. The rocket is going so fast we don't know where we're going to land, or if we'll land softly, or in a very large crater. The past few decades have examples of craters. Where there are potential profits, there are people who don't mind crashing the economy to get them.

I don't understand why we're allowing this rocket to begin with. Why do we need to be moving this quickly and dangerously? Why do we need to spend trillions of dollars overnight? Why do we need to invest half the fucking stock market on this brand new technology as fast as we can? Why can't we develop it in a way that isn't insanely fast and dangerous? Or are we incapable of decisions not based on greed and FOMO?
by hi_hi | 2025-11-04 01:45:53+00:00
The article seems well researched, has some good data, and is generally interesting. It's completely irrelevant to the reality of the situation we are currently in with LLMs.

It's falling into the trap of assuming we're going to get to the science fiction abilities of AI with the current software architectures, and within a few years, as long as enough money is thrown at the problem.

All I can say for certain is that all the previous financial instruments that have been jumped on to drive economic growth have eventually crashed. The dot com bubble, credit instruments leading to the global financial crisis, the crypto boom, the current housing markets.

The current investments around AI that we're all agog at are just another large scale instrument for wealth generation. It's not about the technology. Just like VR and BioTech wasn't about the technology.

That isn't to say the technology outcomes aren't useful and amazing, they are just independant of the money. Yes, there are Trillions (a number so large I can't quite comprehend it to be honest) being focused into AI. No, that doesn't mean we will get incomprehensible advancements out the other end.

AGI isn't happening this round folks. Can hallucinations even be solved this round? Trillions of dollars to stop computers lying to us. Most people where I work don't even realise hallucinations are a thing. How about a Trillion dollars so Karen or John stop dismissing different viewpoints because a chat bot says something contradictory, and actually listen? Now that would be worth a Trillion dollars.

Imagine a world where people could listen to others outside of their bubble. Instead they're being given tools that re-inforce the bubble.
by hn_acc1 | 2025-11-04 01:47:23+00:00
Sure, people with ZERO enterprise experience might say - hey, let's write our <main software> in PHP - I had a lot of fun 15 years ago with that, and I'm sure we can make it work.. That's the "3 toothpicks" in your example.

But is anyone REASONABLY competent going to do that? They might pick C/C++, Go, Rust, Java, etc. Those aren't a choice between "bulldozers and toothpicks" - they are more akin to choosing between Caterpillar, Volvo or Hitachi as the vendor of choice for construction equipment. They may have some gaps in their specific list of equipment, they may charge too much for one specific tool, your workers may have experience with one, not the other, etc..

Your example should be the textbook definition of a strawman argument..
by oofbey | 2025-11-04 01:48:46+00:00
I think we both love Math. But I respectfully disagree. These are games. In a game like Portal, standard intuition about geometry mostly applies, as long as there isn’t a portal in the portion of space you’re considering. The boundaries between reality and magic are what make it interesting. And the fact that it’s mostly normal but sometimes not is exactly what makes it interesting. Because for the player, it doesn’t matter if the proofs are invalid, their intuition mostly holds.

In HyperRogue, normal Earth intuition is mostly inapplicable because of the hyperbolic geometry. The fact that it has portals and therefore proofs fail shouldn’t IMHO be the defining features of the world. Unless you think the key audience of the game is topologists or something, but if you care about non-mathematicians getting into the game, I’d say focus on intuition not axioms.
by gpupromain | 2025-11-04 01:49:29+00:00
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by bccdee | 2025-11-04 01:49:51+00:00
I find the argument for the bubble to be extremely straightforward.

Currently, investment into AI exceeds the dot-com bubble by a factor of 17. Even in the dot-com era, the early internet was already changing media and commerce in fundamental ways. November is the three-year anniversary of ChatGPT. How much economic value are they actually creating? How many people are purchasing AI-generated goods? How much are people paying for AI-provided services? The value created here would have to exceed what the internet was generating in 2000 by a factor of 17 (which seems excessive to me) to even reach parity with the dot-com bubble.

"But think where it'll be in 5 years"—sure, and let's extrapolate that based on where it is now compared to where it was 3 years ago. New models present diminishing returns. 3.5 was groudbreaking; 4 was a big step forward; 5 is incremental. I won't deny that LLMs are useful, and they are certainly much more productized now than they were 3 years ago. But the magnitude of our collective investment in AI requires that a huge watershed moment be just around the corner, and that makes no sense. The watershed moment was 3 years ago. The first LLMs created a huge amount of potential. Now we're realizing those gains, and we're seeing some real value, but things are also tapering off.

Surely we will have another big breakthrough some day—a further era of AI which brings us closer to something like AGI—but there's just no reason to assume AGI will crop up in 2027, and nothing less that that can produce the ROI that such enormous valuations will eventually, inexorably, demand.
by kolektiv | 2025-11-04 01:50:11+00:00
I was curious about Shakti after reading this and the comments, so followed the link to shakti.com on Wikipedia. It seems it now redirects to the k.nyc domain, which displays a single letter 'k'.

I wondered if I was missing something, so looked at the source, to find the following:

<div style='font-family:monospace'>k

Nothing but that. Which is, surely, the HTML equivalent of the Whitney C style: relying on the compiler/interpreter to add anything implicit, and shaving off every element that isn't required, such as a closing tag (which, yes, only matters if you're going to want something else afterwards, I guess...). Bravo.
by zeroq | 2025-11-04 01:50:47+00:00
Not an expert but I'll drop my 2c

Most of my career was somehow related to graphics programming and I always thought it's bit weird that most quantization algorithms were operating in RGB model despite the fact that it was designed for hardware, not so for faithful color manipulation.

The easiest way to see that is to imagine a gradient between two colors and trying to make it in RGB. It doesn't seem right most of the time.

If so, then why would we consider distance in 3D space between two colors as faithful representation of their likeness?

Well, lo and behold, it's 2025 and everyone finally accepting LAB as the new standard. :)
by kevinsane | 2025-11-04 01:51:34+00:00
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by rglover | 2025-11-04 01:51:35+00:00
SEEKING WORK - Tennessee, USA (Remote)

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I also offer more specific services [4] that focus on using the stack I've built to give you an easy-to-maintain, scalable setup.

I'm also capable of assisting with design, copywriting, and strategy (I just tend to do this as part of my normal work anyways; no surprises or gouging).

I prefer project-based rates and well-scoped work but can be flexible depending on budget and timing.

Contact: ryan.glover@cheatcode.co

LinkedIn: https://linkedin.com/in/ryangglover

[0] https://cheatcode.co

[1] https://cheatcode.co/joystick

[2] https://cheatcode.co/mod

[3] https://cheatcode.co/push

[4] https://cheatcode.co/services
by kylixz | 2025-11-04 01:52:27+00:00
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If you know networking, ATAK, p2p, ROS2 or wireless MANETs please apply. I’m building out a team to apply the technology to life saving markets and need a hand. You’ll own some greenfield development, get out in the field with firefighters, work with UAVs, and ride multicast over cutting edge mesh radios.

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by codingjaguar | 2025-11-04 01:53:21+00:00
This quite aligns with our observation at Milvus. Recently, we helped several users migrate from pgvector as the workload grew substantially.

It’s worth recognising the strengths of pgvector:

• For small-to-medium scale workloads (e.g., up to millions of vectors, relatively static data), embedding storage and similarity queries inside Postgres can be a simple, familiar architecture.

• If you already use Postgres and your vector workloads are light (low QPS, few dimensions, little metadata filtering / low concurrency), then piggy-backing vector search on Postgres is attractive: minimal added infrastructure.

• For teams that don’t want to introduce a separate vector service, or want to keep things within an existing RDBMS, pgvector is a compelling choice.

From our experience helping users scale vector search in production, several pain-points emerge when scaling vector workloads inside a general-purpose RDBMS like Postgres:

1. Index build / update overhead • Postgres isn’t built from the ground-up for high-velocity vector insertions plus large-scale approximate nearest neighbour (ANN) index maintenance, for example, lacking RaBitQ binary quantization supported in purpose built vector db like Milvus.

• For large datasets (tens/hundreds of millions or beyond), building or rebuilding HNSW/IVF indices inside Postgres can be memory- and time-intensive.

• In production systems where vectors are continuously ingested, updated, deleted, this becomes operationally tricky.

2. Filtered search

• Many use-cases require combining vector similarity with scalar/metadata filters (e.g., “give me top 10 similar embeddings where user_status = ‘active’ AND time > X”).

• Need to understand low level planner to juggle pre-filtering, post-filtering, and planner’s cost model wasn’t built for vector similarity search. For a system not designed primarily as a vector DB, this gets complex. Users shouldn't have to worry about such low level details.

3. Lack of support for full-text search / hybrid search

• Purpose built vector db such as Milvus has mature full-text search / BM25 / Sparse vector support.
by archerabi | 2025-11-04 01:54:59+00:00
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by monero-xmr | 2025-11-04 01:56:12+00:00
This website is full of unthinking drones acting with hive mind behavior, that is my contention, and I think very differently, not just on here but with almost everyone I engage with. However I succeed over and over with asymmetric bets on a wide variety of things, including and especially tech and making money in tech, so if we compare bank accounts and career trajectories, investments, etc. it would be wise to let me speak
by DevDesmond | 2025-11-04 01:56:19+00:00
Location: Boston / Somerville MA

Remote: Yes, or Hybrid/In Person

Willing to relocate: No

Technologies: My current favorite stack for building products is with TypeScript, React, (or React Native), PostgreSQL, Vite, Linux (Arch, Debian, or Ubuntu), Bash, and Nginx

Résumé/CV: https://drive.google.com/file/d/1fjHlGavAHEn1CK2-mDI-FPkuLIS...

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LinkedIn: https://www.linkedin.com/in/joshdesmond/

Hello! I'm a fullstack app developer. I can build a product or own features from start to finish. I would love to join your team or help out, whether as a contractor or full time hire!
by seec | 2025-11-04 01:57:19+00:00
But oysters are really not good. It tastes weird with too strong a note of salty water and has a pretty bad texture that makes masticating unenjoyable. They are poor man's food that got super expensive with clever marketing and supply management (and since they need to be alive the supply chain is extremely complicated and expensive, you can't store them for long).

If you live near a sea and can get them dirt cheap why not, but if you live far into the land, they are mostly a waste of good money and a way for pretentious people to appear fancy/rich at the Christmas holiday.
by paxys | 2025-11-04 01:57:46+00:00
By that logic none of us should be paying monthly subscriptions for anything because obviously someone would disrupt that pricing model and take business away from all the tech companies who are charging it? Especially since personal computers and mobile devices get more and more powerful and capable with every passing year. Yet subscriptions also get more prevalent every year.

If Apple does finally come up with a fully on-device AI model that is actually useful, what makes you think they won't gate it behind a $20/mo subscription like they do for everything else?
by JKCalhoun | 2025-11-04 01:57:46+00:00
They might be referring to RTL (resistor-transistor logic). A transistor in the circuit can maintain the same output current that was input. (A transistor in fact a diode and a half.) RTL was superseded by TTL (transistor-transistor logic) but, hey, the Apollo computers that put astronauts on the Moon used RTL logic.

You could start with the late Don Lancster's book [1].

I have a little "breadboard helper" that I am wrapping up (that includes a project manual) for creating RTL circuits and others [2]. (I hope to sell a few.)

RTL book [1]: https://archive.org/details/RTL_Resistor-Transistor_Logic_Co...

Prototyping [2]: https://cdn.bsky.app/img/feed_fullsize/plain/did:plc:oxjqlam...
by satisfice | 2025-11-04 01:57:48+00:00
Homeless people must be so happy now that people acknowledge that they can feel at home without a house to live in. There never was a problem with homelessness, I am sure they would say. (this is sarcasm)

But doesn’t “unhoused” sound a little too much like “unhinged?” Has anyone checked whether being referred to as a “person” might be offensive to men and women and boys and girls who have more specific identities? (this is not sarcastic)
by adlumal | 2025-11-04 01:58:07+00:00
I built a pure-Python port of Stanford OpenIE that GPU-accelerates the natural-logic forward-entailment search itself (via batched reparsing) rather than replacing it with a neural model. This often yields more triplets than standard OpenIE while maintaining the original semantics.

Many neural OpenIE systems train on labels from classical systems. This keeps the classical algorithm but parallelizes the BFS exploration on GPU.
by specialp | 2025-11-04 01:58:30+00:00
The real mover for lower retirement plan fees was lawsuits. There have been loads of 401k excessive fee class action lawsuits and this got almost every employer negotiating to avoid this. Of course there's some plausible deniability in some cases but there is something on the other side against that https://hallbenefitslaw.com/401k-excessive-fee-class-action-...
by Eisenstein | 2025-11-04 01:59:56+00:00
Our tools should not do what we ask if we ask them to do things they should not do.

If it were possible for a gun to refuse to shoot an innocent person then it should do that.

It just so happens that LLMS aren't great at making perfectly good decisions right now, but that doesn't mean that if a tool were capable of making good decisions it shouldn't be allowed to.
by gus_massa | 2025-11-04 02:00:16+00:00
You can sell AR$10 (US$0.007) coins to collectors for AR$3000 (US$2) approximately. They are unofficially out of circulation since 2020 IIRC. (They are in theory still valid, but it's hard to find something to buy with them. Prices are rounded to AR$100 (US$0.07).)
by FroshKiller | 2025-11-04 02:00:42+00:00
Here's the extent of my interest: I take my understanding of your use case and specifications, then I write source code that tries to generate as few instructions to suit your needs as possible while still being comprehensible to the next maintainer.

The app should write records to a database? Fine. Here's where you configure the connection. The app in production is slow because the database server is weak? Not my problem, talk to your DBA.

The app should expose an HTTP endpoint for liveness probes? Fine. It's served from the path you specified. Your reused it for an external outage check, and that's reporting the service is down because the route timed out due to your ops team screwing up the reverse proxy? Literally not my problem, I could not care less.
by skywhopper | 2025-11-04 02:01:52+00:00
Really tired of seeing the story about how, “sure Worldcom et al went bankrupt but their investments in fiber optics gave us the physical infrastructure of the Internet today.”

I mean, sort of, but the fiber optics in the ground have been upgraded several by orders of magnitude of its original capacity by replacing the transceivers on either end. And the fiber itself has lasted and will continue to last for decades.

Neither of those properties is true of the current datacenter/GPU boom. The datacenter buildings may last a few decades but the computers and GPUs inside will not and they cannot be easily amplified in their value as the fiber in the ground was.
by richardfeynman | 2025-11-04 02:01:59+00:00
Actually, in this case I expect you to reject common law standards you would otherwise embrace: the right to a fair trial, the presumption of innocence, the writ of habeas corpus, standards of evidence, etc., and instead to rely on your instincts and feelings. It feels nicer for many to think like a medieval peasant than an enlightened liberal when it comes to Israel and the Jews.

Nor am I surprised by your antipathy to Israeli courts, despite the fact that Israel’s courts rank highly on independence and rule-of-law lists, are broadly regarded as independent and capable of delivering fair process. Bodies that effectively vouch for this include Freedom House, global rule-of-law datasets (e.g., the World Bank WGI), and the practical trust reflected in extradition arrangements with other western countries.
by zeroq | 2025-11-04 02:02:06+00:00
It's not a contradiction if you assume that (a) language choice is critical and (b) rewrites are doomed to be failures.

Having that said I agree that language/platform is a "non technical requirement" in 90% of real world cases. You pick what you know or in more industrious scenarios - what's available on the market or what's the most cost effective.

But people are indeed irrational about programming languages. There's tribalism, stereotypes and preconceptions. Most notable is probably PHP, language for human failures and shit projects. As if same exact project written in Java was suppose to be of higher philosophical value.

But it's something you can't deny. I've been asked in non ironic way by a (non technical) founder investor if I could recommend him Rails programmers, because he read about it and it's suppose to be great. I asked him about specifics of his new project and he said he doesn't have an idea yet, but it has to be in Rails. Go figure.
by zetier | 2025-11-04 02:03:09+00:00
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