MurphyA/hacker-news huggingface dataset:
by kennywinker | 2025-07-17 23:27:52+00:00
My comment was two words. Not meant to “interrupt” or “distract” - idk how one could even interrupt in a comment thread - I posted 7 hours after you, were you mid-sentence?? Like I said, I just meant to gently correct your misgendering and misspelling. Two words. So relax, maybe consider learning to take criticism a little better?

I haven’t added anything about the matrix movies because I think you’re quite far off, and you’ve reacted to pushback terribly. But, I’ll give you a direct response to your point if you’d like? imo the social commentary in the matrix is present and abundant, it’s just aimed at a higher (lower?) level than the kind of “corporations are corrupt” or “ads are bad” social commentary that’s easiest to name as social commentary. It’s about questioning the fabric of your personal reality: your job, your home, your government, your gender, your name. The idea is that these things are a shared illusion, and can be a cage if we let them. Some of that is a cage imposed by ourselves (“I am a software developer”), some of that is a cage imposed by others (“the wachowski brothers”). If that isn’t social commentary, idk what is.

But I didn’t respond to your message because I disagreed with you - i responded because “someone is wrong on the internet” (https://xkcd.com/386/)
by gabesullice | 2025-07-17 23:27:54+00:00
"So... Taxes?"

If we're talking about wealth not income, then no, not really. We don't usually think of asset seizure as "taxes". In other words, one "taxes" flows (like capital gains and wages) and "siezes" stocks (like bank deposits and equity).

"You seem to be positing that it's entirely expected and understandable"

I wasn't making value judgement, but yes, if you look at it with the assumption these wealthy individuals are cold, calculating, self-interested actors, then it's "expected and understandable" to me.

"That seems counterintuitive to me, at least."

I think you're using "intuitive" as a shorthand for "the way things ought to work in a righteous world", where I find incentives and disincentives to be a more intuitive way of understanding the world.

"wealthy individuals in well functioning systems should commit fraud to the detriment of the system that brought them their wealth"

To be fair, it's not necessarily fraudulent to have offshore accounts or to conceal your identity (it can certainly be depending on the circumstances). Technically I have an "offshore" account, I just happen to be living outside the US and a US citizen. I also use mechanisms to conceal my identity when registering domain names, for example. Is it the same thing, no, but these people might not technically be doing anything illegal.

It isn't necessarily true that those systems "brought them their wealth" either. Plenty of them likely inherited wealth that was accumulated long before the current systems were put in place (granted, it could very well have been accumulated illegitimately 300 years ago).

(Again, I'm not saying any of this is how the world should work, I'm trying to look at the world dispassionately and describe how things seem to be)

At the level of wealth we're discussing, these individuals probably have to think about "diversifying" among nation-states. Instead of worrying about whether to short the tech sector, they're worried about a country being invaded and the new puppet regime deciding to nationalize the hydroelectric dam they financed. Or they may be worrying about whether their country of residence will pass a law that the biggest national telcom must sell the government a majority stake (i.e., their share) at a government-mandated price denominated in an inflating currency... with expert bureaucratic efficiency.

So... no, not really taxes.
by const_cast | 2025-07-17 23:28:01+00:00
Side note: but this is also why online privacy matters. If there's little to no data on you, you will appear as a new customer, and you can get really sweet deals.

Use a new browser session, use something like Tor that protects you from fingerprinting, poke around on a VPN, try changing your user agent. Don't log into anything. This is the ideal way to shop.
by alphager | 2025-07-17 23:28:23+00:00
Even if Moore's law was still in effect and the computer resources required stayed the same and compute stayed as efficient per watt (neither is true), it would just halve compute costs every 18 months. You're able to read about people hitting $4000 costs/month on the $200 plan upthread. That's 8 years until it's cost effective.

Are they really ready to burn money for 8 years?
by tomhow | 2025-07-17 23:29:00+00:00
It's a misconception that most HN users are startup founders taking investor funds.

Most HN users are tech employees or freelancers on salaries or contractor fees, so whatever political slant HN has aligns with that.

Posts about the U.S. administration and tech celebrities get flagged because people try and submit them every day and they lead to repetitive flamewar discussions, which is everything that HN is trying to avoid.
by JKCalhoun | 2025-07-17 23:29:15+00:00
> I can spot AI writing very quickly now, after just a few sentences or paragraphs.

Not denying this is true — but like a lot of what we've seen with AI, lets see how you feel in two years time when the models have improved as much.

I think it was actually Brian Eno that said it (essentially): whatever you laugh about with regard to LLMs today, watch out, because next year that funny thing they did will no longer be present.
by zahlman | 2025-07-17 23:30:13+00:00
> The reactive ingredient is passion, not the learning modality.

Sure, but passion also drives self-teaching. It's less necessary in a classroom setting because there's always someone trying to keep you on track.

> Self-taught approaches tend to be goal oriented (I'm learning X because I want to do Y), which can overlook fundamentals that are important.

For some, understanding a system can be a goal in itself.
by random3 | 2025-07-17 23:30:21+00:00
They likely outperform for the same reason they are self-thought— i.e. it's most likely a confounder. If you have enough curiosity/pull, motivation, discipline to do it, you'll outperform in general, self-thought or not.

There's also a survivor bias at play, in the sense that the self-teaching attempts results that you see in professional environments are those that made it. So, the true question is, for those that tried this path and failed, would have they been better off with proper teachers. Sometimes it may just be a matter of time - taking longer to learn because of various reasons, that wouldn't be the case in normal educational environment.

With this said, I went through CS and math school and enjoyed it, but I don’t think I’m compatible with the format and prefer self learning.
by canpan | 2025-07-17 23:30:37+00:00
> Yet, I can’t escape the fact that it’s better reading than what I write

I worry we will have a lot less good writers or artists in the future. Everyone starts bad, without the skill. The hurdle is, why should I put in effort to learn, if AI is already somewhat good.

Someone mentioned here before, we learn to judge skill before we can learn the skill itself. The drive to jump the gap is what creates the genius.

Please don't give up, you can do it!
by kevinmpeterson | 2025-07-17 23:31:39+00:00
Probably - if cost goes down to operate a machine, then the base machines can be smaller. Will eventually be interesting to go for much bigger changes... ditch the cabs, lower profiles, place your cameras in smart spots, move the pivot points so they are best for the job instead of best for a person. Vehicle distribution might change, too - heavy machines are tools and the tool you choose is a combo of best quality, right cost, speed, etc. That landscape will shift.

The variety of machines and their specificity is super fascinating and very specific. Definitely will change.
by austin-cheney | 2025-07-17 23:31:43+00:00
That depends entirely on the business and the experience of the given developer. There is a false perception that inventing an original solution is high risk. Risk is accounted for by the prior practice of the person doing the work and the degree of testing upon that work. This common false perception is Invented Here Syndrome.

In some cases it makes more sense to the business to approach an original solution as determined by external constraints in the project, such as eliminating dependencies, achieving a superior performance target, or unique security constraints.

Usually the primary concern in the big corporate world is hiring and firing, everything else be damned.
by godelski | 2025-07-17 23:32:05+00:00
True, but I find that highly problematic.

It's not a good system if it's hard to differentiate. We should be encouraging making money by providing meaningful value to the people buying the product. To get those things aligned. I think we engineers can play a role too. While not having the ultimate decision I think speaking up and just pushing here and there to prioritize product quality over profits goes a long way. In the long run, I think quality and profits are usually aligned, though I think rarely in the short term
by b112 | 2025-07-17 23:33:07+00:00
LLMs don't think, nor are they intelligent or exhibiting intelligence.

Language does have constraints, yet it evolves via its users to encompass new meanings.

Thus those constraints are artificial, unless you artificially enforce static language use. And of course, for an LLM to use those new concepts, it needs to be retokenized by being trained on new data.

For example, if we trained LLMs only on books, encyclopedias, newpapers, and personal letters from 1850, it would have zero capacity to speak comprehensibly or even seem cogent on much of the modern world.

And it would forever remain in that disconnected positon.

LLMs do not think, understand anything, nor learn. Should you wish to call tokenization, learning, then you'd better call a clock "learning" from the gears and cogs that enable its function.

LLMs do not think, learn, or exhibit intelligence. (I feel this is not said enough).

We will never, ever get AGI from an LLM. Ever.

I am sympathetic to the wonder of LLMs. To seeing them as such. But I see some art as wonderous too. Some machinery is beautiful in execution and to use.

But that doesn't change truths.
by slwvx | 2025-07-17 23:33:11+00:00
I live in Silicon Valley, and am generally happy with my tiny contribution to the tech space. Even so, I detest the use of "Silicon Valley" as a label for every good or bad thing that Elon Musk (who doesn't live or work in SV) or some other well-known tech person comes up with.

I'd like an article on "The Washington press push to create click-bait" to see what people in Washington say.
by sadcodemonkey | 2025-07-17 23:33:19+00:00
I've found that there's greater range among CS graduate software engineers. Of course there are some truly excellent thinkers who know how to bring their training to bear on all kinds of problems. But some of them, well, you wonder how they even graduated college.

Among the self-taught, there's less variation. If they've managed to land a first job, they're usually at a pretty decent level of knowing how to learn new skills and apply them to solving problems. They were born in the "real world" instead of in the classroom, and it usually shows up in their sensibilities.

Just what I've observed from my own experience. (I'm self-taught myself.)
by toss1 | 2025-07-17 23:34:58+00:00
NO

This is not "price discovery working efficiently" in arm's length transactions among two equal trading partners.

This is MAXIMUM_VALUE_EXTRACTION working efficiently between one player with all the power and information and another player with none of the power and information.

This is nothing more than a scheme to figure out what is the maximum amount of money they can extract for the transaction, for every single party. And, as pointed out in the article, the poor will get shafted even harder because they have fewer options, whereas the wealthy cardholders (who least need the deals) will get better deals because they have many options.

How is it that you are unable to see this is a scheme to screw everyone, and you in particular (for all possible values of you)?
by ammiranda | 2025-07-17 23:35:03+00:00
Jeopardy Archive Trainer – Practice with 200K+ real questions + LLM answer validation I built this as a trivia obsessive who wanted better practice than the existing online tools. It generates authentic Jeopardy rounds from the full historical dataset and uses LLMs to handle answer validation intelligently. The interesting technical challenge: Traditional string matching fails spectacularly for Jeopardy answers. Users might answer "France" when the correct response is "What is France?" or vice versa. Even worse, there are valid variations like "French Republic" or abbreviations. I solved this by integrating both Ollama and OpenAI for semantic answer comparison.

Stack:

- FastAPI backend with SQLite (200K+ questions from Kaggle) - React frontend with responsive game UI - Docker containerization with automatic model pulling - Supports both Ollama (local) and OpenAI for answer validation - Fallback to string comparison if no LLM available

Features:

- Generates realistic Jeopardy/Double Jeopardy/Final Jeopardy rounds - Smart answer validation that understands context and variations - Score tracking and clean game interface - One-command Docker deployment

Had to architect the LLM integration to be provider-agnostic since Ollama performance on my hardware wasn't optimal. The backend automatically switches between OpenAI and Ollama based on environment configuration, with graceful fallback to string matching if neither is available.

Currently using this for my own practice and it's been way more effective than memorizing question banks. The LLM validation makes it feel like playing the actual game.
by cdrini | 2025-07-17 23:35:40+00:00
Hmm I don't think a universal language is implied by being able to translate without a rosetta stone. I agree, I don't think there is such a thing as a universal language, per se, but I do wonder if there is a notion of a universal language at a certain level of abstraction.

But I think those ambiguous cases can still be understood/defined. You can describe how this one word in lion doesn't neatly map to a single word in English, and is used like a few different ways. Some of which we might not have a word for in English, in which case we would likely adopt the lion word.

Although note I do think I was wrong about embedding a multilingual corpus into a single space. The example I was thinking of was word2vec, and that appears to only work with one language. Although I did find some papers showing that you can unsupervised align between the two spaces, but don't know how successful that is, or how that would treat these ambiguous cases.
by lores | 2025-07-17 23:36:31+00:00
Life isn't a zero-sum game, and individually profit-maximising actions may not be in even the profit maximiser's interest long-term, let alone society's.

In the European Antiquity and Middle-Ages, at least, there were laws against merchants taking too much profit. It didn't matter if a high price optimised the allocation of a resource - the gouging was seen as more deleterious to society than the inefficiency, and malefactors were punished harshly, with heavy fines or even exile or death.

I feel like we're due for a medieval revival.
by ben_w | 2025-07-17 23:37:15+00:00
Zig when others zag. This too shall pass, and will be forgotten.

Flash websites no one watched. Carousels. Consultants saying "we need a viral". Every product needed a MySpace page, to be prefixed with an "i", or to have most vowels removed. Blue-and-orange film posters.

All those trends will be lost in time, like tears in rain.
by mattigames | 2025-07-17 23:37:38+00:00
I don't think that AI being somewhat good is the main stopper, it's that we know for certain that it will improve at a giant pace, the very same prompt that triggers a mediocre book today will trigger a good book tomorrow (as an aside, I firmly believe that the word "trigger" is way more apt than "create" when talking about AI output), there is billions of dollars invested to make sure of that, and is not like we haven't seen unbelievable leaps already for art generation.
by jksmith | 2025-07-17 23:37:52+00:00
I think the bias noose has tightened a lot over the years, so we don't avail ourselves to experiement like we used to - no chance for critical mass now that the profession has become so commoditized. It was wide open when I first started and devs were using all kinds of toolchains. The most money I've ever made selling applications (in today $) was from a TP (DOS) then later Delphi (Windows) codebase. Way back in 1991 I remember having a cigar with a client in SF and the dude wrote me a 70k check right there on the bar. What a huge thrill for me that was. Wild west of price and value discovery, which has totally disappeared.

One thing I do believe: the quality of software from MSFT has gone down, in part because their business model has gone from providing products to monetizing the users. Their products are just stagnant honeypots to collect data. This is opening a door for the small time dev to try new things, maybe with unpopular toolchains. I've got something that would be great for highlighting Ada's mission critical rep. Price and value discovery aren't dead (yet).
by impish9208 | 2025-07-17 23:38:09+00:00
Sounds like a product description out of the J. Peterman catalog.

Lorca wrote here, Picasso sketched here, Buñuel and Dali schemed to shock the world here. Even today, you'll still find ideas hanging in the air at Madrid's Cafe Gijon-along with the pungent smoke of Ducados. Stir sugar into your cortado and watch the room unfold in the nearest mirror. There are so many, reflecting into each other, you can see everything from one spot. Are those young ladies debating García Márquez? It's perfectly acceptable to stroll over and get involved. All it takes is confidence-and this jacket. Spanish Café Linen Blazer.
by trog | 2025-07-17 23:38:43+00:00
Maybe we should define our terms then? I favour this definition of "ur-fascism" by Umberto Eco: https://archive.is/VamLM

To steal a few examples from a convenient summary list someone[1] made:

1. The cult of tradition. “One has only to look at the syllabus of every fascist movement to find the major traditionalist thinkers. The Nazi gnosis was nourished by traditionalist, syncretistic, occult elements.”

2. The rejection of modernism. “The Enlightenment, the Age of Reason, is seen as the beginning of modern depravity. In this sense Ur-Fascism can be defined as irrationalism.”

3. The cult of action for action’s sake. “Action being beautiful in itself, it must be taken before, or without, any previous reflection. Thinking is a form of emasculation.”

4. Disagreement is treason. “The critical spirit makes distinctions, and to distinguish is a sign of modernism. In modern culture the scientific community praises disagreement as a way to improve knowledge.”

...

10. Contempt for the weak. “Elitism is a typical aspect of any reactionary ideology.”

Open to other definitions. But I look at that list, written in 1995, and it feels like you can check off a lot of these items in things that are rapidly being normalised.

1. https://www.openculture.com/2024/11/umberto-ecos-list-of-the...
by whstl | 2025-07-17 23:38:46+00:00
This is gonna sound like an old man yell at clouds post but...

I also remember university being great. I built a compiler, a toy OS and interfaced with GPS.

But a few years ago I was invited to teach on another university and I was very disappointed. The curriculum was basically a modern bootcamp stretched over a few years with a lot of unrelated classes sprinkled in. (EDIT: I just checked it and: lots of business, management, humanities, chemistry, environment, entrepreneurship... and one e-sports class?).

Almost no fundamentals, except for an algorithms class, almost straight to React and a few backend frameworks that were popular in the startups in the area.
by benlivengood | 2025-07-17 23:39:22+00:00
You also can't translate "Mage (foaled April 18, 2020) is an American Thoroughbred racehorse who won the 2023 Kentucky Derby" into Hellenistic Greek or some modern indigenous languages because there isn't enough shared context; you'd need to give humans speaking those languages a glossary for any of the translation to make sense, or allow them to interrogate an LLM to act as the glossary.

I'd say our current largest LLMs probably contain sufficient detail to explain a concept like a named race horse starting from QCD+gravity and ending up at cultural human events, given a foothold of some common ground to translate into a new unknown language. In a sense, that's what a model of reality is. I think it's possible because LLMs figure out translation between human languages by default with enough pretraining.
by jug | 2025-07-17 23:39:46+00:00
Yeah honestly I'm just waiting for Mistral Large 3. They've hinted about it. It's probably going to become the new language model in Le Chat, and imminent:

From the "One more thing" on the Mistral Medium 3 blog post in May:

> With the launches of Mistral Small in March and Mistral Medium today, it’s no secret that we’re working on something ‘large’ over the next few weeks. With even our medium-sized model being resoundingly better than flagship open source models such as Llama 4 Maverick, we’re excited to ‘open’ up what’s to come :)

That version ought to close the gap to large top models today enough to not matter much anymore. And the Cerebras speed will/does make it feel awesome compared to ChatGPT.
by _def | 2025-07-17 23:39:50+00:00
I think it is possible to create art with so called AI. Just not in the way people usually tend to think or expect. Imitating what already exists gives you slop. But used as tools, you can try to create pieces of art that are genuinely valuable. It's just not making it easier. It's more difficult if anything. But not impossible. And some people trailblaze with it.
by roadside_picnic | 2025-07-17 23:40:15+00:00
What's unfortunate is that there aren't enough people pushing LLMs to assist in writing in creative ways that really involve messing with the model.

I'm a huge William S. Burroughs fan, and, for those unfamiliar, he and a few others invented an algorithmic technique, the "Cut-up technique" [0], to basically remix their writing. It's a major part of the reason that much of Burroughs' work as a magically confusing aspect to it.

"Prompt and pasting" from LLMs is dull, but awhile back I was experimenting with token-explorer [1] to see what would happen if I started with a prompt and explored the "high-entropy" states of the LLM. By controlling the sample path to stay in a high-entropy state you start getting very different types of responses that feel like nothing that normally comes from an LLM. You could argue it's a form of "statistical automatic writing" [2]

There is tremendous potential for genuinely interesting writing to be created with an LLM but it's going to require popping open the box and playing around. In the Stable Diffusion world there's lots of people trying all sorts of odd experiments to create things and, while not the mainstay of generative AI images, they are able to create really interesting things.

I would love to see more people ripping open local LLMs and seeing just what the real posibilities are.

0. https://en.wikipedia.org/wiki/Cut-up_technique

1. https://github.com/willkurt/token-explorer

2. https://en.wikipedia.org/wiki/Automatic_writing