skysight-inc/HackerNews huggingface dataset:
> I’m not against Tailwind, but I didn't used it yet because I struggle to see why it's a better approach compared to other options like Web Components or React Styled Components.

> The biggest issue I have with Tailwind is how it clutters the HTML

You're 100% clearly in the first group. Maybe I shouldn't have said "hate" in that group, just people that don't like it or see its benefits.

> Like Web Components

That's a nice solution, but in practice as of today and relatively speaking: nobody is using them.

> and Styled Components

Except the performance is a lot worse. And you still have to come up with names for every single div that needs a minimal one line style.

And both of these solutions end up with huge CSS files. Huge CSS files are worse than having larger HTML markup, because CSS is a blocking resource and HTML is not.

> I really value keeping HTML very short and readable by not mixing presentational styles directly in the markup

People used to say this about React, they preferred their HTML separate from their JavaScript, all nice and clean. I'm now 150% sure you're in the first group.

> Yes, I've read the docs but never tried it out, I don't hate it, but I can't understand why I would choose it over other options. The fact of having a million classes in the middle of plain HTML makes them both unreadable for me.

Alright, now you've recognized it.

> These two approaches allows me to not have to read presentational things in the middle of my html, and allow my html to be more clear and readable.

That's a non issue. There are extensions that will just hide classnames. You're just blending your mind looking for reasosn to justify your "I don't like it".

I promise the day you use it in a real life project where you're working with > 3 other people you will understand it's benefits, and how having "large class lists" is a non-issue and a totally acceptable trade off over the practical benefits it provides. Both on performance of the resulting CSS and maintainability over a large period of time. And think in the insane amount of discussions you'll avoid regarding if we're calling this div "styledDivWrapper" or "WraperContent" or "CardWrapper" or ".card__item--dark". Not an issue if you work alone, but when working with others this becomes a real annoyance that tailwind completely removes.

Tailwind is not for your, don't use it.

Tailwind is not for purists and architecture philosophers.

Tailwind is for pragmatic people, working on real life projects within teams where they have to ship and spend less time philosophizing on the purity and beauty of things.
Worth noting that people have been unpacking and analyzing DeepSeek-R1 vigorously for days already on X before it got to Hacker News — it wasn't always this way.
Laos is not in the "other direction" to Yunnan; Laos borders Yunnan.
You have a valid point, to which I'll concede. The rule book gives an example (spanning pages 4-5) where a guesser uses prior clues to select a card while the count is still within the number stated by the spymaster, but I suppose an allowance for guessers to deviate in this way does not also imply that spymasters may deviate in this way. Mea culpa!

Taking this a step further, given that it's well-known that a clue is deemed invalid when it pertains to cards in certain non-definitional ways (sounds-like, number of letters, etc.), it seems extremely reasonable to call a clue followed by N invalid if it doesn't pertain to N cards in a definitional way.
If you can strap visual, audio and touch sensors onto them and they can genuinely start improving themselves based on the that raw input, then we have a general intelligence.
No natural reservoir of covid has been found. Ergo it's not natural.
> don’t see why seeing an ad next to some content would cause me to think differently about the contents of the ad.

If that didn't happen, I imagine enough of the global $1 trillion-plus industry would have noticed by now, and already adjusted their strategies to exploit the under-valued placements.
The nVidia market price could also be questionable considering how much cheaper DS is to run.
Do you still use spinal? Have there been other advances in HDL that you've seen over the last 6 years?
There has never been much secret sauce in the model itself. The secret sauce or competitive advantage has always been in the engineering that goes into the data collection, model training infrastructure, and lifecycle/debugging management of model training. As well as in the access to GPUs.

Yeah, with Deepseek the barrier to entry has become significantly lower now. That's good, and hopefully more competition will come. But it's not like it's a fundamental change of where the secret sauce is.
I was an "operator" on a Tandem NonStop. First was Pitney Bowes, I preferred the night shift. In the computer room, there was a Tandem, and a UNIVAC. My job was mostly swapping disk packs on the Tandem, and swapping tapes on the UNIVAC.

One of my jobs was to shutdown the dialup system (customers mailing machines would send data about the mailings they made overnight). I had to shutdown the dialup lines according to the time zones across Canada. I decided to write a script to automate it. My script would shutdown each phone line in order. The first time I ran it, I "broke" the Tandem. My script was a basic loop. It would check the time, and shutdown one of the timezones. First time I ran it the Tandem "mainframe" froze. I had to call "Doug" in the middle of the night, I was freaking out. Doug came in, looked at my script and quietly pointed out that the time command was a high priority system. My script didn't have any "waits" in it, the loop I wrote was constantly asking the system the time, taking up 100% of the processing. "Doug" had to reboot the Tandem, and after the "wait" was put into my script, all was good.

After I left Pitney Bowes I was an operator at the OPP (Ontario Provincial Police), that system had the OMPPAC system on it (Ontario Municipal Police Automated Cooperative), The criminal database for the Province of Ontario.
You gotta get over your deal about Porsches and money. Get some therapy or something, yo.

As far as LLM introspection goes, it's a hot area of research. Just because you don't see any finished products on the market at this time doesn't mean that people stopped caring or that no one does. The Golden Gate Claude experiment shows there's some really interesting parts to delve into.
How do you query your iceberg tables? We are looking into moving away from Bigquery and Starrocks [1] looks like a good option.

[1] https://www.starrocks.io/
I mean, you talk about a predictable, deterministic next-token generator...
YC Graveyard: 821 inactive Y Combinator startups
I don't get this whole debate, surely what's meant by "reason" can be strictly defined and measured? Then we can conclusively say whether or not it's happening with LLMs.

It seems to me like the debate is largely just semantics about how to define "reason".
Do lawnmowers count?
So, 2?
It was France:

https://www.businessinsider.com/french-california-high-speed...

Doubly delicious since the French have a long and not very nice colonial history in North Africa, sowing long-lasting suspicion and grudges, and still found it easier to operate there.
It should be. I think AMD has left a lot on the table with respect to competing in the space (probably to the point of executive negligence) and the new US laws will help create several new Chinese competitors. NVIDIA probably has a bit of time left as the market leader, but it's really due mostly to luck.
The benchmarks for the different models focus on math and coding accuracy. I have a use-case for a model where those two functions are completely irrelevant and I’m only interested in writing (chat, stories, etc). I guess you can’t really benchmark ‘concepts’ as easily as logic.

With distillation, can a model be made that strips out most of the math and coding stuff?
What are AI Agents? [video]
Full multimodal Android llm app running without netowrk
>- the human in the room is also important. LLMs are like pianos, we play prompts on the keyboard to them, and they play back language to us. The quality and originality of the output aren't solely inherent to the model, but are co-created in the dialogue with the prompter. It's not just about the instrument, but also the 'musician' playing it.

I mean isn't that what humans are as well? You can get two LLMs talking to each other and suddenly the musician in the room doesn't matter.
Are the any plans to add local models? Ot tools only work with openai and claude?
The prompt in table 1 makes it very likely that the model will use the correct format. The pretrained model is pretty good so it only needs to stumble upon a correct answer every once in a while to start making progress. Some additional details in the Shao et al, 2024 paper.
The word you're looking for is copyright enfrignment.

That's the secret sause that every good model uses.
I take it you have some gripe with https://www.scryer.pl/clpz? Could you explain in more detail?
Ask HN: What is this devious Chrome throttling?
This is a question I wouldn't ask on S.O because no one would know what I was talking about. Here goes:

I'm messing around building a CPU pixel blitter, for fun. Here's a tiny demo:

https://thestrikeagency.com/ktest/dist/

I ran into lots of problems when I tried to run these draws on a setTimer, so I built a simple [actual, delta-based] timer.

If you watch it in Chrome, you'll see draws take ~5ms for the first 3 seconds, then throttle to 15ms for the next 50-60 seconds. Then all by themselves if you leave it running that long, they decide to go back to 5ms. If you background the window, it stays throttled for 50 seconds after you put the window in front.

I was aware of Event throttling and aware setTimer throttling. But this is running off Promises finished at the end of each iteration. (The code is unobfuscated if you want to look). Is Chrome throttling async/await ... based on user interaction?

Once Chrome decides I've kept it open for a full minute, it pegs at 60fps and doesn't drop again.

Does anyone know: What is this alchemy, and how can I prevent Chrome from throttling it for seconds 3 to 60 ?

[EDIT] VERY importantly: If you reload the tab, the throttling does not happen! It starts fast and stays fast after a reload. It only throttles if you close the tab and open it anew. Which is even weirder. Chrome remembers not to throttle a script after you reload it?!
Neuroscience and evidence be damned, [the brain is a computer] is being transformed into [the brain is an LLM]. Happens with every new technology.

Edit: What is happening with people these days? They seem to be reducing people and their minds to machines more easily than ever.
Elon Musk complains about China's ban on X
[deleted due to controversy]
As we have seen here it won't be a Western company that saves us from the dominant monopoly.

Xi Jinping, you're our only hope.
Thanks—I think that's the story I was remembering.

If I'm getting this right, these are two different stories involving different pilots and different aircraft but they happened on the same day! (April 29, 1975)
You want to talk evidence, let's talk evidence. What does the brain do that these models don't (or, more generally, can't)?

Be specific.

And no, it doesn't "happen with every new technology." Nothing even remotely like this has been seen before the present decade.
This was a really interesting read, thanks.
I think you’re underestimating people who do this.
It does not work fine on Github.
It's semantics. But there's a general motivation behind it that's less technical. Basically if it can reason, it implies human level intelligence. That's the line separating man from machine. Once you cross that line there's a whole bunch of economic, cultural and existential changes that happen to society that are permanent. We can't go back.

This is what people are debating about. Many many people don't want to believe we crossed the line with LLMs. It brings about a sort of existential dread. Especially to programmers who's pride is entirely dependent upon their intelligence and ability to program.
Ultimately, we don’t know the actual benefits and I just picked numbers from thin air to illiterate a point. But yea linear extrapolation of such estimates hundreds of years into the future is nonsense.
My mental model for chain-of-thought is not “reasoning”. It’s more of an iterative search through the latent space of the model.
I must be missing something, but I tried Deepseek R1 via Kagi assistant and IMO it doesn't even come close to Claude?

I don't get the hype at all?

What am I doing wrong?

And of course if you ask it anything related to the CCP it will suddenly turn into a Pinokkio simulator.
One would think the endgame entities have better things to do.
If China really released a GPU competitive with the current generation of nvidia you can bet it'd be banned in the US like BYD and DJI.
>I find it curious that you associate terms like "rugged", "vegan" and "compassionate" with a particular leaning on the political spectrum.

I find it curious that you didn't bother to watch the linked video which contains the aforementioned satire.
The biggest reasons I read here for SaaS/subscription are "updates"

ie. "We shipped early something with loads of bugs we intend to fix as you pay us" vs the model of "We make sure things work first time bug free" of days gone past... but then yeah... things changed and become too complex
I don't disagree, but the important point is that Deepseek showed that it's not just about CapEx, which is what the US firms were/are lining up to battle with.

In my opinion there is something qualitatively better about Deepseek in spite of its small size, even compared to o1-pro, that suggests a door has been opened.

GPUs are needed to rapidly iterate on ideas, train, evaluate, etc., but Deepseek has shown us that we are not yet in the phase where hardware CapEx guarantees victory. Imagine if Deeepseek hadn't been open sourced!
I've never seen a polar bear. Ergo they don't exist.
LLMs and Unix Timestamp
Hello, I've tried requesting different AIs to convert 1737873496 into a readable format, but it turns out that it's not an easy task.
> What does this post have to do with "hacker" news?

https://news.ycombinator.com/newsguidelines.html

> critical comments [...] outright silly propaganda comments

I'd need to see specific links to say anything about them.

> while you essential pin this thread on the frontpage

Nobody pinned anything. The thread is ranking on the frontpage because it got plenty of upvotes.

Could you please stop flaming now? You've been doing way too much of that, and not only in this thread.
I used to look down on ChatGPT and other LLMs because they're crazy expensive to train and need special tuning like SFT/RLHF. I thought their "intelligence" was limited and economically impractical — good for assisting but not replacing humans. At best, they might take over some customer service, translator or teaching jobs.

But now, with R1 out there, I'm getting a little nervous, kinda like when Go players saw AlphaGo. Sure, AlphaGo didn't replace humans, but Go is a game, not work.
Companies won't hire AI to play games, but they'll absolutely use bots to code software and build cars.
You’ve got 88 in your name bro DON’T look into that
This is one of my favorite YT channels working on a similar research without all the fluff: https://www.youtube.com/@ArtemKirsanov

Also have a look at Michael Levin's work : https://www.youtube.com/results?search_query=michael+levin
I guess that's the thing: I can't imagine wanting to automate a light switch. There are plenty of practical things to automate. For example, window shades for passive solar heating (or the prevention thereof), hvac, hell I think it would be awesome to have a temperature sensor in my utility room and machinery to "scram the reactor" (shut off the well pump and drain all the water pipes) if the temperature drops below 34°F. But light switches?

Sibling comments suggest automatically turning on/off lights if someone is expected to arrive or depart, but wouldn't that person just think "weird, they left the lights on"?
Basically engineers are rejoicing, some VC connected C-levels are saying “nah, CCP helped them”. It’ll be fun if DS team gets proven right. Everyone will be back to the drawing board. It’s making a bit of news within China as well, as Baidu, Tencent, Bytedance are also spending a lotta money for AI training.
I would expect the query plan for SQL server to essentially return records matching `id` first (which again should be a situation where uniqueness comes into play) and then performing the rest of the execution on the subset that matches, which is hopefully one.

I leave allowances for `id` to be a stand-in for some other identity column that may represent a foreign key to another table. In which case I'd still expect SQL server's query planner to execute as: initial set is those where said column matches the supplied number, then further applies the logic to that subset. In fact I'd love to see where that isn't the case against a transactional DB.
NDV = Number of distinct values. Here partitioning on high cardinality columns, essentially.
Wow, I initially thought that the first dialog box was a screencap of a "real" one...

Impressive!
Indeed, a good Codenames-playing bot should know how to do all of this, in addition to using its LLM to generate great clues.
Right. I stand corrected and it makes sense. I may have misunderstood the OP. It would not make sense to encode each unicode point as a token and then start training the subword tokenizer on top unless we go to the vocabularies of many millions.
True, and likely lots of other data that should not have been used to train a model.

It is at this point hard to imagine a model that is good at reasoning that doesn't also have vast implicit "knowledge".
Theoretically, a lab leak should be considered less embarrassing than a hick selling wild animals perfectly legally - wet markets that sell even wild animal meat are legal in China (and other places in the world) in spite of the known dangers of this practice. And people making a mistake while intentionally working with dangerous substances/organisms is also seen as more explicitly culpable than the more distributed blame of people allowing a known dangerous traditional practice to continue, wherein the participants are not aware that they are performing dangerous experiments.

But of course, there is considerable bias to view traditional practices like wet markets more favorably than modern practices like virology labs. So, in reality, the virus leaking from a virology lab would be found far more condemnable than the virus being contracted randomly at a wet market.
There's a sort of existential dread once man has created a machine that can perform on par with man himself. We don't want to face the truth so we move the goal posts and definitions.

To reason is now a human behavior. We moved the goal posts so we don't have to face the truth that AI crossed a barrier with the creation of LLMs. It doesn't really matter, there's no turning back now.
AGI would be able to replace those workers, at which point they aren't essential anymore.
Cool repo—thanks!
> certain types of non-native english always have a feel to them which reflects the mismatch between two languages

This. My partner always speaks frenglish (french english) after talking to her parents. You have to know a little French to understand her sentences. They’re all English words, but the phraseology is all French.

I do the same with Slovenian. The words are all English, but the shape is Slovenian. It adds a lot of soul to your words.

It can also be topic dependent. When I describe memories from home in English, the language sounds more Slovenian. Likewise when I talk about American stuff to my parents, my Slovenian sounds more English.

ChatGPT would lose all that color.

Read Man In The High Castle to see this for yourself. Whole book is English but you can tell the different nationalities of each character because the shape of their English changes. Philip K Dick used this masterfully.
[I typed something dumb while half asleep]
Has anybody listened to this podcast episode? https://www.youtube.com/watch?v=5d-eqdRSx7Y&t=1s

Curious to have a discussion on this with anybody knowledgeable on the topic.
I haven't tried kagi assistant, but try it at deepseek.com.

All models at this point have various politically motivated filters. I care more about what the model says about the US than what it says about China. Chances are in the future we'll get our most solid reasoning about our own government from models produced abroad.
Wasn't he just telephoning Berlin telling people not to feel bad about their history of xenophobia?

https://www.politico.com/news/2025/01/25/musk-german-afd-ral...

So Germany should close their doors and China should open theirs... all in the same day, eh?
You didn't include any of that information above—you just made a denunciatory flamewar comment. That's what we're asking you not to do.

If you had posted this later comment originally, it would have been fine, or almost fine—it's probably still too much of a political battle post to be completely fine.
The most sensible and pragmatic advice in this thread.
Let me qualify your statement... CapEx is what EXISTING US firms were/are lining up to battle with.

With R1 as inspiration/imperative, many new US startups will emerge who will be very strong. Can you feel a bunch of talent in limbo startups pivoting/re-energized now?
>They should work reliably and predictably like every good procduct.

So you're saying they should be simple?

>unless you are a very simple person who always only does very simple things and lead a uniquely simple life

Considering the massive popularity of MacOS and iOS which all mandate the same reliable and predictable user experience on every Apple device, most people are "very simple" persons who "do very simple things and lead a uniquely simple life".

The power user paradigm of old that expose all the knobs and dials and levers there are to pleasure us simply does not appeal to the commons.
> We can say with a high degree of confidence that SARS-CoV-2 was _not_ engineered.

Do you have any links, articles, or further reading you could share to help me understand where the high degree of confidence comes from?

This guy seems to be convinced of the exact opposite conclusion that is is indeed engineered.
https://www.youtube.com/watch?v=5d-eqdRSx7Y
Humanity keeps running into copyright issues with every major leap in IT technology (photocopiers, tape cassettes, personal computers, internet, and now AI). I think it's about time for humanity to rethink their take on the unnatural restriction of information.

I personally hope that countries recognize copyright and patents for what they really are and abolish them. Countries that refuse to do so can play catch up.
The brain is a neural net. And so is the LLM.
That's kind of like asking an algebra equation solver to help you find synonyms for English words.

It's a very easy task, but LLMs aren't designed to do that kind. At best, someone has manually created a layer that notices your question involves math, "steals" the work from the LLM, and tries to reach the answer another way.

There are already plenty of websites that will convert the number for you.
Seems sensible to blame Nvidia for driver issues while everyone else provide upstream kernel and userspace drivers nowadays.

Linus expressed clearly what many feel on the matter.
> Can you feel a bunch of talent in limbo startups pivoting/re-energized now?

True! It certainly should be, as there is a lot less reason to hitch one's wagon to one of the few big firms that can afford nation state scale GPU compute.