MurphyA/hacker-news huggingface dataset:
by dkural | 2025-09-28 16:08:55+00:00
This article is a great example of how the human is struggling to extrapolate what happens next. There won't be any humans anywhere near this part of the tech stack, just like no one building a SAAS writes assembly code; or has to put together their own server cluster a datacenter (remember pre-cloud?) for their company anymore. He's dead Jim. No one is telling anyone to ship the ML code without any testing. Human coders also make mistakes. I'll bet that in a few years product managers / QA people would rather work with an ML stack to generate code than a human engineering team. It'll not just be cheaper and faster, but a lot less hassle & more accurate. As an example, Python has roughly ~100 or so "keywords", and extensive public libraries and open source algorithms to call upon. Anyone who thinks this presents any sort of challenge for an LLM to profoundly master is is delusional. They can do IMO-grade math, and help proving novel theorems. They can code your YC startup just fine.
by theptip | 2025-09-28 16:09:34+00:00
> Where are they going to get more data?

This is a great question, but note that folks were freaking out about this a year or so ago and we seem to be doing fine.

We seem to be making progress with some combination of synthetic training datasets on coding/math tasks, textbooks authored by paid experts, and new tokens (plus preference signals) generated by users of the LLM systems.

It wouldn’t surprise me if coding/math turned out to have a dense-enough loss-landscape to produce enough synthetic data to get to AGI - though I wouldn’t bet on this as a highly likely outcome.

I have been wanting to read/do some more rigorous analysis here though.

This sort of analysis would count as the kind of rigorous prediction that I’m asking for above.

E2A: initial exploration on this: https://chatgpt.com/share/68d96124-a6f4-8006-8a87-bfa7ee4ea3...

Gives some relevant papers such as

https://arxiv.org/html/2211.04325v2#:~:text=3.1%20AI
by extra88 | 2025-09-28 16:10:09+00:00
In-video sponsors are a form of contextual ad but ads inserted by YouTube are personalized (that doesn't mean context is not also a factor).

Channels like MKBHD (and LTT) need more revenue than what they get from YouTube ads because their expenses have greatly increased, particularly staff.

You can't automate contextual ads in news media, otherwise you get airline ads next to stories about airplane crashes. Or travel ads for places experiencing natural disasters or political upheaval. People pairing ads with stories increases the labor costs and there's already not enough money being paid for actual journalism to increase the cost of having ads.
by fxtentacle | 2025-09-28 16:10:12+00:00
That threat is as hollow as it gets.

Public companies will happily can the entire management team if they cause as little as a 5% dip in stock price. Apples EU revenue is larger than China and Japan combined. Voluntarily forfeiting that is like the modern management equivalent of ritual self-sacrifice: afterwards, they would have so much unsold stock on their hands that it’s going to tank prices worldwide.
by AnotherGoodName | 2025-09-28 16:10:27+00:00
I do appreciate that this article moves past absolute negativity on LLMs and actually speaks to the fact that they are extremely useful for well defined programming tasks. I'm a bit sick of articles that are just pure negativity on these tools.

I will raise that LLMs are pretty good at some of the non-coding tasks too.

eg. "I'm currently creating an AI for a turn based board game. Without doing any implementation, create a plan for the steps that need to be done including training off real world game data".

The LLM creates a tasklist for iterative steps to accomplish the above. It usually needs correction specific to the business/game needs but it's a great start and i recommend doing this just so the LLM has a doc with context on what its trying to achieve in a bigger picture as you have it complete tasks.
by ottah | 2025-09-28 16:10:34+00:00
Alternative argument, there is no need for more training data, just better algorithms. Throwing more tokens at the problem doesn't solve the fact that training llms using supervised learning is a poor way to integrate knowledge. We have however seen promising results coming out of reinforcement learning and self play. Which means that anthropic and openais' bet on scale is likely a dead end, but we may yet see capability improvements coming from other labs, without the need for greater data collection.
by lupusreal | 2025-09-28 16:10:35+00:00
There is a long and shameful history of repair techs and computer shops doing this to people. From the stories I've heard from people who've been in that industry, looking for nudes on customer devices has been almost an expected and tacitly tolerated norm for decades. Its not going to stop on it's own, so we need to start throwing the book at these people. Very long prison sentences are in order. It's a form of sexual abuse and should be considered a very severe felony.
by Canada | 2025-09-28 16:10:44+00:00
I noticed this years ago while in China. I saw someone at a bar with a laptop out using my web site. I went and chatted him up, and I noticed a different TLS certificate, I don't recall if he moused over the lock icon or if his browser, or back then when browsers showed the issuer in the address bar. Freaked me out.

Apparently it's JD Cloud now. Or maybe it was the, and I don't recall correctly. It was a Chinese company, and it really freaked me out when I saw it.

Our company did not do any configuration to enable this behavior. This was in 2017.

AWS was a completely separate entity in China at the time. Fully backdoored of course. Opening an account there required a local company.

With Cloudflare, they were straight up MITM our site which had nothing to do with China at all.
by StopDisinfo910 | 2025-09-28 16:11:14+00:00
Asian brands dominate the phone market in Europe with phones spanning the whole gamut of quality and flagships which are in every way comparable if not superior to what Apple offers.

Honestly even if Google somehow decided to stop selling Android to Europe, something which seems extremely unlikely, it would swiftly be replaced by Chinese alternatives with no obvious loss of functionality.

Apple has zero leverage with the "we will stop selling" strategy. It’s just there so they look less pathetic when it comes to what they are actually doing: bribing Trump so he intervenes for them. We really have come a long way from the "Think different" company.
by steve_adams_86 | 2025-09-28 16:11:22+00:00
I suspect it's a minority of people on the right, and frankly, I've known people on the left (in Canada, at least) who antagonize science and various institutions for no other reason than gut feelings. People on extreme ends of political spectrums are problematic, period. They've always been present, but the Internet amplifies their mania to all of us like never before
by _DeadFred_ | 2025-09-28 16:11:41+00:00
Soundbars in the past were a niche market for people with expensive Plasma screens so they had to appeal to that group.

Soundbars today are a cheap addition to make up for the horrible sound on everyone's cheap $300 LCD 65 inch TV that in addition to horrible sound looks worse at 4k than the 720 Plasma did.
by dragontamer | 2025-09-28 16:11:45+00:00
Ladders are a thing so easy that its literally in this beginner series of tutorials. Its a thing that 30kyu beginners learn and master.

Its very strange to me that AlphaGo / AlphaZero was unable to ever learn ladders. It shows that the way humans learn and AIs learn is quite different (or at least, MCTS + Neural Net machines learn differently).

Yes, Go is a strategic game of patterns and perhaps we humans overemphasized the ladder. Nonetheless, its a concept that humans can see and calculate with reasonable speeds that the (earlier) AI was unable to do (and now we've built stronger AIs that can prove this weakness).

---------

This 100% makes the 2016-era discussions about the "strategic brilliance" of AlphaGo come up into question. Now that KataGo is superior (ie: MCTS+NeuralNets + dedicated Ladder Solver), we need to double-check all those "strategically brilliant" moves with the newer AI and see if a ladder messed with them.

Etc. etc.

The things AlphaGo sees aren't necessarily useful to us humans, nor are they useful to modern AI-levels of Go. They're just... that. Trapped in 2016. There should not be any great mystery assigned to the 2016 era game, aside from it being a pivotal moment for AIs.

The game itself is now suspect, now that we know all of AlphaGo's flaws. As Go players, we have better things to study.
by troupo | 2025-09-28 16:11:48+00:00
1. So much emotion

2. None of that says that the EU isn't rich

3. None of that proves that the bullshit about revenue

Do you know how I know that? Because that "7%" comes from this quote: "Just to keep it in context, the changes apply to the EU market, which represents roughly 7% of our global App Store revenue."

App Store revenue is not all of Apple's revenue. Oh, and those same execs claim they don't even know if App Store makes money or loses it, so how would they know.
by tonetegeatinst | 2025-09-28 16:11:52+00:00
Nanofabrication is a very expensive field to get into and the equipment and support facilities are normally only seen at dedicated higher education university, or special research labs like IMEC.

I hope we can see the barriers to extry lowered so more people can experiment, just like how the computer became common place in the home or how 3d printing became much more affordable to hackers and makers.
by shawnz | 2025-09-28 16:11:52+00:00
> Of course, the user who named those files probably wants file-9.txt to come before file-10.txt. But 1 is smaller than 9, so file-10.txt should be first in alphabetical order. Everyone understands that, and soon people learn to put enough leading zeros if they want their files to stay sorted the way they like. Well, apparently all these operating systems have decided that no, users are too dumb and they cannot possibly understand what alphabetical order means. So when you ask them to sort your files alphabetically, they don’t. Instead, they decide that if some piece of the file name is a number, the real numerical value must be used.

I think there are many things wrong with your assessment of the situation.

First, where does it say in these file managers that they're sorting by alphabetical order? I see that you've specified that you want the files sorted by name, but I don't see that you've specified you want them sorted by name alphabetically. And what does "alphabetical sort" even mean when you're sorting characters which are not letters? What you mean is probably "lexicographical sort".

Second, you admit yourself that users probably want natural sort. Why would you expect these products to do the thing which they know users usually don't want by default? That just seems like bad design to me. They know users usually want natural sort, and you know users usually want natural sort, so why would you expect the default behaviour to be a lexicographical sort?

Third, just like how you've learned to work around the lack of natural sort in poorly designed products of years past by adding leading zeroes, you can just add trailing zeroes to get the lexicographical ordering that you want. Why do you seem to be implying that the latter is more user-hostile than the former? It doesn't make sense to me. A decision had to be made about what sort to use and they picked the one that most people want. Isn't that what we should be expecting in a product that caters to its users?

I see in other comments you've suggested that there should be a separate option for choosing between lexicographical sort and natural sort. But in the past, when lexicographical sort was the only option, why weren't you complaining about it being user-hostile to only have one option then? Why is it only when the default is something you're personally not used to that it warrants complaint? And where do we stop, do we have separate controls for every single sortable string field to determine whether it should be sorted lexicographically or naturally? Or just the name field? Don't you think that is going to lead to interface bloat?
by card_zero | 2025-09-28 16:12:13+00:00
He plainly says "the folly of human conceits". It's nice if he does a u-turn on this elsewhere, but the speech is still gleefully wallowing in putting down humans as big-headed ... for what? And why are "superstar" and "supreme leader" in quotes like that? Those superstars and supreme leaders on earth are the actual genuine ones. I know of no others elsewhere, do you? I mean OK important people may tend to be pompous, but some people are indeed important. Sagan, for instance, was a celebrity, meaning that he was celebrated by other people on account of his being some good. I don't need him to deny it, and I don't need him to make this speech vicariously denying the importance of everybody else.
by james_marks | 2025-09-28 16:12:25+00:00
I’ve also had success writing documentation ahead of time (keeping these in a separate repo as docs), and then referencing it for various stages. The doc will have quasi-code examples of various features, and then I can have a models stubbed in one pass, failing tests in the next, etc.

But there’s a guiding light that both the LLM and I can reference.
by makeitdouble | 2025-09-28 16:12:34+00:00
> the lack of documentation

If the code base expects flexibility, trusting documentation is the last thing you'd want to do. I know some people live and die by the documentation, but that's just a bad idea when duck typing or composition is heavily used for instance, and documentation should be very minimal in the first place.

When a function takes a myriad of potential input, "can this function do X" is an answer you get by reading the function or the tests, not the prose on how it was intended 10 years ago or how some other random dev thinks it works.
by sdenton4 | 2025-09-28 16:12:41+00:00
Curiously, humans don't seem to require reading the entire internet in order to perform at human level on a wide variety of tasks... Nature suggests that there's a lot of headroom in algorithms for learning on existing sources. Indeed, we had models trained on the whole internet a couple years ago, now, yet model quality has continued to improve.

Meanwhile, on the hardware side, transistor counts in GPUs are in the tens of billions and still increasing steadily.
by dlubarov | 2025-09-28 16:13:04+00:00
The 680k estimate is from [1], which essentially

- begins with the high estimate from [2], which uses some very questionable data (like WhatApp chats) to argue that most deaths were not counted by GHM

- extrapolates it to the present, as if the casualty rate were a constant

- multiplies it by 5, which was the multipler that was somewhat arbitrarily picked in that Lancet letter [3]

- forgets that this includes future deaths (attributable to past conflict events), and uses the past tense as if all these supposed indirect deaths already occurred

They also end up with an estimate of "about 380,000 under-five-year-old infant" deaths, which seems unlikely since there were never more than about ~340k children under five in the strip.

Overall, it's about as believable as that letter which claimed Hamas was under-reporting starvations by over three orders of magnitude [4].

[1] https://arena.org.au/politics-of-counting-gazas-dead/

[2] https://www.thelancet.com/journals/lancet/article/PIIS0140-6...

[3] https://www.thelancet.com/journals/lancet/article/PIIS0140-6...

[4] https://news.ycombinator.com/item?id=42209193
by dreamcompiler | 2025-09-28 16:13:14+00:00
It me takes longer to install a large Mac program from the .dmg than it takes to download it in the first place. My internet connection is fairly slow and my disk is an SSD. The only hypothesis that makes sense to me is that MacOS is still riddled with O[n] or even O[n^2] algorithms that have never been improved and this incompetence has been made less visible by ever-faster hardware.

A piece of evidence supporting this hypothesis: rsync (a program written by people who know their craft) on MacOS does essentially the same job as Time Machine, but the former is orders of magnitude faster than the latter.
by badsectoracula | 2025-09-28 16:13:26+00:00
> the LLM may not be learning anything, but I am

Regardless of that, personally i'd really like it if they could actually learn from interacting with them. From a user's perspective what i'd like to do is to be able to "save" the discussion/session/chat/whatever, with everything the LLM learned so far, to a file. Then later be able to restore it and have the LLM "relearn" whatever is in it. Now, you can already do this with various frontend UIs, but the important part in what i'd want is that a) this "relearn" should not affect the current context window (TBH i'd like that entire concept to be gone but that is another aspect) and b) it should not be some sort of lossy relearning that loses information.

There are some solutions but there are all band-aids to fundamental issues. For example you can occasionally summarize whatever discussed so far and restart the discussion. But obviously that is just some sort of lossy memory compression (i do not care that humans can do the same, LLMs are software running on computers, not humans). Or you could use some sort of RAG but AFAIK this works via "prompt triggering" - i.e. only via your "current" interaction, so even if the knowledge is in there but whatever you are doing now wouldn't trigger its index the LLM will be oblivious to it.

What i want is, e.g., if i tell to the LLM that there is some function `foo` used to barfize moo objects, then go on and tell it other stuff way beyond whatever context length it has, save the discussion or whatever, restore it next day, go on and tell it other stuff, then ask it about joining splarfers, it should be able to tell me that i can join splarfers by converting them to barfized moo objects even if i haven't mentioned anything about moo objects or barfization since my previous session yesterday.

(also as a sidenote, this sort of memory save/load should be explicit since i'd want to be able to start from clean slate - but this sort of clean slate should be because i want to, not as a workaround to the technology's limitations)
by LeonB | 2025-09-28 16:13:26+00:00
Recently I had the screen replaced on my child’s iPad. The tech asked for passcode, and I refused to provide it. The tech complained and said when I came to pick it up he’d need to guide me through some things.

Indeed, there were some settings that needed to be set, to ”help” the new screen.

Having said that — I’ve previously documented a case (well over 10 years ago) where I caught a local PC repair company who used their access to a machine of mine they were repairing - to quickly scan through the thumbnails of our personal photos, and look closer at any image which showed any flesh.

People expect to be trusted but don’t act in a trustworthy manner.
by bgwalter | 2025-09-28 16:13:33+00:00
"AI" does not encourage real thinking. "AI" encourages hand waving grand plans that don't work, CEO style. All pro-"AI" posts focus on procedures and methodologies, which is just LARPing thinking.

Using "AI" is just like speed reading a math book without ever doing single exercise. The proponents rarely have any serious public code bases.
by epistasis | 2025-09-28 16:13:41+00:00
This is reminding me of the whole "Worse is better" essay and debate:

https://news.ycombinator.com/item?id=27916370

The author wants the "worse" sort, one based on ASCII/Unicode codepoints, without any intelligence for numbers that 99% of GUI users want.

For their purposes, they've assumed something about the implementation, to the point that a convenience feature is actually a misfeature for them. But the author here is probably a developer, or close to one, so they do not represent the needs of most people using computers.

Understanding the target audience for your product results in very different design decisions. Better is better might be great for products, but worse is better is probably better for systems that need to grow and evolve.
by lo_zamoyski | 2025-09-28 16:15:21+00:00
I don’t know how you came to such a bizarre conclusion. I value true science, I appreciate science, but for what it is, not what it is not. A robust philosophy of science helps in this regard, as it allows us to examine and to understand the nature of science, its methods, its limits, the nature of the knowledge its gives us, and so on. Scientism is incoherent from the start, as its basic proposition is self-refuting, as it is not itself a scientific claim.

W.r.t. Sagan, it is the general character of his work that it privileged science (and I mean this in the modern sense of the term, i.e., “empirical science”) to the exclusion of other rational modes of knowing. Indeed, if anything is paradigmatic of rationality, it is philosophy, not empirical science. And Sagan’s insistence on evidence of does not square with things like his views on mathematics (never mind some of the superficial commentary on numerical representation) or what proofs for the existence of God can consist of.

Sagan’s views were also often guided by sentiment rather than reason. The first that comes to mind if the childish and fallacious inference involving the tacit assumption that size is proportional to significance. But of course, they were presented as if they were reasoned.

My point is, whatever his merits as an astronomer and the practice of astronomy (I have heard varying opinions), he was a mediocrity in areas like philosophy and theology. He should have had the humility to recognize the limits of his knowledge.
by troupo | 2025-09-28 16:15:25+00:00
> Apparently my source is a big fat liar

He is very uncaring when it comes to defending Apple and to smearing EU.

Even when shown that his reading is incorrect, he wrote a long article basically saying "so what I was still right" https://daringfireball.net/2024/03/more_on_the_eus_market_mi...
by AshamedCaptain | 2025-09-28 16:15:32+00:00
> In the Apple side, Airpods have had decent ~100ms latency for a few years (enough for casual gaming)

This needs a big citation. It has always been claimed that AirPods have no discernible latency and every time it is tested it is actually pretty subpar (>150ms).

> Bluetooth "aptX Low Latency" has also been around for years, though adoption has been a bit slow. It is quite standard on Android phones

Almost no Android phones support it. Anything Samsung for example is excluded, even if they use Snapdragon Sound chips.

It is not really a technology problem, since I was doing 50ms latency with plain old HFP profile on BT 1.x back in 2002 with a Nokia and the cheapest headset. Latency has being going up even though nothing really changed in the underlying technology (Classic Bluetooth Audio HFP/A2DP is practically unchanged since Bluetooth 2.x times, while LE Audio introduced in BT 5.x is used by almost no one and their codec selection can be considered sabotage).

The problems are (from an enthusiast & armchair analyst PoV):

- Consumers don't care (YouTube works well, after all) and can't even measure it correctly. Manufacturers don't report latency on specs.

- Everyone has an incentive to make it subpar so that they can promote their proprietary solutions with vendor lock-in. Qualcomm/CSR is _specially_ guilty of this, and they dominate the BT headset industry. But literally everyone is doing it these days (Samsung, Sony, Apple, etc.). And even then, most of the time these techs provide negligible improvements on latency or quality (since, #1, customers can't measure).

- The Bluetooth SIG no longer has any remaining teeth (it never had many to begin with). They just rubber-stamp and things barely interoperate with each other these days (e.g. last Sony headsets "support" LE Audio as per logo but on release could not talk with any of the existing LE Audio stacks).