MurphyA/hacker-news huggingface dataset:
by btilly | 2025-09-30 19:53:09+00:00
Yes, you can show such equiconsistency statements. As Gödel proved, for any set of classical axioms, there is a corresponding set of intuitionistic axioms. And if the classical axioms are inconsistent, then so is the intuitionistic equivalent. (Given that intuitionistic reasoning is classically valid, an inconsistency in the intuitionistic axioms trivially gives you one in the classical axioms.)

So the care that intuitionists take does not lead to any improvement in consistency.

However the two approaches lead to very different notions of what it means for something to mathematically exist. Despite the formal correspondences, they lead to very different concepts of mathematics.

I'm firmly of the belief that constructivism leads to concepts of existence that better fit the lay public than formalism does.
by peanut_merchant | 2025-09-30 19:53:27+00:00
Personally been here about 15 years. There are ebbs and flows of different trends, but HN has never been pure tech or science.

My favourite thing about HN has always been it's sprinkling of the "interesting/thought provoking" amongst the more technical or science based e.g. 5 in depth articles about <insert language tech stack etc.>, blog post on seagulls in 1973 east Berlin, philosphical article ruminating on death and coding, Go compiler written in C# etc. etc.

I get the point about self promotion. But fwiw I think this list is quite insightful, and a fun read.
by mamonster | 2025-09-30 19:53:37+00:00
From people I know personally:

"Arbs" on stuff that big desks don't touch because of capacity (small mergers for example, you lever up on 2-3 small merger arbs per year and you are almost there);

DEX to liquidity pool latency arbs for shitcoins if you want a crypto example;

Pure arbs (One of my friends who admittedly is not satisfied with 1mio USD comp did this trade: https://notion.moontowermeta.com/financial-hacking-etf-vs-ne... ).

Edit: The other option is that if you are a trader in "special" markets (the best example is biotech/medstocks) where domain knowledge really matters being 4 sharpe is basically 1 good trade a year, and at 5mio USD AUM you are always at capacity.
by aurareturn | 2025-09-30 19:53:37+00:00
I also wonder why they have not been acquired yet. Or is it intentional?

A few issues:

1. To achieve high speeds, they put everything on SRAM. I estimated that they needed over $100m of chips just to do Qwen 3 at max context size. You can run the same model with max context size on $1m of Blackwell chips but at a slower speed. Anandtech had an article saying that Cerebras was selling a single chip for around $2-3m. https://news.ycombinator.com/item?id=44658198

2. SRAM has virtually stopped scaling in new nodes. Therefore, new generations of wafer scale chips won’t gain as much as traditional GPUs.

3. Cerebras was designed in the pre-ChatGPT era where much smaller models were being trained. It is practically useless for training in 2025 because of how big LLMs have gotten. It can only do inference but see above 2 problems.

4. To inference very large LLMs economically, Cerebras would need to use external HBM. If it has to reach outside for memory, the benefits of a wafer scale chip greatly diminishes. Remember that the whole idea was to put the entire AI model inside the wafer so memory bandwidth is ultra fast.

5. Chip interconnect technology might make wafer scale chips more redundant. TSMC has a roadmap for glueing more than 2 GPU dies together. Nvidia’s Feynman GPUs might have 4 dies glued together. IE, the sweet spot for large chips might not be wafer scale but perhaps 2, 4, 8 GPUs together.

6. Nvidia seems to be moving much faster in terms of development and responding to market needs. For example, Blackwell is focused on FP4 inferencing now. I suppose the nature of designing and building a wafer scale chip is more complex than a GPU. Cerebras also needs to wait for new nodes to fully mature so that yields can be higher.

There exists a niche where some applications might need super fast token generation regardless of price. Hedge funds and Wallstreet might be good use cases. But it won’t challenge Nvidia in training or large scale inference.
by fluoridation | 2025-09-30 19:54:02+00:00
What do you imagine a generated video about poetry would be?

>Every AI video demonstration is always about funny stuff and fancy situations.

The thing about AI slop is that by its very nature, unless it's heavily reined in by a human, it's invariably lowest common denominator garbage. It very likely will generate something you yourself could think of within the first five seconds of hearing the prompt, not some very clever take on it, so it can only work as a placeholder (AI as a replacement of stock images is great, for example) or to add background detail where it won't call attention to itself and its genericity.

>imagine building a video about the moment Jesus was born

Given there are multiple paintings on the subject, I very much doubt no one has generated something like that already.
by advisedwang | 2025-09-30 19:54:14+00:00
The article says:

> One Beethoven biographer63 has previously suggested, on circumstantial grounds, that Ludwig senior may not have been Johann van Beethoven’s biological father

> 63 Canisius, C. Beethoven “Sehnsucht und Unruhe in der Musik”: Aspekte zu Leben und Werk Originalausgabe. Schott, 1992

So it's been hypothesized but presumably not demonstrated genetically.
by bob1029 | 2025-09-30 19:54:41+00:00
It's the inaccuracy of things like shadows, sub-surface scattering and specular highlights. I think the shadow inaccuracy is what the human visual system is most sensitive to.

These LLMs might make content that looks initially impressive but they are absolutely not performing physically based rendering or have any awareness of the lighting arrangement in these scenes. There are a lot of things they get right, but you only have to screw up one small element to throw the whole thing off.

I am willing to bet that Unreal Engine 5 will continue to produce more realistic human faces than OAI ever can with these types of models. You cannot beat the effects of actually running raytracing in a PBR pipeline.
by ryandrake | 2025-09-30 19:54:48+00:00
It's so ambiguous. Let's say I'm a citizen of country A, currently residing in country B. I'm using a VPN headquartered in country C to make my traffic appear to originate from country D. I access a web site with servers physically located in country E, that uses a load balancer / cache hosted in country F. The company that runs the web site is headquartered in country G but has employees in countries H, I, and J.

Whose laws need to be followed?
by layer8 | 2025-09-30 19:54:51+00:00
It’s the server’s choice to send or not to send the data. The fact that the server is receiving a request for the data in no way implies that it has to obey it. If someone places an order for a product whose distribution violates a law, the distributor is still responsible for sending it. Someone selling drugs is still responsible even if the buyer requested the drug. Someone distributing unlicensed material is still responsible even when that material was specifically requested.
by lowsong | 2025-09-30 19:55:29+00:00
I think that you've made my point really quite well. I gave perhaps the most basic possible example of accommodation, adjusting a single word with no impact on other project members and you were still able to argue about it.

> Maybe you believe it is necessary to identify yourself online as belonging to some group, perhaps in order to force a change, but again I think this is just trying to play politics where it's often not welcome.

People just want to be themselves. If the very act of appearing to be from a different group is "playing politics" then what you actually mean is "you cannot be different".

This behavior is exactly why a CoC is needed.
by csvance | 2025-09-30 19:56:29+00:00
Technically you don't need to know what array indexing is being used if you iterate using firstindex(arr):lastindex(arr). AFAIK the issue was that this wasn't consistently done across the Julia ecosystem including parts of the standard library at the time. No clue as to whether this still holds true, but I don't worry about it because I don't use OffsetArrays.
by xpe | 2025-09-30 19:56:35+00:00
> The entire value/fact dichotomy that the announcement bases itself on

Hmmm. Here I will quote some representative sections from the announcement [1]:

>> News is broken. We all know it, but we’ve somehow accepted it as inevitable. The endless notifications. The clickbait headlines designed to trigger rather than inform, driven by relentless ad monetization. The exhausting cycle of checking multiple apps throughout the day, only to feel more anxious and less informed than when we started. This isn’t what news was supposed to be. We can do better, and create what news should have been all along: pure, essential information that respects your intelligence and time.

>> .. Kagi News operates on a simple principle: understanding the world requires hearing from the world. Every day, our system reads thousands of community curated RSS feeds from publications across different viewpoints and perspectives. We then distill this massive information into one comprehensive daily briefing, while clearly citing sources.

>> .. We strive for diversity and transparency of resources and welcome your contributions to widen perspectives. This multi-source approach helps reveal the full picture beyond any single viewpoint.

>> .. If you’re tired of news that makes you feel worse about the world while teaching you less about it, we invite you to try a different approach with Kagi News, so download it today ...

I don't see any evidence from these selections (nor the announcement as a whole) that their approach states, assumes, or requires a value/fact dichotomy. Additionally, I read various example articles to look for evidence that their information architecture group information along such a dichotomy.

Lastly, to be transparent, I'll state a claim that I find to be true: for many/most statements, it isn't that difficult nor contentious to separate out factual claims from value claims. We don't need to debate the exact percentages or get into the weeds on this unless you think it will be useful.

I will grant this -- which is a different point that what the commenter above made -- when reading various articles from a particular source, it can take effort and analysis to suss out the source's level of intellectual honesty, ulterior motives, and other questions I mention in my sibling comment.

[1]: https://blog.kagi.com/kagi-news
by thrance | 2025-09-30 19:57:04+00:00
I am not American, and I don't think that "trans people have a right to participate in society" is a political take. The real issue is with people thinking that "trans people shouldn't exist" is a valid opinion to hold, and I don't feel particularly bad for them being "silenced".

If this view falls in the American left's umbrella, then I'm sorry to say: they're objectively right and fuck the guys who hold anti-human views.
by ilikepi | 2025-09-30 19:57:19+00:00
Not sure what post you have in mind, but Kenji Alt-Lopez's video[1] on the topic is excellent. If I remember right, it's based on work he did with a well-known food publication (or show or something)...

[1]: https://www.youtube.com/watch?v=hb0Elaa6gxY
by strstr | 2025-09-30 19:57:33+00:00
Legitimately, they are often too hard. Balancing the problems is quite challenging.

On top of that, the solutions often make the problems seem much intimidating than they are (not that they are easy). Most solutions involve a lot of “happenstance”, where someone tried something and it got an outcome that was useful, which they build on top of. This makes the solutions look crazy complicated (“how would i have ever thought of this!?”), when in reality they are Rube Goldberg machines built out of duct tape and baling wire.

I’ve only solved a few Google CTF problems, and one of them was the one I wrote, lol. That was nearly a decade ago though.
by gman83 | 2025-09-30 19:57:48+00:00
This dynamic is a core theme in Asimov's "Foundation." The Empire's technological stagnation is defined by its inability to create new atomic devices. They had the old ones, and they had technicians to maintain them, but the actual knowledge of how to design and construct one from the ground up had been lost to institutional rot. They could patch the old world together, but they couldn't build the new one.
by dsego | 2025-09-30 19:57:54+00:00
This aligns with my experience as well. The bigger sensor does generate pictures that look more crisp in big prints or zoomed in. In theory it should gather more light, but in reality, phones stitch together multiple exposures, and frequently produce nicer low light images without much noise. For sharing on social media, it's hard to notice a difference. For me its event worse with the x100 since the wide lens doesn't have that signature compression and depth of field, so the photos don't really stand out that much, no wonder most x100 photographers rely on color filters (film sims) and high contrast to draw attention.
by Cybermyber | 2025-09-30 19:58:03+00:00
Hi HN — I came across a browser-based cyberwarfare simulator. You can play as a Red Team attacker or a Blue Team defender. It looks like a terminal, shows recon/exploit steps, and simulates network attacks, but everything is scripted — no real network connections or exploits are performed.

From the perspective of someone who works in security: does this kind of simulation have any educational or realism value, or is it purely entertainment? Are there any situations where a simulator like this could meaningfully teach concepts about attacks or defenses, or is it mostly “movie-style hacking”?

Curious to hear thoughts from people who deal with real-world attacks.
by fifticon | 2025-09-30 19:58:10+00:00
imgur itself is an empty husk of its former self. Last time I visited their site, they had fired all their moderators and replaced them with AI. They were bought at some point by .. media labs? I don't recall their name, but I recall that they are moneygrubbing bastards, to phrase it in neutral terms. I don't intend to visit their site again. Instead, I have made an AI agent that can do it for me.
by lc2817 | 2025-09-30 19:58:25+00:00
I run many parallel LLM coding sessions and documented the workflow engineering needed to make it productive. The series covers: managing multiple conversations with visual indicators and telemetry, coordinating parallel LLMs with shared context (memento notes) and smoke tests, tools that became obsolete as models improved, and the societal implications of AI-augmented development (what happens to junior developers when LLMs handle entry-level work?). Everything from tmux automation to spaced-repetition learning systems. The key insight: LLMs are productive only if you build the right workflows around them—otherwise you're just flying blind.
by jillesvangurp | 2025-09-30 19:58:35+00:00
I don't tend to look at the clock for pasta. I just eyeball it and sample it. You can sort of see the pasta turning whiter from the outside in. Especially with my regular goto brands, I can see when it is done. I fish some out with a fork to verify usually when it's getting close.

And I generally mix it with some sauce and it might sit in there for some minutes. So the cooking process actually continues after you remove it from the water. Cooking a bit longer in the sauce and shorter in the water is going to help the flavor and texture. There's no point in being hyper precise about the cooking time and then letting it sit for five minutes or whatever in the sauce. Nobody ever measures that time. Add pasta water to loosen the sauce if it absorbs too much.

Speaking of pasta water, use less water for boiling paste; not more. Many TV cooks get this completely wrong. They'll dump 100 grams of pasta in a gallon of water. Complete waste of time, energy, and salt (assuming they season the water correctly).

Especially if you plan to use the starchy water for your sauce, you need to use as little water as you can get away with. If you use too much water, there's not going to be a lot of starch in there. If it still looks like clear water by the time your pasta is cooked, you used way too much water. You might as well just use tap water for your sauce. The water should be cloudy not clear. As long as it doesn't cook dry, it's fine. About 2-3x the dry weight should be plenty for most pasta types. Restaurants tend to reuse their pasta water for multiple batches of pasta so they'll use more water. But the water has lots of starch after a few batches.
by btilly | 2025-09-30 19:59:07+00:00
Sure, we can choose to work in a set of axioms that says that there exists an oracle that can solve the Halting problem.

But the fact that such systems don't create contradictions emphatically *DOES NOT* demonstrate the constructive existence of such an oracle. Doubly not given that in various usual constructivist systems, it is easily provable that nothing that exists can serve as such an oracle.
by SeanAnderson | 2025-09-30 19:59:09+00:00
It's not an exaggeration to me? I literally stopped the video and went back to the start and re-read. You're more than welcome to speak about your opinions and experiences, but I'm speaking about mine.

I'm over here thinking, "It felt like just yesterday I was laughing at trippy, incoherent videos of Will Smith eating spaghetti."

I love the progress we're making. I love the competition between big companies trying to make the most appealing product demos. I love not knowing what the tech world is going to look like in six months. I love not thinking, "Man. The Internet was a cool invention to have grown up in, but now all tech is mundane and extractive." Every time I see AI progress I'm filled with childlike wonder that I thought was gone for good.

I don't know if this represent SOTA for video generation. I don't care. In that moment I found it impressive and was commenting specifically on the joy I experienced watching the video. I find it frustrating to have that joy met with such negativity.
by teraflop | 2025-09-30 19:59:30+00:00
On top of everything else, Scientist-1 doesn't come off looking too good.

He was contracted to make a synthetic dataset, based on a small set of records which were supposedly randomly sampled from a larger original dataset. He didn't really have any way of knowing he was being lied to at that point, or what his work would be used for.

But when he invoiced $13k for his services, including a detailed breakdown of what he did, Javice came back and offered him an extra $5k if he would change the invoice to a one-liner that just said "data analysis services". And he immediately agreed.

I find it hard to believe someone could get that request and not understand that they were being asked to be complicit in fraud. At best, it's really poor judgment.
by sib | 2025-09-30 19:59:33+00:00
>> I own an M4 iPad Pro and can't figure out what to do with even a fraction of the horsepower, given iPadOS's limitations.

> It's a nice problem to have, since for most of computing history it's been the other way around. (Meaning the hardware was the constraint, not the OS.)

For anyone who works with (full-size) image or video processing, the hardware is still the constraint... Things like high-ISO noise reduction are a 20-second process for a single image.

I would be happy to have a laptop that was 10x as fast as my MacBook Pro.
by TheAceOfHearts | 2025-09-30 19:59:40+00:00
Really impressive engineering work. The videos have gotten good enough that they can grab your attention and trigger a strong uncanny valley feeling.

I think OpenAI is actually doing a great job at easing people into these new technologies. It's not such a huge leap in capabilities that it's shocking, and it helps people acclimate for what's coming. This version is still limited but you can tell that in another generation or two it's going to break through some major capabilities threshold.

To give a comparison: in the LLM model space, the big capabilities threshold event for me came with the release of Gemini 2.5 Pro. The models before that were good in various ways, but that was the first model that felt truly magical.

From a creative perspective, it would be ideal if you could first generate a fixed set of assets, locations, and objects, which are then combined and used to bring multiple scenes to life while providing stronger continuity guarantees.
by pazimzadeh | 2025-09-30 20:00:10+00:00
if you're not an animal then you don't have to worry about IL-6

neuroimmunology is very cool, look into it

there are nerves which directly contact macrophages and other immune cells in the spleen and it's not clear why

https://www.nature.com/articles/s41598-020-66619-0
by mytailorisrich | 2025-09-30 20:00:28+00:00
> When asked what types of fraud they thought were ‘reasonable’, nearly a quarter (24%) said selling a vehicle privately that was subject to a finance agreement – also known as asset conversion –

Well, if you continue to make payments as required then no-one loses anything.

On the other hand, in the UK anyone can instantly check a vehicle's details because the government has a website that allows anyone to check whether a vehicle is taxed and has an valid MOT (safety check) along with all the vehicles details, including date of last V5C logbook, which means owner has moved or changed. Tax date will probably also change if sold. So, in principle I would expect a decent car finance company to find out fairly quickly!
by big_toast | 2025-09-30 20:00:30+00:00
Wait, does lima do isolation in a macos context too?

It looks like linux vms, which apple's container-cli (among others) covers at a basic level.

I'd like apple to start providing macOS images that weren't the whole OS.. unless sandbox-exec/libsandbox have affordance for something close enough?

You can basically ask claude/chatgpt to write its jail (dockerfile) and then run that via `container` without installing anything on macos outside the container it builds (IIRC). Even the container-cli will use a container to build your container..
by rchaud | 2025-09-30 20:00:42+00:00
First of all, investment banks are awash in capital thanks to 14 years of ZIRP and massive profitability. They don't like keeping cash on hand, so that means they dole it out into investments, some of which will flop.

Second, banks are the primary creditor in these deals, meaning they get paid first. They don't do these deals without ensuring that the company has enough saleable assets to ensure they get their pound of flesh. Lots of companies have billions in pension-earmarked reserves they don't have to pay out on if they declare bankruptcy. Guess who gets first dibs on that cash.

Third, they can shift the risk by selling their interest in these companies to another party. They are not stuck with it forever.
by jsnell | 2025-09-30 20:00:45+00:00
> Getting the most out of models requires maximally exploiting parallelism, so sandboxing is a must.

What are your thoughts on checkpointing as a refinement of sandboxing? For tight human/llm loops I find automatic checkpoints (of both model context and file system state) and easy rolling back to any checkpoint to the most important tool. It's just so much faster to roll back on major mistakes and try again with the proper context, than to try to get the LLM to fix a mistake, since now the broken code and invalid assumptions are contaminating the context.

But that relies on the human in the loop deciding when to undo. Are you giving some layer of your system the power of resetting sub-agents to previous checkpoints, do you do a full mind-wipe of the sub-agents if they get stuck and try again, or is the context rot just not a problem in practice?