MurphyA/hacker-news huggingface dataset:
by geeksinthewoods | 2025-12-05 15:22:54+00:00
Ya. It seems like evolution itself has been running a sparsity experiment for millions of years. Sparse attention may be the universal price of survival: efficiency over imagination, precision over possibility.

The line about "missing insights being rare, deferred, and distributed" is like the hardest to notice in practice: optimization wins are loud (speed, cost, scores). Meanwhile the things we prune are often counterfactual ideas that never form, weird bridges that never get built, questions that never feel worth asking because our router did not surface them.

One thing I'm still unsure about (and would love to think about more) is how direct the analogy should be. In models, sparsity is engineered / learned under explicit objectives. In biology and culture it's much more emergent and multi-objective.
by ViewTrick1002 | 2025-12-05 15:23:34+00:00
Almost the entire early large scale adoption came from people writing async web services.

From 2023:

> In that regard, async/await has been phenomenally successful. Many of the most prominent sponsors of the Rust Foundation, especially those who pay developers, depend on async/await to write high performance network services in Rust as one of their primary use cases that justify their funding.

https://without.boats/blog/why-async-rust/
by jl6 | 2025-12-05 15:23:48+00:00
> The disavowal comes 25 years after publication and eight years after thousands of internal Monsanto documents were made public during US court proceedings (the "Monsanto Papers"), revealing that the actual authors of the article were not the listed scientists – Gary M. Williams (New York Medical College), Robert Kroes (Ritox, Utrecht University, Netherlands), and Ian C. Munro (Intertek Cantox, Canada) – but rather Monsanto employees.

Why wasn’t the paper retracted 8 years ago?
by cb321 | 2025-12-05 15:23:49+00:00
In this case, it compiles & runs fine with floats (if you just delete the type constraint "Fibable") because the string "1" can be implicitly converted into float(1) { or 1.0 or 1f64 or float64(1) or 1'f64 or ..? }. You can think of the "1" and "2" as having an implicit "T(1)", "T(2)" -- which would also resolve your "doesn't work for me" if you prefer the explicitness. You don't have to trust me, either. You can try it with `echo fib(7.0)`.

Nim is Choice in many dimensions that other PLang's are insistently monosyllabic/stylistic about - gc or not or what kind, many kinds of spelling, new operator vs. overloaded old one, etc., etc., etc. Some people actually dislike choice because it allows others to choose differently and the ensuing entropy creates cognitive dissonance. Code formatters are maybe a good example of this? They may not phrase opposition as being "against choice" as explicitly as I am framing it, but I think the "My choices only, please!" sentiment is in there if they are self-aware.
by thwarted | 2025-12-05 15:24:03+00:00
> Or you have a leader above who has no idea and goes with the quickest/cheapest option.

This leader is not going with the quickest or cheapest option. Doing so would probably be laudable. They are going with the claims made by someone that a certain way is going to be quicker or cheaper. It doesn't matter if it actually is, or ends up being, quicker or cheaper. One plan is classified as meeting the requirements while another plan is classified as being cheaper, the cheaper one will be chosen even though it doesn't meet the requirements.
Show HN: Torial – Explainer videos that generate in 20 seconds
by bames_jond | 2025-12-05 15:24:11+00:00
Been working on this for a few months after realizing how time consuming it is to create educational content. You input text, it generates a complete video with visuals, voiceover, and animations in ~20 seconds(for brainrot videos) or 2 minutes(for in-depth videos). More than 10k videos have been generated so far. Would love feedback on video quality and what use cases you'd find valuable.
by 1718627440 | 2025-12-05 15:24:17+00:00
> My local bakery is a giant chain.

That's not what I would call a local bakery. Or are they making bread there?

> Any market inherently results in consolidation.

Only when you can undercut prices through scale. There are of course baking shops here as well, but they just don't have the quality of a real baker.
by willguest | 2025-12-05 15:24:41+00:00
..and most people problems are communication problems.

Calling them 'people problem' is a convenient catch-all that lacks enough nuance to be a useful statement. What constitutes good communication? Are there cross purposes?

> Non-technical people do not intuitively understand the level of effort required or the need for tech debt cleanup; it must be communicated effectively by engineering - in both initial estimates & project updates. Unless leadership has an engineering background, the value of the technical debt work likely needs to be quantified and shown as business value.

The engineer will typically say that the communication needed is technical, but in fact the language that leadership works with is usually non-technical, so the translation into this field is essential. We do not need more engineers, we need engineer who know how to translate the details.

I realise that, here on HN, most will probably take the side of the rational technologist, but this is a self-validating cycle that can identify the issue, but cannot solve it.

IMO, we need more generalists that can speak both languages. I have worked hard to try and be that person, but it turns out that almost no-one wants to hire this cross-discipline communicator, so there's a good chance that I'm wrong about all of this.
by tim333 | 2025-12-05 15:25:15+00:00
Polymarket:

This market will resolve to "Yes" if the AI industry experiences an industry downturn by the specified date, 11:59 PM ET. Otherwise, this market will resolve to "No".

For the purposes of this market, the AI industry will be considered to have experienced an industry downturn once at least three of the following events have occurred within 90 days of this market's specified timeframe: - NVIDIA Corporation (NVDA) closing stock price is down 50% from its all-time high. - iShares PHLX Semiconductor ETF (SOXX) closing stock price is down 40% from its all-time high. - OpenAI, Inc. or Anthropic PBC declares bankruptcy. - OpenAI, Inc. is acquired. - H100 rental price falls to $1.00 or lower for five consecutive days, as shown on the SiliconData Silicon Index at: https://www.silicondata.com/products/silicon-index. - Major AI Hardware Supplier Collapse: Taiwan Semiconductor Manufacturing Company Limited (TSM), ASML Holding N.V. (ASML), Broadcom Inc. (AVGO), Arista Networks, Inc. (ANET), or Super Micro Computer, Inc. (SMCI), closing stock price is down 50% from its all-time high.

Current odds - 35% by end 2026.
by robrenaud | 2025-12-05 15:25:40+00:00
From what I've seen at neurips, in terms of most different but maybe viable, it would be this.

https://sakana.ai/ctm/

In terms of a fresh perspective on designing learning systems, nested learning seems very interesting.

https://abehrouz.github.io/files/NL.pdf

Hearing the clarity, creativity, and force behind his thoughts and speech, I'd give a more than 1/200 chance Ali Behrouz gets himself a Turing award. At the very least, I think he will end making major contributions to AI.
by DaveZale | 2025-12-05 15:26:08+00:00
There are organizations in the US like Homegrown National Park, Wild Ones, and dozens of native plant societies that encourage rewilding of urban and suburban areas with plant natives. This is a really important step, too, in saving what's left of wildlife. The commercial focus on non-native grasses and ornamentals is sometimes a disaster for wildlife. Once the ecosystem is out of balance, it's not just a disaster for wildlife, either. Once the predators are gone, it's easy to get infestations of rodents and their diseases, noxious insects out of control, etc. It's not easy to re-wild a place, but the natural beauty of native plants and healthy wildlife, although not without inconvenience, has long term benefits for human livability, and relatively low costs.
by lanthissa | 2025-12-05 15:26:08+00:00
i dont think this should matter, plenty of conglomerates have brands across quality levels.

think old navy, gap, banana republic.

the quality difference is important for the conglomerate same with netflix vs hbo, the corporate benefit is being able to save on costs around like amortizing the corporate side of things (accounting, marketing, real estate, research ect)
by Neywiny | 2025-12-05 15:26:12+00:00
Hmmm disagree on your chain there. Plenty of easy hardware algorithms are hard for software. For example, in hardware (including FPGAs), bit movement/shuffling is borderline trivial if it's constant, while in software you have to shift and mask and or over and over. In hardware you literally just switch which wire is connected to what on the next stage. Same for weird bit widths. Hardware doesn't care (too much) if you're operating on 9 bit quantities or 33 or 65. Software isn't that granular and often you'll double your storage and waste a bunch.

I think they certainly go hand in hand in that algorithms relatively easier for software vs previously are easier for hardware vs previously and vice versa, but they are good at different things.
by zaphar | 2025-12-05 15:26:14+00:00
Those boundaries are pretty fuzzy. The complexity of the logic with conditionals and loops in a module means that you have pretty much stopped describing what it should like and instead described how to make it look the way you want it.

I have read terraform modules where I had to execute the logic to know what got produced which moves it from your imperative description to the declarative description as far as I'm concerned.
by WorldMaker | 2025-12-05 15:26:30+00:00
It also underlines in the US that sports is probably the last interest in linear programming. It would be interesting to get a picture of how many US customers will pay for ESPN in a Disney+ bundle but not Linear Hulu. I'm sure Disney will be tracking it, and probably made a smart move making the more interesting bundle the one with ESPN but not Linear Hulu.
by happytoexplain | 2025-12-05 15:26:44+00:00
This problem isn't specific to cases where you are rebasing "again and again". Just needing to do a single rebase (e.g. prior to opening a PR) for a stacked feature is enough to need a solution.

And, as others have pointed out, the modern solution is `--update-refs`, so there's no need for complicated workflows any more anyway.

If you mean rebasing as each PR in the stack is merged, most Git platforms have the ability to do that automatically.
Show HN: Every 5x6 Nonogram
by okayestjoel | 2025-12-05 15:26:45+00:00
Every 5x6 Nonogram is a realtime, collaborative web game with the goal to complete all 90,305,804 5x6 nonogram (aka picross) logic puzzle boards. Includes nonograms that have a unique solution, are line-solvable (no backtracking or guessing needed), no empty edges (so cannot be represented by a small board), and excludes rotations and reflections (so every board is truly unique).

This is a follow up to Every 5x5 Nonogram, a game I launched earlier this year.

Improvements this time around include: * Login with Patreon (free or paid) gives you an account w/ customizable colors and saves your individual score * Watch others solve in realtime, square by square * No puzzle swiping - players cannot complete a nonogram another player is solving

Let me know what you think!
by vel0city | 2025-12-05 15:26:58+00:00
> The reality is that cable was a paid premium service, unlike broadcast TV, which was free and littered with ads.

The reality is, most cable channels had ads from day one. Less ads than most broadcast stations (which made up most of the channels you had on cable at the start anyways) but still a lot of the first cable-only channels had ads from the start. WTBS had ads on cable in 1976. MSG/USA had ads on cable starting in 1977. CNN had ads on day one in 1980. MTV had ads on day one in 1981.
by munchbunny | 2025-12-05 15:27:14+00:00
> Then I offered as part of my design (and from my XP in more than 10yrs of working in products with petabyte datastores) that dealing with so many services connecting to the Data store directly could run into scale issues.

There's a small but substantial number of engineers out there who haven't operated at the kinds of scales where hyperscalers' limits become normal architectural problems and don't have the humility to imagine that it could be the case. (e.g. blob stores do in fact have limits you can hit, and when you operate at petabyte scales you have to anticipate in the architecture that you can hit them for even trivial operations.) I also work on petabyte datastores and have encountered a bunch of those engineers over time.

To be fair though, that's the small minority of engineers I've encountered, and if it wasn't arguing about the types of scale problems unique to petabyte scales, it'd be about some other nuanced subject matter. It's a humility problem.
by fulafel | 2025-12-05 15:27:35+00:00
PCIe is full duplex. And there's no requirement for ethernet ports to be able to do full tilt. Even with a 1x PCIe 3.0, a 10G port will be much much better than a 2.5G one.

(But PCIe 3.0 of course is from 2010 and isn't too relevant today - 4.0, 5.0, 6.0 and 7.0 have 16/32/64/128 Gbps per lane respectively)
by mihaic | 2025-12-05 15:27:46+00:00
> How many competitors do you need? Apple, Disney, Netflix, Comcast, and Paramount are five major competitors.

I actually already agree that the number is not the problem. I can't articulate better, but somehow these don't actually feel like "competitors" in the classical market sense, but rather as stars orbiting the same center, as they're all moving in the same direction, and from time to time merging with one another.
by jeffheard | 2025-12-05 15:27:56+00:00
And most people problems are communication problems. Engineers aren't engaged with the product vision or the customer base, and are allowed to silo themselves. Product doesn't see the point of engineers being engaged and feed the engineering team like an in-house outsourcing shop. Sales and CS fail to understand the cost of their promises to individual customers to the timelines of features they're hungry for from the product plan. Goals and metrics for success fail to align. And thus everyone rows in their own direction.

The solution usually isn't "better people." It's engaging people on the same goals and making sure each of them knows how their part fits with the others. It's also recognizing when hard stuff is worth doing. Yeah you've got a module with 15 years of tech debt that you didn't create, and no-one on the team is confident in touching anymore. Unlike acne, it won't get better if you don't pick at it. Build out what that tech debt is costing the company and the risk it creates. Balance that against other goals, and find a plan that pays it down at the right time and the right speed.
by seemaze | 2025-12-05 15:29:04+00:00
>HN boosters overdoing it on their home WiFi in what must be a bid to get their partner to divorce them..

Au contraire!

I got tired of the refrain "are you messing with the network again?" in the evenings when the neighbors are all streaming Netflix and crowding the airwaves, so I installed several low power UI APs around the house and and popped my own DNS and devices to a separate VLAN.

No more complaints :)

I do wish Unifi offered more configuration in the ad-blocking department, but I'm hesitant to inflict anything but the most vanilla deployment on the remainder of the household..
by mapt | 2025-12-05 15:29:09+00:00
Depending on weather and the site, a weed burner can be very effective for what people used to use glyphosate for.

For large areas, tarping can work pretty well in the summer. I accidentally cut a perfectly rectangular hole in my lawn by leaving a tarp on the ground as I was moving soil into containers. Enough sunlight was absorbed through the translucent plastic that it quickly baked the area underneath to death.
by mopsi | 2025-12-05 15:29:21+00:00
The USSR had starved millions of Ukrainians to death before the Nazis even rose to power. Mirrors the British hunger games in India.

If you want to excuse and trivialize the suffering caused by Russians in Eastern Europe, then by the same token you trivialize the suffering of Indians under British rule. All the same excuses apply: some Bandera-Ramachandran surely conspired against the British and therefore the Bengal famine is your own fault.
by stefan_ | 2025-12-05 15:29:44+00:00
It's worse, they seem to think tech debt is just a "state of mind", a "personality defect":

> The code was calcified because the developers were also. Personality types who dislike change tend not to design their code with future change in mind.

This line of thinking (we will make it with future change in mind!) is of course exactly the bullshit that is tech debt in the first place.
by Retric | 2025-12-05 15:30:32+00:00
I had an awesome 1080p rear projection DLP TV in a dark room. A brighter screen works better in a bright room, but you really want a dark room for an optimal experience anyway.

The technology got quite good but inherently took up more space and eventually couldn’t compete on price. Though that also means you’re sitting closer to the screen which made replacement flatscreens in the same space look smaller.
by ryandvm | 2025-12-05 15:30:34+00:00
I don't know about war, but I'm more interested in where AI goes from here.

We are currently coming around a corner in the information landscape where the majority of content on the Internet may well be AI output. It's going to be interesting seeing how the frontier AI companies deal with separating the wheat from the chaff otherwise, it's not clear to me how they will avoid model collapse from the LLMs being trained on their own excrement.

Statistical content generation isn't going to advance (and will actually regress) if the LLMs are just going to be trained mostly on what they said a few months ago.
by pjmorris | 2025-12-05 15:30:44+00:00
Jerry Weinberg wrote a number of books to this point, starting with 1971's 'The Psychology of Computer Programming.' Here's what he had to say a decade or so later...

"The First Law of Consulting: In spite of what your client may tell you, there’s always a problem.

The Second Law of Consulting: No matter how it looks at first, it’s always a people problem." [0]

Everything he wrote is worth the time to read.

[0] Weinberg, Gerald. "The Secrets of Consulting: A Guide to Giving and Getting Advice Successfully", 1986
by geeksinthewoods | 2025-12-05 15:30:51+00:00
The attention lottery framing feels especially timely now that DeepSeek's V3.2 tech report is out in the open. Seeing the actual top-k sparse routing and the post-training RL numbers spelled out makes the trade-offs concrete. Huge wins on speed and context, but every pruned token really is a quiet bet against the weird tail stuff that sometimes sparks real leaps...

What struck me most is how much DeepSeek's transparency accidentally lights up the closed models too. Long-context traces and million-token windows almost certainly lean on some variant of this under the hood. This article makes those black boxes feel a lot less mysterious. It leaves me both impressed by the engineering and quietly worried about the curiosity cost.

Also, the song / music video at the end is absurd in the best way!
by ymyms | 2025-12-05 15:31:29+00:00
I’ve been working on an identity/authorization system for machines and kept getting stuck on a basic question: what is machine identity, independent of any one stack (Kubernetes, cloud, OAuth, etc.)?

This post proposes a simple model based on where identity originates (self-proven / attested / asserted), what privileges it has at birth, and how it lives over time (disposable vs durable). I’ve also mapped common systems like SSH, SPIFFE/SPIRE, API keys, IoT, and AI agents into it.

I’d be very interested in counterexamples, ways this breaks down in real systems, or prior art I’ve missed.
by bobdvb | 2025-12-05 15:31:40+00:00
From previous experience some platforms are considered a "leakage source" for content and major rights owners won't put their content there because it's too easy to steal from. The security measures that are put on streaming platforms aren't totally ineffective, they're restrictive but it's considered worth the trouble because platforms can actually measure the effect of restrictions.

The low resolution option is something many rightsholders accept, but from a product proposition perspective it's difficult to explain to many customers. They're just grumpy that they paid for content and can only watch it in SD, that reduces your customer satisfaction. Better to do nothing than a poor job sometimes.
by Lerc | 2025-12-05 15:31:50+00:00
I can see a viewpoint where it would be beneficial. It allows humans to develop things and once developed they transition into a stable operating state predominantly automated.

This, of course, is considering only the case that they achieve the ability to actually make the automation.

If a product can generate a steady return on investment by reducing costs. There is incentive to maintain that service without enshitification. The automation lacks the design ability to endlessly modify the product to add 'features' that exploit users.

The idea is that humans can do more things and are more expensive, because they can do more than just operate an existing product, if you are paying for them anyway you can put some of their efforts maximizing all those things that generate more revenue at the cost of user experience

The counterpoint is what happens when AI is a capable enshitifier.

A world with more capable AI might require more of a paradigm shift. Instead paying for a service like this, you pay for a single human who can manage an AI to deliver a bespoke service.

You are still going to need a human to understand what you want and communicate that to an AI. It'll be quite some time before people are comfortable with an AI deciding what you want and giving it to you unprompted.

Again this is predicated on AI better than we currently have.

If we do get to that stage perhaps we see AI maintained open source projects.

If AI cans do it all, why wouldn't people just ask an AI to make them their own sass.

The truly all-in AI sass would just have all API calls forwarded to an AI and it deciding what to do on a call by call basis. I could see people trying that, but I suspect when AI is capable enough to do the job, the world would have changed sufficiently that we can't predict from here what it is that we would want them to make for us.
by irae | 2025-12-05 15:32:12+00:00
I believe you are speculating on digital mastering and not codec conversion.

From the creator's PoV their intention and quality is defined in post-production and mastering, color grading and other stuff I am not expert on. But I know a bit more from music mastering and you might be thinking of a workflow similar to Apple, which allows creators to master for their codec with "Mastered for iTuenes" flow, where the creators opt-in to an extra step to increase quality of the encoding and can hear in their studio the final quality after Apple encodes and DRMs the content on their servers.

In video I would assume that is much more complicated, since there are many quality the video is encoded to allow for slower connections and buffering without interruptions. So I assume the best strategy is the one you mentioned yourself, where AV1 obviously detects on a per scene or keyframe interval the grain level/type/characteristics and encode as to be accurate to the source material at this scene.

In other words: The artist/director preference for grain is already per scene and expressed in the high bitrate/low-compression format they provide to Netflix and competitors. I find it unlikely that any encoder flags would specifically benefit the encoding workflow in the way you suggested it might.