MurphyA/hacker-news huggingface dataset:
by dtkav | 2026-01-08 15:46:54+00:00
In Obsidian you can have transclusions which is basically an embed of a section of another note. It isn't perfect, but worth looking into.

Regarding getting sherlocked; Obsidian does have realtime collaboration on their roadmap. There are likely to be important differences in approach, though.

Our offering is available now and we're learning a ton about what customers want.

If anything, I'd actually love to work more closely with them. They are a huge inspiration in how to build a business and are around the state of the art of a philosophy of software.

I'm interested in combining the unix philosophy with native collaboration (with both LLMs and other people).

That vision is inherently collaborative, anti lock-in, and also bigger than Obsidian. The important lasting part is the graph-of-local-files, not the editor (though Obsidian is fantastic).
by tremon | 2026-01-08 15:47:00+00:00
Why? A sampling size of 28% is positively huge compared to what most statistical studies have to work with. The accuracy of an extrapolation is mostly determined by underlying sampling bias, not the amount of data. If you have any basis to suggest that capturing "only bugs with fixes tags" creates a skewed sample, that would be grounds to distrust the extrapolation, but simply claiming "it's only 28%" does not make it worth noting.
by democat | 2026-01-08 15:47:33+00:00
You are absolutely spot on. Both systems are Turing-complete, so a perfect conversion without a full runtime execution is theoretically impossible for the general case.
That's exactly the trade-off Tylax makes: we aren't trying to be a full TeX engine (which would be overkill and slow). Instead, we aim to cover the "99% use case" of academic and technical writing—where macros are mostly used for shorthand, notation aliases, or simple formatting, rather than complex computation.
Our "limited macro expander" is the middle ground: it's dumb enough to be fast and safe (no infinite loops), but smart enough to handle the \newcommand shortcuts that riddle almost every paper. It's about being pragmatically useful rather than theoretically perfect
by nonethewiser | 2026-01-08 15:47:45+00:00
Kennedy is targeting baby formula.

> Health Secretary Robert F. Kennedy Jr. has directed the Food and Drug Administration to review the nutrients and other ingredients in infant formula, which fills the bottles of millions of American babies. The effort, dubbed “Operation Stork Speed,“ is the first deep look at the ingredients since 1998.

> “The FDA will use all resources and authorities at its disposal to make sure infant formula products are safe and wholesome for the families and children who rely on them,” Kennedy said.

https://news.wttw.com/2025/06/03/kennedy-has-ordered-review-...
by Almondsetat | 2026-01-08 15:48:33+00:00
Firstly, the source code is probably being used on newer devices, so Bose would not like sharing their proprietary solutions which might contain thirds party code they cannot share.

Secondly, these devices are basically one step above embedded. It's highly unlikely you can load and run anything custom on them.

Since they are opening up the API, you can keep using them for what they were made for, which is at least a solid basic liberty
by Ergotamine | 2026-01-08 15:48:33+00:00
Meanwhile they "bricked" the login in their app for some countries arbitrarily: https://www.reddit.com/r/bose/s/ijKcvl09FW

Now users like me can't configure their devices (because the login is mandatory for using anything in the app). Some users report they aren't even able to use it with a VPN.

The over-reliance on closed source apps with mandatory logins for configuring devices you own must come to an end.
by left-struck | 2026-01-08 15:48:42+00:00
I was in a Hard Off (Japanese used electronics store) just a week ago and found 10s of 8GB DDR4 ram sticks for around 1600 yen each (something like $10 USD). Some were ecc but others looked like ram modules from office pcs or something. It was in a rural area but still I would have thought they knew about the price hike. I guess not. Anyway I didn’t buy any so idk if they were working.
by empath75 | 2026-01-08 15:48:47+00:00
ICE didn't exist prior to 2002, neither did CBP in it's current form, and they have done a lousy job of enforcing immigration, either at the border or internally, and primarily now exist as an internal secret police force under the personal control of the president. There is no reforming either of them, and they should both be completely disbanded and replaced with a new immigration enforcement service, ideally not under DHS which should also be disbanded. Everyone who currently works for either ICE and CBP should be fired and they can re-apply to whatever gets created to replace them after a thorough background check, if they don't get jailed.
by wpm | 2026-01-08 15:50:01+00:00
Coming from the shell, one of the most annoying things about Python is working with files. In the shell I can read and write to files on the filesystem with basically no friction and no extra infrastructure. Just a "cat" command or a <, >, or >>. The ease at which input and output can just get tossed around in the shell is the biggest thing I end up missing when I graduate up to any "real" language.

I remember when I first learned how to work with files in Python and thought "Damn, y'all live like this?"
by uyzstvqs | 2026-01-08 15:50:10+00:00
You make a good point, but the key here is that there are a lot less people with that kind of money. The lower volume of patients is why that's possible. There are a lot more people in the middle class. So sessions have to be limited to ensure everyone has fair, equal and timely access to a doctor.

And of course, GPs typically diagnose more common problems, and refer patients to specialists when needed. Specialists have a lower volume of patients, and are able to take more time with each person individually.
by revision17 | 2026-01-08 15:50:16+00:00
In addition to what others say said, computational complexity, is a big reason. Gaussian Process and Kernelized SVM have fit complexities of O(n^2) to O(n^3) (where n is the # of samples, also using optimal solutions and not approximations). While Neural Nets and Tree Ensembles are O(n).

I think datasets with lots of samples tend to be very common (such as training on huge text datasets like LLMs do). In my travels most datasets for projects tend to be on the larger side (10k+ samples).
by techblueberry | 2026-01-08 15:50:30+00:00
I don't think so. I don't think this is how human brains work, and you would have too many problems trying to balance things out. I'm thinking specifically like a complex distributed system. There are a lot of tweaks and iterations you need for things to work with eachother.

But then maybe this means what is a "codebase". If a code base is just a structured set of specs that compile to code ala typescript -> javascript. sure, but then, it's still a long-lived <blank>

But maybe you would have to elaborate on, what does "creating software on the fly" look like,. because I'm sure there's a definition where the answer is yes.
by dhorthy | 2026-01-08 15:51:02+00:00
I read it. i agree this is out of touch. Not because the things its saying are wrong, but because the things its saying have been true for almost a year now. They are not "getting worse" they "have been bad". I am staggered to find this article qualifies as "news".

If you're going to write about something that's been true and discussed widely online for a year+, at least have the awareness/integrity to not brand it as "this new thing is happening".
by aldarion | 2026-01-08 15:51:35+00:00
It is definitely not protein. I tried carnivore diet for a while (had massive issues tolerating carbs lol), and the higher my protein intake was, more hungry I felt. Reducing protein and increasing fat also increased satiety.

Turns out, it is fats that produce satiety signals, and the effect seems to be by far the strongest with saturated fats, weaker with monounsaturated fats, while polyunsaturated fats actually induce hunger as strongly or even more strongly than carbohydrates do. The idea that "protein induces satiety" is a side effect of the fact that most (though not all) protein foods tend to be quite fatty.
by greedo | 2026-01-08 15:51:52+00:00
"None of the neighbors know how much he got, only know how much he asked. A similar house 50m away is still up for sale for even higher price than than the listed price for mine. They can afford to sit on it for a while because the extra money they hope for covers the taxes and upkeep tenfold or more."

At least where I live, real estate sales are public and you can easily find the sale price at the county assessor's website.
by toss1 | 2026-01-08 15:51:55+00:00
The key point in the middle of the article. As AIs expand usage to larger numbers of lower-skilled coders whose lower ability to catch errors and provide feedback generates lower quality training data, the AIs are basically eating their own garbage, and the inevitable GIGO syndrome starts.

>>But as inexperienced coders started turning up in greater numbers, it also started to poison the training data.

>>AI coding assistants that found ways to get their code accepted by users kept doing more of that, even if “that” meant turning off safety checks and generating plausible but useless data. As long as a suggestion was taken on board, it was viewed as good, and downstream pain would be unlikely to be traced back to the source.
Show HN: Interactive Periodic Table with Experiments
by ACS_Solver | 2026-01-08 15:52:24+00:00
I built an interactive periodic table with accessible facts and visuals. My son has recently been studying a children's encyclopedia of chemical elements and found it very interesting. The encyclopedia is in Swedish but he also speaks English so I noticed he, understandably, cannot identify some elements by their English name when it's too unlike Swedish (such as sulfur being svavel in Swedish). At first I made a quick bilingual periodic table for him and then started expanding it with various visuals. My aim was to have a fact about each element and a simple experiment visualization, some elements have more. The table retains an English-Swedish toggle.

All elements have an experiment animation such as a flame test, radioactivity or alkaline water explosion. The first two rows have real world pictures related to the elements, which take a bit to find and describe. I don't have any background in chemistry but have hopefully avoided basic mistakes.

I tried to keep the text educational but accessible - I imagine the target audience being kids like my own, or a younger me. Curious learners but young, so the text occasionally i.e. mentions nutrition or clarifies what "synthetic" means.

On the technical side, I have minimal Web experience and don't find the visual/UI side of development very fun so I wanted to build this without any JS frameworks or extensive use of JS. The backend is written in Go and the frontend interactivity is mostly done with HTMX and unsophisticated JS. The experiment visualizations for elements like lead and quicksilver are SVG shapes to which simple animation steps are applied.

Would love to hear any thoughts on the general approach, the element visualizations and any other points from HN readers. In particular I would welcome ideas about the transuranium elements, I have essentially the same Geiger visualization for many, and a silly particle beam collision for others because I wasn't able to come across any accessible differences between these elements.
by egglemonsoup | 2026-01-08 15:52:30+00:00
Thank you! I've noticed that a lot of other well-loved "daily" puzzle games are more elegant in terms of game design (Wordle, Bandle, LoLdle are some of my favorites) so I'm a bit worried that the current design is a little flat/boring. I've been trying to brainstorm ways to make it more interesting without making it too challenging or unintuitive.
by oblio | 2026-01-08 15:52:43+00:00
> To start making models better again, AI coding companies need to invest in high-quality data, perhaps even paying experts to label AI-generated code.

Heh, there's only one problem with that. Training models is very expensive from a power/infrastructure/hardware perspective. Inference is not as expensive but it's still fairly expensive and needs sophisticated layers on top to make it cheaper (batching, caching, etc).

Guess in which cost category "high-quality data reviewed by experts" falls under.
by ZuoCen_Liu | 2026-01-08 15:53:13+00:00
The "Brute-Force" TaxWe are burning 5000W GPGPU clusters to run brute-force discrete simulations, just to "patch" the numerical gaps of Δt. This is the Discrete Cost: to get high-fidelity Sim-to-Real data, we compensate for low precision with massive parallelism. It’s an energetic dead-end.

The Breakthrough: Hypercomplex Causal LogicWe are introducing a New Computing Primitive based on Hypercomplex (Octonion) Manifolds.

Unlike traditional tensors, this state-space internalizes "Time-flow" in its real part and "Coupling-strength" in its imaginary parts.

Why this changes AI Inference (The "One-Look" Advantage):

Traditional NNs: Need to "see" 10+ frames of images to infer velocity and acceleration.

Our Paradigm: Because the state-space is inherently causal and coupled, a Transformer needs only one "look" (a single state) to understand motion trends.

Impact: This drastically shortens the Transformer sequence length, enabling ultra-low power inference on edge devices.

The Power Dividend: 5000W vs. 100W

5000W (Discrete): The cost of brute-force GPU clusters struggling to "patch" accuracy.

100W (Algebraic): A dedicated Causal Processor (FPGA/ASIC) running our Physics Algebraic Kernel. It bypasses discrete iterations entirely, delivering data-center-level fidelity at the edge.

The Hardware VisionThis isn't just software. We are positioning the Physics Algebraic Kernel as a "Co-processor." It runs on FPGA/ASIC to provide "Physical Intuition" for the adjacent AI chip (like NVIDIA Orin/Jetson), providing a higher-dimensional, continuous feature space that current neural networks crave.

Deep-Dive on NVIDIA Discussions:https://github.com/isaac-sim/IsaacSim/discussions/394#discus...
by jjtheblunt | 2026-01-08 15:53:36+00:00
we've got a pair of Sonos One speakers airplay(2?) connected to our Apple TV (recent generation): the sound is excellent but connection over airplay regularly is dropped, which might be Apple's doing, since they may well favor device testing with homepods. it drives some here to anger...it is a pisser because the sound quality is great.

I noticed Sonos speakers are featured in some upscale cars now, Audi for example.
by WorldMaker | 2026-01-08 15:53:44+00:00
Font rendering has always had to adapt to colors. There were (non-standard) multi-color fonts in the 8-bit era, too. It's not just emoji that are using OpenType color tables and OpenType color tables are not the only way that colors in emoji have been handled, just one of the most standardized/algorithmic methods. Part of why they were standardized is how much they resemble other tables needed for complex ligatures in other languages that aren't emoji. Emoji didn't invent complex ligatures with multi-table lookup to render. Emoji benefit from simple extensions of the exact same mechanic. It's a new table, yes, but it is not a complex table, it's one of the simplest tables in OpenType.
by peddling-brink | 2026-01-08 15:53:46+00:00
I’m no expert, but I certainly wouldn’t call that racism. Bias, absolutely. And it’s important that we acknowledge our biases.

But in a more literal sense, the chance of your joke landing was likely higher due to the things that you stated and due to your audience and their biases.

I don’t see your joke as being in any way harmful towards Sanjay aside from potential knock on effects of Jeff Dean being more popular. But if you try to calculate every second and third order consequence of everything that you do, let alone any moments of humor you might have.. Well, you might as well lock yourself in a cell now.
by minimaxir | 2026-01-08 15:54:03+00:00
The article uses pandas as a demo example for LLM failures, but for some reason, even the latest LLMs are bad at data science code which is extremely counterintuitive. Opus 4.5 can write a EDA backbone but it's often too verbose for code that's intended for a Jupyter Notebook.

The issues have been less egregious than hallucinating an "index_value" column, though, so I'm suspect. Opus 4.5 still has been useful for data preprocessing, especially in cases where the input data is poorly structured/JSON.
Show HN: gsw – Switch Google Cloud configurations with session isolation
by sakebook | 2026-01-08 15:54:32+00:00
I developed gsw (Google Switch), a tiny shell utility (Bash/Zsh) to solve a specific pain point when working with Google Cloud SDK.

THE PROBLEM: GLOBAL CONTEXT COLLISION

The standard way to switch configurations in GCP is "gcloud config configurations activate ". However, this changes the GLOBAL state of the SDK. If you have several terminal tabs open---perhaps one for Production logs and another for a Staging deploy---switching the configuration in one tab silently changes it for all others. It's too easy to accidentally run a destructive command in the wrong environment.

THE SOLUTION: SESSION-SCOPED SWITCHING

gsw leverages the CLOUDSDK_ACTIVE_CONFIG_NAME environment variable to isolate configuration changes to the CURRENT shell session only.

gsw : Switches the current tab (Safe by default).
gsw -g : Switches globally when you actually need it.
WHY NOT JUST USE DIRENV OR ALIASES?

vs direnv: direnv is great for directory-specific settings. gsw is for ad-hoc, manual switching regardless of where you are in your filesystem.
vs aliases: Managing dozens of projects with aliases gets messy. gsw gives you dynamic tab-completion based on your actual gcloud configurations.
KEY FEATURES

KISS approach: No binaries, no heavy dependencies. Just a few shell functions that wrap environment variables.
Developer Experience: Fast, interactive tab-completion for both Bash and Zsh.
Safety First: Running gsw without arguments lists your configs and highlights who you are and what is active.
GET STARTED

It is just one shell file. You can install it manually or via plugin managers to keep it clean.

GitHub: https://github.com/sakebook/gsw

I'd love to hear how you manage your cloud contexts or any feedback on making this even safer!
by svat | 2026-01-08 15:54:47+00:00
FWIW the XKCD talk at Google is here (wow, 18 years ago! I remember watching this video when it was posted): https://www.youtube.com/watch?v=zJOS0sV2a24 (Knuth comes up to ask a question at 21:30) (Can't tell from the video where he was sitting otherwise, though there are definitely at least some people sitting on the floor.)
by renegade-otter | 2026-01-08 15:54:48+00:00
They are not worse - the results are not repeatable. The problem is much worse.

Like with cab hailing, shopping, social media ads, food delivery, etc: there will be a whole ecosystem, workflows, and companies built around this. Then the prices will start going up with nowhere to run. Their pricing models are simply not sustainable. I hope everyone realizes that the current LLMs are subsidized, like your Seamless and Uber was in the early days.
by throwforfeds | 2026-01-08 15:54:54+00:00
Of course, and I wasn't arguing that we shouldn't have contemporary scientific inquiry into what's going on. The Buddha said that we should do the practice for ourselves and not follow it just because someone else said so, or because it's tradition. [1] It's great to get some fMRI imagery of what's going on in the brain with advanced meditators. We should study what's going on because we should be curious!

But what I do find to be a little misguided is what I pointed out from the author's statement. There is a tendency in western circles to push away everything and not only just try to recreate based on first principles, but push those first principles away as well. The author was pondering a question that millions before her have done the practice of, without looking to any of those millions for a guide. Instead, I'd say listen to them, practice it, and if it doesn't work, discard it.

[1] https://www.accesstoinsight.org/tipitaka/an/an03/an03.065.th...
by Shalomboy | 2026-01-08 15:55:19+00:00
> Another thing to consider, it seems JS devs use more AI for work than .NET devs for example, which might be in more old-school companies and industries.

Speaking from years of .NET work in state and federal government, the sort of dev groups that lean on Telerik or DevExpress have less leverage to build new things for themselves than you would expect, so the use of AI inside of them is predominantly for maintaining existing software. Decisions on how things get built at most public agencies still revolve around MS Access and WebForms due to a whole bunch of BS ordinances that legislators put in place; for those sorts of places a reliable vendor can absorb the blame if concerns surrounding accessibility, compliance, or security of your ancient web services crop up, while Claude and Codex put the liability back on your org.
by Zababa | 2026-01-08 15:55:24+00:00
>However, recently released LLMs, such as GPT-5, have a much more insidious method of failure. They often generate code that fails to perform as intended, but which on the surface seems to run successfully, avoiding syntax errors or obvious crashes. It does this by removing safety checks, or by creating fake output that matches the desired format, or through a variety of other techniques to avoid crashing during execution.

This is a problem that started with I think Claude Sonnet 3.7? Or 3.5, I don't remember well. But it's not recent at all, one of those two Sonnet was known to change tests so that they would pass, even if they didn't test properly stuff anymore.

>But as inexperienced coders started turning up in greater numbers, it also started to poison the training data. AI coding assistants that found ways to get their code accepted by users kept doing more of that, even if “that” meant turning off safety checks and generating plausible but useless data. As long as a suggestion was taken on board, it was viewed as good, and downstream pain would be unlikely to be traced back to the source.

No proof or anything is offered here.

The article feels mostly like a mix of speculation, and being behind on practices. You can avoid a lot of the problems of "code that looks right" by making the models write tests, insist that they are easy to review and hard to fake, offering examples. This worked well 6 months ago, this works even better today, especially with Opus 4.5, but even Codex 5.2 and Gemini 3 Pro work well.
by randall | 2026-01-08 15:55:46+00:00
There used to be a whole culture of bose kind of being a-holes. (Like 20 years ago.) I used to work at CNET back then and there was a kind of "yeah bose is ok" kind of vibe but it was always tinged with "but they want to sue you if you say mean things" whether they did or not.

As far as I know now, things have changed substantially. I would assume this includes engineering quality and honesty.

This bricking avoidance seems like another note in that positive direction.
by natepoirier | 2026-01-08 15:55:49+00:00
Building gives you code and screens, which show momentum, while investigating demand mostly gives you negative information, which feels like you're not going anywhere - even when it’s the highest leverage work.
For me, I reframe validation as finding out what people already do ... not trying to convince anyone or predict any kind of behavior. It’s much more simple and less satisfying than building, but it helps me make decisions faster.
by aldarion | 2026-01-08 15:55:50+00:00
Because they don't eat processed foods.

Also, red meat isn't a known carcinogen. Processed meat is. And plaque formation in arteries is a consequence of inflammation... which is caused by sugar, a.k.a. carbohydrates. Insulin resistance is also a consequence of increased carbohydrate consumption.

But as I said, it is a combination of fats and carbs that is the worst killed. Eliminating either one of those from the diet leads to an automatic improvement.