MurphyA/hacker-news huggingface dataset:
by mapontosevenths | 2025-12-08 15:43:22+00:00
It's been repeated a huge number of time since, and widely debated. When Libet first did the experiment it was only like 200ms before the mind become consciously aware of the decision. More recent studies have shown they can predict actions up to 7-10 seconds before the subject is aware of having made a decision.

It's pretty hard to argue that you're really "free" to make a different decision if your body knew which you would choose 7 seconds before you became aware of it.

I mean, those long term predictions were only something like 60% accurate, but still, the preponderance of evidence says that those decisions are deterministic and we keep finding new ways to predict the outcome sooner and with higher accuracy.

https://pubmed.ncbi.nlm.nih.gov/18408715/
by Sanzig | 2025-12-08 15:43:49+00:00
Tailscale is a bit more than a VPN. It operates in a mesh configuration rather than a traditional VPN concentrator setup. Tailscale's control plane orchestrates NAT traversal for devices on the Tailnet (through techniques like UDP hole punching) and allows them to establish direct Wireguard tunnels between them. That way, there's no VPN concentrator bottleneck because there's no concentrator at all, every device establishes tunnels to every other device.
by jwcooper | 2025-12-08 15:44:16+00:00
You can do that now, and for at least the last year.

Very few games don't work anymore, and most that don't are using kernel level anti-cheat or are generally hostile to users anyways (Fortnite and Destiny 2 could work, but they actively block Linux).

I main Fedora with an Nvidia 3080 and haven't had issues for quite some time now.
by mingus88 | 2025-12-08 15:44:18+00:00
IMO no 3rd party app is worth using on those devices.

My parents pay over $300/mo for an Xfinity bundle. It includes everything (phone, internet, and all streaming services on one bill)

The paramount+ app on the Xfinity box took TEN MINUTES to load a show. This is after crashing three times back to the logo.

Xfinity warns that it’s a 3P app and they aren’t responsible for it but it should be criminal to take the money and subject elderly people to this under spec hardware. Even live sports will pause and stutter.
by underlipton | 2025-12-08 15:44:36+00:00
Delivery in particular remains underpriced at even the high prices we see. The way the platforms are set up, you're basically paying to chauffeur a single order straight to your house, on-demand. Mobile tech and "own car" efficiencies don't begin to cover those costs. The problem was that this is the kind of service that they had to offer in order to supersede existing delivery.

In an ideal world, you'd instead have drivers assigned to either particular neighborhoods or particular restaurants, allowing for order-stacking and predictable routes. Bonus for set-time daily deliveries (get your order in before 6 or have to wait until 9). Bigger bonus for set neighborhood drop-off points (like those consolidated mailboxes, but warming compartments). Anything more bespoke would cost extra.

Unfortunately, the balance of inefficient operations, decreasing competition, and "line go up" is that prices have to increase.
by FabHK | 2025-12-08 15:44:44+00:00
> nobody cares about good tech

Indeed. For example: Chia is arguably decent tech (better than Bitcoin), built by Bram Cohen (of BitTorrent fame), innovative PoSpace+Time. But nobody cares, it's at #450 in market cap, way down below Doge (#10), $TRUMP (#72), Fartcoin (#144), Melania (#375).
by LanceH | 2025-12-08 15:44:51+00:00
Stomp on brakes is pretty basic, and all that was ever needed for overpowering a prius's engine/motor.

This "scandal" was never about mechanical failures. It was almost certainly about driver error and mass hysteria.

As for Toyota settling, had this been Ford or Chevy, the government wouldn't have had the appetite to go after them for what was always a non-issue. It was just less expensive for Toyota to fix floor mats and pay a billion to put it all behind them.
by mattstir | 2025-12-08 15:45:05+00:00
> The block chain is, and always was, an extremely inconvenient database.

That's the entire point when the goal is to achieve a public, immutable, decentralized ledger that prevents double-payments without needing to trust a third-party to adjudicate properly. It being inconvenient makes it exceptionally difficult to edit history.

Whether that's a useful goal is less clear when nearly all of modern society relies on trusting parties at some point along the way (will the thing you bought be delivered to you? Will the service you purchased actually be rendered? etc).

> Maybe it goes to show how few people understand economics and anthropology

A financial process being unwieldy hasn't really been an issue historically. Why are most publicly issued stocks in the US owned by Cede and Company for example? No one that has stocks really thinks about the underlying system (the fact that they have contractual rights to stocks rather than actually owning stocks), as long as it ultimately works.

Where things have broken down in my opinion is how centralized the systems have become with massive exchanges being the only realistic way to interact with them. In the same way that a bicycle wasn't designed to be a moving van, these systems weren't designed to be centralized. With that being the reality though, the entire blockchain backbone is mostly useless, and at that point it really is an inconvenient database.
by coldtea | 2025-12-08 15:45:13+00:00
>Except in cases where the training data is more wrong than correct (e.g. niche expertise where the vox pop is wrong)

Same for human knowledge though. Learn from society/school/etc that X is Y, and you repeat X is Y, even if it's not.

>However, an LLM no more deals in Q&A than in facts. It only typically replies to a question with an answer because that itself is statistically most likely, and the words of the answer are just selected one at a time in normal LLM fashion.

And how is that different than how we build up an answer? Do we have a "correct facts" repository with fixed answers to every possibly question, or we just assemble our training data from a weighted graph (or holographic) store of factoids and memories, and our answers are also non deterministic?
by TYPE_FASTER | 2025-12-08 15:45:19+00:00
At one point years ago, there was an iOS release where the recently used apps would render, then re-order themselves after a second or two. You could tell it was caching then dynamically updating. It was frustrating from a UX perspective because you would go to tap on an app and by the time you tapped, it would open a different app because they had re-ordered themselves.

It was fixed in an update, but to me that's the canary in the coal mine that priority is wrong. Apple will be ok without Steve as long as somebody is obsessed with the UX being very good. When I see the quality of the UX experience degrading while other UX changes are made that don't improve the basic UX, then there's a problem.

I subscribe to Apple Music, and have built playlists on the service. The fact that I have to enable sync (which then wastes 70G of space on my iPhone) to use my playlists is BS. I don't see a technical reason for it. The only conclusion I can come to is they want to drive storage subscriptions by taking up space using music sync. If anybody wants to explain why sync needs to be enabled, that would be cool, but is a really concerning product management decision IMO.
by jraph | 2025-12-08 15:46:06+00:00
Then make this specific solution open source, and make the laywers pay for support and roadmap decisions / features they require! Make them pay for integrations with Azure AD and struff like this! Make them pay for the binary! The possibilities are endless, it can work!

You can aim for better than "where MS is".

This could constitute a killer argument to make your solution appealing.
by alphazard | 2025-12-08 15:46:25+00:00
Write-time understandings no, write-time language yes. You can always change it, which is what happened in the case of women and slaves. To be clear, changing the text is the correct way to handle that, we shouldn't have just relied on the understandings of people changing over time to fix those issues.

The famous example you give illustrates why a system without precise meaning cannot work. It can seem like it works when lots of people act in good faith, but it quickly breaks down with even a few actors play the actual game instead of some "spirit of the game". In 1973, judges ruled one way, playing the actual game to accomplish a goal, and then everyone acted surprised in 2022, when the same tactics (playing the actual game not the spirit) reverted the decision.

I'm going to take a guess, and assume that you were in favor of the 1973 understanding and not the 2022 understanding. It would have been nice for that to have been captured precisely in some kind of specification, instead of enacted with a volatile read-time mechanism.
by jacquesm | 2025-12-08 15:46:29+00:00
Funny, I had the exact opposite reaction. Things I had taken for granted all my life suddenly became un-anchored and as a result so did I. I have never felt an actual feeling of panic that threatened to overwhelm me before that happened and it was a very mild earthquake. I had to really force myself to calm down and stay rational and do what was the safest rather than to give in to the 'flee' reflex.

The problem with earthquakes is when they start you know you're in one but you have no idea where you're headed, whether this is as bad as it gets or whether you're going to end up in a pile of collapsed rubble and what is the best decision greatly hinges on something you can't know ahead of time, which is the peak magnitude and the kind of earthquake you are experiencing.
by randerson | 2025-12-08 15:46:33+00:00
I rarely agree with Trump, but I'm a former exec at a public company and he's not wrong. You need a horde of lawyers and accountants and investor relations and SOX compliance people and auditors etc for the earnings reports. SOX adds burdensome processes at every layer of the organization. Your CFO and CEO will be preoccupied by earnings. It's a real disincentive for a small/medium cap company to go (or stay) public. A PE firm taking a company private can get rid of all this overhead on Day 1.

Not to mention, quarterly reports incentivize a company to focus on the current quarter instead of longer-term sustainability. Reporting twice a year doesn't solve all the above problems, but it sure would reduce them a little.
Show HN: PyGraphina – A Graph Library for Python
by habedi0 | 2025-12-08 15:46:36+00:00
Hi everyone,

I've made an early version of a new graph data science and analytics library for Python named PyGraphina. It's written in Rust and at the moment includes implementations for a large collection of popular graph algorithms, including:

- Centrality metrics: PageRank, betweenness centrality, etc.

- Community detection algorithms like connected components, Louvain, etc.

- Heuristics for hard graph algorithms, such as Max clique finding.

- Link prediction algorithms like Jaccard coefficients, Adamic-Adar index, etc.

The aim of the project is to make PyGraphina as feature-rich as NetworkX, with the performance benefits of Rust.

Project's GitHub repo: https://github.com/habedi/graphina/tree/main/pygraphina

PyGraphina's documentation: https://habedi.github.io/graphina/python
by ndsipa_pomu | 2025-12-08 15:47:26+00:00
This makes no sense to me. Surely DEI reinforces those 2 clauses?

Without DEI, it's just white men that will be hired and generally, it'll be friends of friends with no regard to their competency. DEI is an attempt to level the playing field as otherwise, racist/sexist employers will continue to be racist and sexist.
by AndrejD | 2025-12-08 15:47:43+00:00
I tried Rentgen on one of our internal APIs and was genuinely impressed with the results. The tool is surprisingly powerful — it quickly exposed issues we hadn’t noticed before. The interface is straightforward, and with just one request payload you can generate hundreds of tests, including security, performance, and various edge-case scenarios. Overall, a very useful and practical tool. Great work!
by ryandrake | 2025-12-08 15:48:19+00:00
LLMs all behave as if they are semi-competent (yet eager, ambitious, and career-minded) interns or administrative assistants, working for a powerful CEO-founder. All sycophancy, confidence and positive energy. "You're absolutely right!" "Here's the answer you are looking for!" "Let me do that for you immediately!" "Here is everything I know about what you just mentioned." Never admitting a mistake unless you directly point it out, and then all sorry-this and apologize-that and "here's the actual answer!" It's exactly the kind of personality you always see bubbling up into the orbit of a rich and powerful tech CEO.

No surprise that these products are all dreamt up by powerful tech CEOs who are used to all of their human interactions being with servile people-pleasers. I bet each and every one of them are subtly or overtly shaped by feedback from executives about how they should respond to conversation.
by pardon_me | 2025-12-08 15:48:52+00:00
The most promising aspect for machine learning in electrical and electronic systems is the quantity of precise and correct training data we already have, which keeps growing. This is excellent for tasks such as ASIC/FPGA/general chip design, PCB design, electrical systems design, AOI (automated optical inspection), etc.

The main task of existing tools is rule-based checks and flagging errors for attention (like a compiler), because there is simply too much for a human to think about. The rules are based on physics and manufacturing constraints--precise known quantities--leading to output accuracy which can be verified up to 100%. The output is a known-functioning solution and/or simulation (unless the tool is flawed).

Most of these design tools include auto-design (chips)/auto-routing (PCBs) features, but they are notoriously poor due to being too heavily rule-based. Similar to the Photoshop "Content Aware Fill" feature (released 15 years ago!), where the algorithm tries to fill in a selection by guessing values based on the pixels surrounding it. It can work exceptionally well, until it doesn't, due to lacking correct context, at which point the work needs to be done manually (by someone knowledgeable).

"Hallucinogenic" or diffusion-based AI (LLM) algorithms do not readily learn or repeat procedures with high accuracy, but instead look at the problem holistically, much like a human; weights of neural nets almost light up with possible solutions. Any rules are loose, context-based, interconnected, often invisible, and all based on experience.

LLM tools as features on the design-side could be very promising, as existing rule-based algorithms could be integrated in the design-loop feedback to ground them in reality and reiterate the context. Combined with the precise rule-based checking and excellent quality training data, it provides a very promising path, and more so than tasks in most fields as the final output can still be rule-checked with existing algorithms.

In the near-future I expect basic designs can be created with minimal knowledge. EEs and electrical designer "experts" will only be needed to design and manufacture the tools, to verify designs, and to implement complex/critical projects.

In a sane world, this knowledge-barrier drop should encourage and grow the entire field, as worldwide costs for new systems and upgrades decreases. It has the potential to boost global standards of living. We shouldn't have to be worrying about losing jobs, nor weighing up extortionately priced tools vs. selling our data.
by ericol | 2025-12-08 15:49:16+00:00
> Ok, so does anyone remember 'Watson'? It was the chatgpt before chatgpt. they built it in house

I do. I remember going to a chat once where they wanted to get people on-board in using it. It was 90 minutes of hot air. They "showed" how Watson worked and how to implement things, and I think every single person in the room knew they were full of it. Imagine we were all engineers and there were no questions at the end.

Comparing Watson to LLMs is like comparing a rock to an AIM-9 Sidewinder.
by johnfn | 2025-12-08 15:49:17+00:00
I wrote a comment saying that this should be possible with a proper playwright harness and screenshot taking. My comment ended up in the negatives (though curiously no one stopped to explain why), as if I was saying something so absurdly inaccurate that it wasn’t even worth rebutting. Thank you for actually running the experiment and proving it - I was almost annoyed enough to do it myself.

I couldn’t understand why it had happened - it felt about as logical to my mind as writing a comment that Rust was faster than Node. I feel there is a strong anti-AI sentiment here, to the point that people will ignore evidence presented directly to them.

Personal vendetta aside, I enjoyed this post! You had some clever tricks I wouldn’t have considered. In fact, the idea of producing a pixel diff as output was particularly imaginative. And the bit about autoformalization definitely hits on something I’ve been feeling when working with AI recently.

EDIT: I notice my comment yesterday is in the positives. Please don’t vote it up. That was not my intention here.
by Zak | 2025-12-08 15:49:40+00:00
It's really hard to come up with a product name as good as "iPhone". Simple does not mean easy.

Unless they're writing a phone review, nobody ever says things like "I took a picture with my Galaxy", or "I edited the video on my Pixel", but substitute "iPhone" and they sound normal.

It also hasn't become generic. Nobody calls another brand of phone an "iPhone" unless they actually mistook it for one.
by DaveZale | 2025-12-08 15:49:49+00:00
really neat!

But over the past couple of decades, HFTs and dark pools have arisen to manipulate prices of common stock to accomodate large clients/orders.

Options prices, especially leaps, may provide a better indicator. This is the space where the hedge funds make billions while the "retail" crowd agonizes over mysterious fluctuations in common stock prices. Like the arrow in the Fedex logo, once you see it, you'll always see it ;-)
by underlipton | 2025-12-08 15:49:53+00:00
Add another: the various platforms talk to each other (or analyze driver movement) in order to manipulate order offerings in such a way as to discourage drivers from taking orders from more than one app at once. One app will wait until the other has confirmed an accepted order before deluging you with their own orders, all taking you in the opposite direction (which makes you late for one or more deliveries, giving cause to terminate your contract).
by tadzikpk | 2025-12-08 15:50:08+00:00
I live in MA and wish that this were true, but do you have data / evidence to support that it rarely happens? Also, I don't know if you have tried to get your $10, but it's not like the sign is always obvious and every time I've tried, it's not like the cashier says "oops" and gives you the thing for free - they call a manager, the manager argues with you, other customers complain about the checkout delay you've created... there's social pressure there so I can understand why customers would not do this even when they can.
by handojin | 2025-12-08 15:50:17+00:00
"We show that backpropagated neural networks trained on a variety of datasets - which could be disjoint and unrelated - diverse hyper-parameter settings, initializations and regularization methods, often learn an architecture-specific, layer-wise similar, low-rank joint subspaces (we refer to this as the Universal Subspace). We provide the first large-scale empirical analysis - across a diverse set of models - that neural networks tend to converge to these joint subspaces, largely independent of their initialization or the specific data used for training."
by adolph | 2025-12-08 15:50:28+00:00
Since when was expense a problem for defense spending?

In the video, the narrator also claims that Ada compilers were expensive and thus students were dissuaded from trying it out. However, in researching this comment I founds that the Gnat project has been around since the early 90s. Maybe it wasn't complete enough until much later and maybe potential students of the time weren't using GNU?

The GNAT project started in 1992 when the United States Air Force awarded New York University (NYU) a contract to build a free compiler for Ada to help with the Ada 9X standardization process. The 3-million-dollar contract required the use of the GNU GPL for all development, and assigned the copyright to the Free Software Foundation.

https://en.wikipedia.org/wiki/GNAT
by glimmung | 2025-12-08 15:50:58+00:00
I've been using a VPN on and off for years when there was a privacy concern.

Now there is a privacy concern 24x7, and so I use a VPN 24x7. A bad law and risk-averse sites have made the web a complete PITA without one.

The number of e.g. news sites and other vanilla content that requires intrusive checks, photo-ID etc. is astonishing.

I wonder how many parents have had to ask their kids for help setting a VPN up? <sigh>
by mitthrowaway2 | 2025-12-08 15:51:02+00:00
A superintelligence would understand that you don't want it to kill people in order to make paperclips. But it will ultimately do what it wants -- that is, follow its objectives -- and if any random quirk of reinforcement learning leaves it valuing paperclip production above human life, it wouldn't care about your objections, except insofar as it can use them to manipulate you.
by alias_neo | 2025-12-08 15:51:31+00:00
I got fed up about a week ago and ditched my Nvidia GPU for a 9070XT.

I run CachyOS and have been having a nightmare of a time on Wayland with my 3D Printer slicer and other tools I use my computer for being unusable.

The only thing that has ever kept me on Nvidia all these years is that they have been killing AMD performance wise for gaming.

The 9070XT is easily performant enough for the gaming I'm doing at the moment, and I can finally ditch the last major headache I've had in two and a half decades of being a Linux user - NVIDIA drivers - good riddance.

I don't play online games other than Helldivers 2 (so anti-cheat is a non-issue) which is working just fine at 70-80FPS max settings in 4K. Also getting good performance with RT off playing Ghostwire in 4K with settings as high as I can get them while staying above 60 FPS with Freesync.

EDIT: 9070XT seems to have a bit of headroom too I got the Asus PRIME OC version; Using LACT I upped the power limit from the stock 317W to 340W and undervolted by -100mv (YMMV on this value) and can get a decent chunk of extra performance out of it.