MurphyA/hacker-news huggingface dataset:
by notmyjob | 2025-10-18 14:21:24+00:00
Look, most of the work of state congressional reps is getting pork approved and garnering federal funds for the state. If you cannot understand that and grasp how having representatives in both groups helps the state then I can’t help you.

Prop 50 is bad for the state as a whole. It is also undemocratic but let’s not pretend that matters to those involved. Those involved in this who work for the state (people like Gavin) should care about the fate of the state they are supposedly working for more than their own presidential ambitions, no? Especially when that person has little chance of winning at the national level because they do really stupid things like prop 50.
by jgrahamc | 2025-10-18 14:21:28+00:00
If the idea is this: "Many quartz watches do their best to hide away any electronic components from view. The design concept for this watch was to embrace those digital components instead [...]" then I'd argue this watch that I built fulfils the requirement better: https://blog.jgc.org/2022/12/the-rogers-watch-retro-display-...
by steveBK123 | 2025-10-18 14:21:37+00:00
It's nice seeing commentary from someone who is both knowledgable in AI and NOT trying to pump the AI bag.

Right now the median actor in the space loudly proclaims AGI is right around the corner, while rolling out pornbots/ads/in-chat-shopping, which generally seems at odds with a real belief that AGI is close (TAM of AGI must be exponentially larger than the former).
by incomingpain | 2025-10-18 14:21:37+00:00
Some projects have decided to decline AI contributions. This will have the big impact of making them stop being relevant.

Then you have the big impact of some people find a bug, using ai to quickly fix it, and then never send it upstream.

But then also the speed at which apps are developed and quality of the code will improve by the developers who fix issue.s

We're also going to get a load more options. new projects in languages that dont exist yet.

I guess what im predicting. its not that open source suddenly will be 50% better on the project we have now. It's more likely the added productivity will make open source wider.
by Forgeties79 | 2025-10-18 14:21:53+00:00
I get a lot of grief for it from a few people but the simple fact is it’s gone from an unthinkable possibility to something I would consider a single-digit- percentage possibility. At that point it feels like something I need to at least be moderately prepared for. Especially as someone in the gulf south.

It just doesn’t feel very safe down here anymore. Watching ICE roll through in full equipment on armored vehicles during Mardi Gras this year was a serious wake up call. That’s not the kind of show of force you do for shits and giggles. That’s textbook “send them a message.”
by nkozyra | 2025-10-18 14:22:48+00:00
> But I mean, you should be able to be an odd duck and also be a director of a brand, as long as you behaviour isn’t hurting anyone…

I think the canonical example here is the Kirn Corksniffer[1] which could have been avoided with some foresight and subsequently a quick apology, but ego can sometimes get in the way.

Behringer definitely made bad products for a very long time, and while I appreciate the increase in quality the synth recreations don't really blow my mind. They're low cost, they're hardware, but almost all of them fall short of the originals.

[1] https://www.vice.com/en/article/a-major-synth-company-create...?
by subjectivationx | 2025-10-18 14:23:05+00:00
Everyone reading this understands the meaning of a sunrise. It is a wonderful example of the use theory of meaning.

If you raised a baby inside a windowless solitary confinement cell for 20 years and then one day show them the sunrise on a video monitor, they still don't understand the meaning of a sunrise.

Trying to extract the meaning of a sunrise by a machine from the syntax of a sunrise data corpus is just totally absurd.

You could extract some statistical regularity from the pixel data of the sunrise video monitor or sunrise data corpus. That model may provide some useful results that can then be used in the lived world.

Pretending the model understands a sunrise though is just nonsense.

Showing the sunrise statistical model has some use in the lived world as proof the model understands a sunrise I would say borders on intellectual fraud considering a human doing the same thing wouldn't understand a sunrise either.
by hopelite | 2025-10-18 14:23:19+00:00
I’m not sure an ad hominem assault is any different. You make proclamations without any evidence as if what you say has any more credibility than the next person. In fact, this response makes a reasonable person discount you.

Sure, it reads like some biased and coping, possibly even interested or paid hit-piece as if what happens can be changed by just being really negative about LLMs, but maybe consider taking your own advice there, kid; you know, an extended break.
by bigtunacan | 2025-10-18 14:23:34+00:00
It’s not just about practicality. Ruby is using message passing, not method calling. This is fundamentally different and a bit foreign to the larger community. Then ruby layers syntactic sugar on top that hides this.

Behind the scenes everything is a message passed using __send__ and you can do this directly as well, but you generally don’t.

So when you write

5.times { puts "Hello" }

It’s sort of expected by the average programmer that you are telling 5 to call the times method and expect it to exist and do what it’s told.

In reality you have indirectly sent a message that looks like

5.__send__(:times) { puts "Hello" }

What we are really doing is sending a message to 5 (the receiver) and giving it the opportunity to decide how to respond. This is where method_missing comes in to allow responding in a custom fashion regardless if a method was explicitly defined.

So you’re not telling 5 to call the method times, rather you are asking, “Hey 5, do you know how to handle the message times?”

These are fundamentally different things. This is actually super important and honestly hard to really grok _especially_ in ruby because of the syntactic sugar. I came from a C/C++ background originally, then Java and then moved to Ruby. After a few years I thought I understood this difference, but honestly it wasn’t until I spent a couple years using Objective-C where message passing is happening much more explicitly that I was able to truly understand the difference in a way that it became intuitive.
by catketch | 2025-10-18 14:25:38+00:00
Different take: depreciated EVs mean they are more affordable on the used market, making them accessible to more people that can't make a $50-80K+ new vehicle work for their budgets. First adopters and EV enthusiast will continue to push the new market, but the tent opens up for more drivers. The next hurdle will be solving disparity of convenience between those that can have home chargers and those that live in apartments or with street parking.

At least in the 4-5 years ago, there was not much of a used market, not much vehicle choice beyond Tesla that was good price/performance, and tough going on charging infrastructure (again outside of Tesla)

That landscape has not completely changed, but it is much different. There's a lot of actual vehicle choice (even if most are still some type of SUV/CUV), and charging situation is reasonable, especially with opening up of NACS

There's a big component of political action against EVs, solar, etc but I think it will just slow, not stop the momentum in the US. With 2 BEVs and a PHEV, I don't see our family going back to ICE vehicles. I miss manual transmissions, that's about it
by ux | 2025-10-18 14:25:45+00:00
Finding the sign of the distance has been extremely challenging to me in many ways, so I'm very curious about the approach you're presenting. The snippet you shared has a "a³-bcd ≤ 0" formula which is all I get without more context. Can you elaborate on it or provide resources?

The winding number logic is usually super involved, especially when multiple sub-shapes start overlap and subtracting each other. Is this covered or orthogonal to what you are talking about?
by dardeaup | 2025-10-18 14:26:28+00:00
Delphi is still very impressive. However, they missed out on a much greater opportunity. Part of Delphi's crown jewels is VCL which can only be used on Windows. If you use Delphi for an OS other than Windows you have to use FireMonkey/FMX. Lazarus has LCL which is VERY similar to VCL, but LCL on Lazarus is not limited to Windows. One can write a LCL application and it works the same on Windows, macOS, and Linux. If Delphi had extended VCL to macOS and Linux it would have become much more valuable. Just my $0.02.
by Swizec | 2025-10-18 14:26:39+00:00
> it’s [US passport] one of only half a dozen passports that lets you visit the US visa free.

That is just false. EU passports can travel to USA Visa free and that’s 27 countries right there.

edit: Oh unless you count ESTA as a type of visa. You have to fill out a 5min always-approved form online.
by 1313ed01 | 2025-10-18 14:26:42+00:00
The nicest thing about programming for DOS (or probably any old home computer or console?) is that you are in full control of inputs and timing. If you only need to update the screen when the user hits a key for instance you can just call a function to wait for the next key-press, handle that, ask for the next... There is no async, no callbacks, no events, no threads. Nothing is easier than just imperative code doing things one line then the next, then the next. You can still have a main loop, but you do not need to, and if some function you call somewhere to handle something wants to wait for a key-press before returning it can do that and you do not have to yield or anything.

I'd love to see some modern environment replicate that somehow. Let us pretend everything is simple and synchronous even if it very much isn't.
by bbor | 2025-10-18 14:27:04+00:00
Exactly this, well said. Symbolic AI works so well that we don’t really think of it as AI anymore!

I know I for one was shocked to take my first AI course in undergrad and discover that it was mostly graph search algorithms… To say the least, those are still helpful in systems built around LLMs.

Which, of course, is what makes Mr. Marcus so painfully wrong!
by futureshock | 2025-10-18 14:27:48+00:00
I’ll borrow ideas from investing: financial independence, diversification and optionality. If you have enough money you can free yourself from the labor market, but you are still deeply tied to your home country. A second citizenship gives you geopolitical independence. And just like diverse investments protect you from the failure of a specific asset, diverse countries can protect you from, for example, a collapse in heath care, a housing crisis or a currency crisis. And most importantly, its like an options contract on life. You have the option, not the commitment to take a high value move to a new country. If the fortunes of your current country sink and your second country rise, you can exercise your option.

There’s a reason people are willing to spend so much on golden visas with the pathway to citizenship.
by riazrizvi | 2025-10-18 14:28:21+00:00
I’ve come to align with Trump’s right wing politics, based on their direct announcements on Youtube and policy decisions. What they are doing makes economic and strategic sense. I have also come to see the general hostility as emanating from people who are fed deranged distortions on the Trump admin’s decisions, likely fostered by narrow business interests and foreign entities who don’t care about the plight of America. This is after 23 years of Democrat support, since I moved to this country.
by ben_w | 2025-10-18 14:28:46+00:00
> If you don't optimize power consumption you're going to increase surface area required to build it. There are hard physical limits having to do with signal propagation times.

While true, that probably stopped being an important constraint around the time we switched from thermionic valves to transistors as the fundamental unit of computation.

To be deliberately extreme: if we built cubic-kilometre scale compute hardware where each such structure only modelled a single cortical column from a human's brain, and then spread multiple of these out evenly around the full volume within Earth's geosynchronous orbital altitude until we had enough to represent a full human brain, that would still be on par with human synapses.

Synapses just aren't very fast.
by timschmidt | 2025-10-18 14:29:08+00:00
None of your examples refute the direct evidence of internal world model building which has been demonstrated (for example: https://adamkarvonen.github.io/machine_learning/2024/01/03/c... ).

Instead you have retreated to qualia like "well" and "sucks hard".

> hallucinating

Literally every human memory. They may seem tangible to you, but they're all in your head. The result of neurons behaving in ways which have directly inspired ML algorithms for nearly a century.

Further, history is rife with examples of humans learning from books and other written words. And also of humans thinking themselves special and unique in ways we are not.

> When using Claude Code or codex to write Swift code, I need to be very careful to provide all the APIs that are relevant in context (or let it web search), or garbage will be the result.

Yep. And humans often need to reference the documentation to get details right as well.
by steveBK123 | 2025-10-18 14:29:13+00:00
Agreed, the problem is that in many scenarios where the US becomes a failed state.. you probably want to be IN the US rather than living under our security umbrella (Canada/Europe/Japan/Korea/Taiwan/Australia). Or worse, in a nation we might end up in a shooting war with (Russia/China).

Either enemies are going to make moves in our absence, or we are going to pray upon former allies (next orange man takes his trade wars kinetic).

So I'd rather still be in the exponentially larger (population & land) isolated continental power surrounded mostly by water and smaller states.
by eszed | 2025-10-18 14:29:25+00:00
"Abstruse knotting techniques" would probably be more a more accurate phrase. I've listened in on two surgeons discuss at great length and in detail the merits of which knot and access path to use for, say, tying off a vein one-handed, by feel, when it's located somewhere behind another organ. The decision is complicated, so far as I was able to understand the conversation, by the patient's current blood volume and rate of loss.
by anon291 | 2025-10-18 14:30:18+00:00
We are already at agi yet no one seems to have noticed. Given its limited sense perception that makes chatgpt et al limited to talking with a partially blind, partially dead, quadraplegic, it has demonstrated and continues to demonstrate above average intelligence. Not sure what more needs to happen.

Sure we don't have embodied AI. Maybe it's not reflective enough. Maybe you find it jarring. Literally none of those things matter
by ufmace | 2025-10-18 14:30:23+00:00
I mostly agree, though I actually wonder if the energy difference is as big as you say. Yeah the big LLM company datacenters consume tremendous amounts of power, but that's mostly for either training or serving ~millions of requests at once. I wonder what the actual net power consumption is for a single machine doing about as much work as a single ordinary person could do with just enough hardware to run the necessary models. Or what the average amount of energy for a single set of interactions is at one of the big shared datacenters - they reportedly have a lot of optimizations to fit more requests on the same hardware. I think it might be only one order of magnitude greater than a human brain. Maybe actually pretty close to equal if you compare total energy used against work being done, since the human brain needs to be kept alive all the time, but can only effectively do work for a limited part of the day.
by childintime | 2025-10-18 14:30:55+00:00
Now, why would you have to make this point, as it's close to a tautology? It's likely because we have a lever and don't use it. In that framing your point gets lost, because it doesn't address any issue. So there is a superfluousness at play that suggests this is disinformation, intended to derail the impetus for change. So I guess you need to elaborate and present a synthesis, perhaps mention alternate levers, instead of downplaying the one that's obvious? I don't see any other significant levers, RethinkX says PV + battery are sufficient for virtually anywhere in the world. Grid demands should lessen over time as local generation comes online. The grid becomes a overnight backup charging method.
by khuey | 2025-10-18 14:31:27+00:00
More applicable to the average American traveler's life than whether they can visit 180 or 181 countries without a visa is the rise of electronic travel authorization requirements from other countries. The UK imposed one earlier this year and the EU is set to do the same next year (though ETIAS seems perpetually delayed). While everyone involved (except Australia) insists that electronic travel authorizations are not visas they are for all practical purposes.
by fuzzfactor | 2025-10-18 14:32:28+00:00
Not just anyone, people will "naturally" draw the line somewhere, and it will be in a number of different places for different people.

As the article emphasizes, "every technological advance seems to make it harder to work, remember, think and function independently …"

This is exactly what it takes for there to be a positive feedback mechanism for AI to accelerate. Almost like people havng the goal lines moved for them. Which it looks like AI has already done in spite of its notorious shortcomings.

That little quote doesn't only apply to AI, think about how it was as slide rule engineering faded into obscurity. Don't ask me how I know, that would be an even worse wall of text ;)

At one time all bridges, vehicles, aircraft and things like that were designed by people who had prevailed because their mindset was aligned with all the others who excelled at doing almost all the math necessary using only that one common tool, which was common among them because it was a best practice across so many cultures, and a leap above what they were using before. It wan't easy and it required a certain mindset which made engineering possible with such a primitive tool. Two pieces of wood.

The future's come a long way and nobody does this any more, so for the longest there's been no need for engineers to even learn how to use a slide rule, or especially not to use it professionally. Things actually did get easier. Slide rules were no longer necessary for engineering, and from that point the type of brain that could do those kinds of projects using only a slide rule has no longer been a requirement for who can become an engineer. This didn't make them stupid, engineering is still hard, naturally in many other ways.

But with that mindset that made it possible to accomplish so much with such primitive tools now largely absent, could that be why not much more is being accomplished with incredibly more advanced tools after so many decades?
by noahjk | 2025-10-18 14:33:34+00:00
> I'm happy to blog and otherwise share your site with folks in my little part of the world

To clarify, do you have a blog that you've managed to share with your local community? Or are these two separate statements?

I ask because I've been lately interested in the idea of a "community" site - a 'hub' for locals - so if that's what you do, I'd love to hear more!
by fourside | 2025-10-18 14:33:36+00:00
> Movie, TV and Music production companies, as well as book publishers… were severely limiting free speech according to their own policies

We’ve been casually throwing around the phrase “free speech” so much that it seems to have lost its meaning. Free speech was never about guaranteeing anyone and everyone a platform and an audience. At least within the context of US law, it’s about expressing ideas without government persecution, with some limits.

It’s an important distinction because now it seems some people are less concerned about the government protecting these rights and more about making sure they can still host videos on Youtube.
by cess11 | 2025-10-18 14:33:37+00:00
I don't know, all of those are pretty similar to me.

I'd like to be able to develop in other languages the way I do when I dabble in Pharo, i.e. mostly windows and widgets and dialogs that abstract away boilerplate, file and directory management, and allows me to relatively easily extend the environment when I feel like it.

Instead I tend to complement the editor or IDE with a rather large set of Linux and Unix programs in terminal emulators. It's not nice or easy to teach, but nicer than trying to figure out whatever module protocol used by the editor. Perhaps I could have stayed with Emacs and been content, but when I arrived at this methodology Emacs was still single threaded and quite sluggish in comparison.

I'm hoping Glamorous Toolkit might be the thing that eventually grows into what I'd like to have.
by imtringued | 2025-10-18 14:33:38+00:00
I'm not sure it's true that symbolic AI is dead, but I think Gary Marcus style symbolic AI is. His "next decade in AI" paper doesn't even mention symbolic regression. For those who don't know, linear regression tries to find a linear fit against a dataset. Quadratic regression a quadratic fit. And so on. Symbolic regression tries to find a symbolic expression that gives you an accurate data fit.

Symbolic regression has an extremely obvious advantage over neural networks, which is that it learns parameters and architecture simultaneously. Having the correct architecture means that the generalization power is greater and that the cost of evaluation due to redundant parameters is lower. The crippling downside is that the search space is so vast that it is only applicable to toy problems.

But Gary Marcus is in favour of hybrid architectures, so what would that look like? In the SymbolNet paper, they have essentially decided to keep the overall neural network architecture, but replaced the activation functions with functions that take multiple inputs aka symbols. The network can then be pruned down into a symbolic expression.

That in itself is actually a pretty damning blow to Gary Marcus, because now you have most of the benefits of symbolic AI with only a tiny vestige of investment into it.

What this tells us is that fixed activation functions with a single input appear to be a no go, but nobody ever said that biological neurons implement sigmoid, relu, etc in the first place. It's possible that the spike encoding already acts as a mini symbolic regressor and gives each neuron its own activation function equivalent.

The "Neuronal arithmetic" paper has shown that biological neurons can not only calculate sums (ANNs can do this), but also multiply their inputs, which is something the activation functions in artificial neural networks cannot do. LLMs use gating in their MLPs and attention to explicitly model multiplication.

There is also the fact that biological neurons form loops. The memory cells in LSTMs perform a similar function, but in the brain there can be memory cells everywhere whereas in a fixed architecture like LSTMs they are only where the designer put them.

It seems as if the problem with neural networks is that they're too static and inflexible and contain too much influence from human designers.