skysight-inc/HackerNews huggingface dataset:
In both modes it creates a ~/Grayjay directory, even when launching from ~/tmp/grayjay/Grayjay.Desktop-linux-x64-v2/ so ~/Grayjay was inevitable. In portable mode it makes the directory and does nothing with it. In non-portable mode it dumps a ton of data into the directory. I didn't pay attention to what the data actually was. So yes you're probably right.

But either way, Portable mode isn't behaving portably because it's touching directories outside of the current directory, and non-portable mode is putting data in ~/Grayjay instead of ~/.config/Grayjay so it doesn't do what I want it to do in any mode.

I'm quite happy actually that while this is a HUGE annoyance... It's also only an annoyance, and VERY simple to fix (as long as they do). Which means that this app is likely going to wind up as a daily driver for me once a few things get ironed out. I see the concept and structure of the app, and I like it.
I was typing the same thing when I saw this comment.

I am not at all shocked squirrels are vicious killers.
AGI will commoditize the skills of the owning class. To some extent it will also commoditize entire classes of productive capital that previously required well-run corporations to operate. Solve for the equilibrium.
> of people who refuse to use AI and who refuse to do business with those who use AI.

Do people refuse to buy from stores which gets goods manufactured by slave labour?

Most people dont care, if AI business are offering goods/services at a lower costs , people will vote with their wallets not principle.
Horses never recovered from mechanization.
I fed all the comments from "OpenAI O3 breakthrough" HT post to o1 pro mode
Below is a shortened summary (under 4000 characters) capturing the key points from the Hacker News thread:

What is ARC-AGI?

A puzzle-based benchmark (“easy for humans, hard for AI”) using visual/grid tasks akin to Raven’s Matrices.
Proposed by François Chollet et al. to measure genuine generalization, not just memorization.
Consists of public, semi-private, and private (hidden) test sets.
Historically, large language models (LLMs) struggled on it, cited as evidence they lacked “true” reasoning.
What did “o3” accomplish?

OpenAI’s “o3” scored 87.5–91.5% on the ARC-AGI public/semi-private sets, surpassing the ~85% threshold for the ARC prize.
Human benchmarks range ~64–76% for average Turkers, >95% for STEM grads.
Two modes:
“o3-low”: Cheaper (~$17–$20 per puzzle), achieves ~75–82% accuracy.
“o3-high”: 172× more compute, ~$1k–$3k+ per puzzle, scoring 87–91.5%.
OpenAI may have spent hundreds of thousands of dollars on 400 test puzzles in high-compute mode.
Reactions

Impressive but expensive: Thousands of dollars per puzzle is cost-prohibitive (human solvers might cost $5/puzzle).
Not “AGI”: Even ARC’s creators say passing ARC doesn’t prove AGI; Chollet notes “o3” fails some trivial puzzles. A new “ARC-AGI-2” could slash its score to ~30%.
Likely uses massive search at inference: Possibly a “tree-of-thought” approach (many sub-reasoning steps, a verifier, then a final answer), similar to AlphaZero’s search.
Other benchmarks: “o3” jumped from ~48% to 70+% on SWE-Bench (code-fixing) and from single-digit to ~25% on Frontier Math (Olympiad-level problems).
Employment & Future

Fears of rapid AI displacement of programmers and knowledge workers. Others see a parallel to the personal computer revolution, with humans still in the loop.
Real-world tasks need maintainable solutions and large contexts, not just puzzle-solving.
Current compute costs (~$1k–$3k per puzzle) are impractical. However, costs have declined steadily, suggesting future viability.
Goalpost-Shifting

Benchmarks lose perceived importance once models exceed them (as with Chess and Go).
ARC authors never claimed it was a definitive AGI test—just a measure of “generalization.”
Inference-time vs. Training-time

Models used to rely on big training sets + single forward passes; now we see iterative chain-of-thought plus large-scale search at inference.
Costs could decrease with more efficient “internal” search methods or session-based learning that amortizes expense.
Main Takeaways

OpenAI’s “o3” demonstrates near-human (or higher) performance on ARC-AGI by combining an LLM with a heavy search strategy.
This approach is incredibly costly but shows that, if you throw enough compute and methodical search at puzzles, LLMs can outperform average humans.
Passing ARC doesn’t confirm AGI; “o3” still struggles on some simple puzzles, and a new version of the benchmark aims to challenge it further.
Long term, decreasing costs and continuing progress could enable practical AI-driven automation in coding, advanced math, research, and more.
For now, I'd settle for an RT-safe way to create a new process that then calls execve. AFAIK, this doesn't for Linux and may not exist for any *nix kernel at this time (not sure about this second part).
Well, 5% said "Something else," so the most charitable reading already puts us at 65% being able to afford it.

But the way the question is worded leaves a lot of fuzzy room around the edges.

For instance, a financially illiterate person may elect to put it on credit despite having enough liquid wealth not to need to (to get the airline points perhaps?)

A shrewd investor may be able to cover it with a personal loan or by borrowing from family with a favorable rate that is lower than the expected return on their investments.

The question asks which best describes what you would do in an emergency and only invokes $1000 as an arbitrary example. Some respondents may simply be confused or pedantic in their response.

Additional bias can be injected when this number is re-reported by third parties, I've seen it reported as "X% of Americans..."

"...Don't have $1000"

"...Can't afford $1000 expense"

"...Don't have $1000 in savings"

"...Couldn't come up with $1000 in an emergency"

And several other hyperbolic variations.
Show HN: QRanalytica – Dynamic QR Codes with Real-Time Analytics
I’m Nookesh and QRanalytica is a tool that I created for an issue that I experienced while conducting marketing campaigns for local businesses. The problem that I had was tracking a QR code engagement on a real-time basis while at the same time updating the destination without changing the printed material over and over again.

I invite you to visit https://qranalytica.com to learn more and hopefully get your customers to try it out.
That book was not very good science or science interpretation and didn’t do a great job of proving that meaningful race-iq differences exist. I also don’t know where the disaster is, could you elucidate some of the cataclysmic results of DEI?
Meanwhile I can't even find this reported in any major newspaper. If MSF was making this statement about Syria or something I would think it would be newsworthy. So a fringe is protesting (in some places at high personal cost) while most of society shrugs their collective shoulder even though this is not Darfur or Rwanda and involves one of the US's biggest allies.
As I said, it's mandatory in RVA23 profile. In fact it has been mandatory since RVA22 profile. A bunch of cores appear to support RVA22.

Whether prebuilt distribution binaries support it or not, I can't tell. Simple glance at Debian and Fedora wiki pages doesn't reveal what profile they target, and I CBA to boot an image in qemu to check. In the worst case they target only GC so they won't have Zba. Source distributions like Gentoo would not have a problem.

In any case, talking about the current level of extension support is moving the goalposts. You countered "there is nothing about the RISC-V architecture which inherently prevents it from ever being competitive with ARM" with "Lack of reg+shifted reg addressing mode", which is an argument about ISA, not implementation.
A bakery still using Commodore 64s originally released in 1982 as cash registers
Norton Guides, iirc. E.g. Ralf Brown Interrupt List was available in it. Reading the docs without leaving an editor made programming much easier.
I don't know that "legally" has much to do in here. The bars to "open an account", "move money around", "hire and fire people", "create and participate in contracts" go from stupid minimal to pretty low.

"Legally" will have to mop up now and then, but for now the basics are already in place.
These models are nearing 2+ trillion parameters. At 4 bits each, we're talking about somewhere around 1tb of RAM.

The problem is that RAM stopped scaling a long time ago now. We're down to the size where a single capacitor's charge is held by a mere 40,000 or so electrons and all we've been doing is making skinnier, longer cells of that size because we can't find reliable ways to boost even weaker signals, but this is a dead end because as the math shows, if the volume is consistent and you are reducing X and Y dimensions, that Z dimension starts to get crazy big really fast. The chemistry issues of burning a hole a little at a time while keeping wall thickness somewhat similar all the way down is a very hard problem.

Another problem is that Moore's law hit a wall when Dennard Scaling failed. When you look at SRAM (it's generally the smallest and most reliable stuff we can make), you see that most recent shrinks can hardly be called shrinks.

Unless we do something very different like compute in storage or have some radical breakthrough in a new technology, I don't know that we will ever get a 2T parameter model inside a phone (I'd love for someone in 10 years to show up and say how wrong I was).
Calling the sentence or two it arbitrarily saves when you statd your preferences and profile info "memories" is a stretch.

True equivalent to human memories would require something like a multimodal trillion token context window.

RAG is just not going to cut it, and if anything will exacerbated problems with hallucinations.
Yes. People seem to forget that at the end of the day AGI will be software running on concrete hardware, and all of that requires a great deal of capital. The only hope is if AGI requires so little hardware that we can all have one in our pocket. I find this a very hopeful future because it means each of us might get a local, private, highly competent advocate to fight for us in various complex fields. A personal angel, as it were.
I'm glad I'm a grumpy self-host guy who still rips CD's and DVD's and plays my .m3u playlists with Winamp 2.95, and streams movies with Jellyfin.

It's glorious, being a digital prepper.
You're actually positioned to have an amazing career.

Everyone needs to know how to either build or sell to be successful. In a world where the ability to the former is rapidly being commoditised, you will still need to sell. And human relationships matter more than ever.
Where’s Ace Ventura?

Allllriiiighhittty then..
LLMs are mostly hype. They're not going to change things that much.
What's your opinion on the veracity of this benchmark - given o3 was fine-tuned and others were not? Can you give more details on how much data was used to fine-tune o3? It's hard to put this into perspective given this confounder.
The thing I wonder about is why we would do this. The technology to really convert industrial-grade apps from C to Rust could probably bullet proof the C apps more easily. They’d just have to do some analyses that fed into existing tooling, like static analyzers and test generators.

Similarly, it they might generate safe wrappers that let teams write new code in Rust side by side with the field-proven C. New code has the full benefits, old code is proven safe, and the interfaces are safer.

A full on translator might be an ideal option. We’d want one language for the codebase in the future. Push-button safety with low, false positives for existing C and C++ is still the greatest need, though. Maybe auto-correcting bad structure right in the C, too, like Google’s compiler tool and ForAllSecure’s Mayhem do.
> I have greybeard coworkers that dissed the technology as a fad 3 years ago. Now they are scrambling to catch up. They have to do this while sustaining a family with pets and kids and mortgages and full time senior jobs.

I want to criticize Art’s comment on the grounds of ageism or something along the lines of “any amount life outside of programming is wasted”, but regardless of Art’s intention there is important wisdom here. Use your free time wisely when you don’t have much responsibilities. It is a superpower.

As for whether to spend it on AI, eh, that’s up to you to decide.
Aalto University to launch historic archive of Nokia's design evolution
It didn’t need to be performant. I was in between jobs for 3 weeks and I reviewing C#/EF Core. I hadn’t programmed in C# in over four years
Zb extension is in both RVA22 and RVA23 profiles, meaning application cores (targeting consumer devices like smartphones) designed in the past few years almost certainly have shXadd instructions in order to be compatible with the mainstream software ecosystem
Came here to say this. I remember these surveys in high school and how non-seriously we took them. Really, I can’t imagine any group less credible to survey than high schoolers.
What Types of Issues Do Devs Handle on On-Call? Would Workflow Automation Work?
I’m looking for insights on the types of tickets devs typically handle during on-call shifts and how much of the work could be automated.

At Amazon, I noticed that many on-call tickets were "no-code" solutions—tasks that involved clicking through buttons or toggling settings, which could likely be automated with the right workflows. The full-time devs mentioned this was common for recurring issues.

Here are my main questions:

What kind of tickets do you typically handle during on-call? Are they mostly monitoring, troubleshooting, or tasks that could be automated?

How often do you get paged for on-call work? At Amazon, it seemed like you got paged every time you were on call. Is that the norm, or do other teams have fewer pages due to more automation?

Would a tool that automates some on-call tasks be useful? I’m thinking of building software that lets devs create workflows to automate recurring issues. AI would classify the issue, interact with customers, and deploy a solution. If it can’t resolve the issue, it would page the dev with recommendations. Do you think this could help reduce the on-call workload?
Thats right. We use the browser color picker.
[0] in the parent comment needs to note most of the increase comes from older people living and staying in their houses longer rather than dying, moving to facilities or in with family.
In most non-competitive coding benchmarks (aider, live bench, swe-bench), o1 ranks worse than Sonnet (so the benchmarks aren't saying anything different) or at least did, the new checkpoint 2 days ago finally pushed o1 over sonnet on livebench.
Imagine the Sun as a ball 1 mile in diameter. If you flew a probe by the Sun that never got closer than 4 miles away (4 diameters) would you describe it as "into the Sun?"

Neither would I.

Sure, it's close enough to get very hot. But it's not into the sun.
Yeah one of my younger brothers falls into this category, his Snapchat streaks have been going for years - from middle school to mid-university so far, and that's not an exaggeration.
If I were really trying to do a good job of it, I’d try to come up with the way to mix the waste into a hard brick too large and heavy for one person to carry, but cart-able for two or three. Perhaps i’d even use a mold to make it look deliberately manufactured to discourage breaking it apart. This way, hopefully, the waste wouldn’t be scattered in small pieces before the community realized what was happening. Hopefully, then, whatever party came into possession of the brick would #1 very visibly possess it and #2 very quickly show signs of illness. Alongside all the other safety measures, I’d hope this would very quickly tell the community that obtained it how dangerous it was while minimizing the scope of harm it ended up causing. I don’t personally see how anything better can be achieved here if we’re assuming this culture has lost all traces of nuclear physics and can’t understand any languages we have, and disregards any pictographic warnings we put on it.
> More of gen z are home owners than previous generations at that age[0]

If you’re going to make a claim this bold and this counter to the prevailing narrative, you’re gonna need to cite a better source than an outbrain-riddled webpage that tells me to “watch our video to find the lede we buried”. I’m not saying this isn’t true, but extraordinary claims require good sourcing and explanation.
I tried that some time ago and found I prefer working with one model (chatgpt back then) with its interface and settings. But you are right a good reason to additionally switch to the ultimate plan would be more support for Kagi which I love. It would still be 2 subscriptions since my chatgpt is pay as you go on the ancient model via api.
From 2020-2024, the UN recorded ~17,000 deaths among children in all measured countries combined. The share of that that is among older children/teens and in developed countries like the US is vanishingly small.
Yes, but it’s design and memorialization to her are deeply intertwined with religious significance: http://counterlightsrantsandblather1.blogspot.com/2013/12/th... (“According to Muslim tradition on the Indian subcontinent, women who died in childbirth are regarded as saints. Shah Jahan had all the more reason to revere his beloved wife as a saint when she died giving birth to their fourteenth child. The design of the Taj Mahal reflects the legacy Shah Jahan wished to create for his deceased wife, not only as deceased royalty, but as a saint. Our experience of the Taj and its gardens is not only about grief for a beloved wife, but a foretaste of the paradise that awaits the righteous and a premonition of the final Day of Reckoning as it is described in the Quran.”)

It was built by people who feared God and wanted to build something lovely in his sight.
That’s not inability to reason though, that’s having a social context.

Humans also don’t tend to operate in a rigorously logical mode and understand that math word problems are an exception where the language may be adversarial: they’re trained for that special context in school. If you tell the LLM that social context, eg that language may be deceptive, their “mistakes” disappear.

What you’re actually measuring is the LLM defaults to assuming you misspoke trying to include relevant information rather than that you were trying to trick it — which is the social context you’d expect when trained on general chat interactions.

Establishing context in psychology is hard.
This looks really cool! Do you have any plans for an Apple Music integration for those who use that over Spotify?
Amazon sellers are in revolt over a new policy they say gives up business data
Darwin has a posix_spawn() syscall. I'm not sure if it's RT-safe, but it is actually a syscall - it's not a wrapper for vfork+execve like it is on Linux.
I think you make a mistake when you look at physics with your modern eyes. Knowledge should make you see more, but this is the case when it makes it hard to see the history. Try to look at it with eyes of 19 centuries physicist.

Physics was all deterministic and objective. And then comes QM saying that there is no determinism and about the role of an observer, and comes GR saying there is no objective observer, because different observers can't agree about time and length.

I heard that physics professors in 19 century told their students that they had chosen the wrong career because physics was almost done. There were slight difficulties with electromagnetism, but they surely is going to be resolved in coming years. And then all that shiny and almost complete physics was blown up because very foundations of it were destroyed.

It was a paradigm shift. If it wasn't then what is? Copernicus? But the Ptolemaic astronomy did work and it works today. With its limitations of course, but it works. You can calculate positions of heavenly bodies with epicycles. Galilean laws of motions? But the laws of Aristotle works no worse then when Aristotle invented them.
Don’t worry. This thing only knows how to answer well structured technical questions.

99% of engineering is distilling through bullshit and nonsense requirements. Whether that is appealing to you is a different story, but ChatGPT will happily design things with dumb constraints that would get you fired if you took them at face value as an engineer.

ChatGPT answering technical challenges is to engineering as a nailgun is to carpentry.
o3-mini (high) uses 1/3rd of the compute of o1, and performs about 200 Elo higher than o1 on Codeforces.

o1 is the best code generation model according to Livebench.

So how is this not a breakthrough? It's a genuine movement of the frontier.
Our remedies proposal in DOJ's search distribution case
Self-driving cars are public transit depending on the terms of use; but I assume we're really talking about mass transit here.

When I was in Germany 25 years ago, a district of about 25k people (less than 1k per square mile) had multiple bus routes (4 IIRC) connecting the main town to other settlements, running through farmland. It was not unduly expensive and the locals certainly seemed to think it made sense. Children would take it to school in lieu of a dedicated school-owned service.

There's a light rail system in Rennes, France (city population about 225k; metro about 750k - https://en.wikipedia.org/wiki/Rennes) that's longer than the PATH system in the NYC area and almost as well used (https://en.wikipedia.org/wiki/List_of_metro_systems).

Even Iceland has public buses, both local and inter-city (https://www.straeto.is/en).
How do I tell it to not show me any short clips with all caps font on them like it’s a news headline?
Insurance isn’t about maximising overall outcome (we know it doesn’t do that!) It’s about managing critical (often existential) risks. You buy insurance when you need to protect against an unrecoverable loss (house burned down, car was stolen, permanently injured and unable to work, etc.) that you can’t just “ride out” and self-finance.
https://free60.org/ probably has all the information you need.
That’s ridiculous. Literally everything can be controlled by a computer by telling people what to do with emails, voice calls, etc.

Yet GPT doesn’t even get past step 1 of doing something unprompted in the first place. I’ll become worried when it does something as simple as deciding to start a small business and actually does the work.
Not zero. Even a full Faraday cage only has 90dB or so of attenuation. But measuring it would be darn hard, since the attenuated signal would be swamped by diffraction, skyscatter and reflection by nearby objects of the stronger side lobes.
Based on the questionnaire for the SCF on the fed's website, it looks like the figure is per person, not per account. Therefore the "rich people have multiple accounts that skew the results" effect won't exist.
Yeah, that’s true unfortunately, but it would also give people a very quick answer if they asked why x person was growing sick: because they brought the curse upon themselves etc. My hope would be that very few people would have to “demonstrate” the curse’s veracity before the culture tossed it back where they found it. It would especially help if the pictures depicted how to deal with the waste once it was realized, eg show some people putting all the material back into the crate then burying it deep in the ground, or in its original location.
Got a source for this? Because it’s brilliant.
A non-issue that can be trivially solved with a free-tier (like the dozens that exist already today) or if you really want, a government-funded starter program is enough to solve that.
As I said, o3 demonstrated field medal level research capacity in the frontier math tests. But I’m sure that your use cases are much more difficult than that, obviously.