Recently Plex increased the cost of a new Lifetime Plex Pass to $750 [1]. It seems like they really want to get most users paying recurring monthly or annual fees. But to me at least that kind of goes against the whole purpose of hosting my own media library.
Thank you to everyone who has contributed to Jellyfin for offering an alternative!
[1] https://www.plex.tv/blog/new-lifetime-plex-pass-pricing/
The (quite excellent) article discusses several of your points. If you haven't read it, I recommend it.
- Commodity market profitability is determined by marginal cost of production. LLMs have marginal cost; traditional software does not.
- Models are not free. Downloading them is free. Running them is not. This has manufacturing economics, not software economics; the idea that they are "free" is an economic category error as it relates to their actual use
- The highest tier Chinese models are not more economical than US frontier models. Try GLM 5.2 and see how much it costs to do real work. I did, and it was more expensive than GPT 5.6.
- This is because US labs are leading on cost efficacy of inference ($/task)
- Training will decline as a percentage of costs as inference expands compute share due to agentic workloads. A big part of training now is optimizing token efficiency. It's hard to distill token efficiency; that is perhaps why Chinese LLMs are so inefficient.
- With increasing inference as % of total compute, if labs create efficient models -- which they can, because they can create highly optimized models amortized over very high inference loads -- they can be low cost producers, and be competitive at $/task rates
The people who are most afraid of Chinese models are the VCs who poured into Anthropic and OpenAI at astronomically high valuations. Anthropic is valued at $1.2T and OpenAI is targeting $850B. These astronomical valuations were built on the premise that these labs would generate massive profits from premium API pricing, but the Chinese labs are completely undercutting this strategy by releasing excellent open models for free. If the frontier labs are forced to cut prices and join the race to the bottom in token prices, these valuations are unjustified, and VCs will face enormous (paper) losses.
When I was in grad school, I had the opportunity to take a course from my adviser in which he discussed his current research and some open questions. It was a relatively accessible subject area and the questions were sometimes easy enough that we could meaningfully contribute.
On one particular Friday afternoon, he stated a conjecture that he hoped was true, and invited us to try to help him prove or disprove it. It was the sort of thing that he really wanted to be true; he liked things smooth and beautiful. I, on the other hand, hoped it was false as I like the weird and exceptional in mathematics. It was also the case that I had absolutely no command of the sort of machinery that one would use to prove such a thing, but I could certainly look for a counterexample.
I learned on Monday that he had spent the entire weekend trying and failing to prove it. I, on the other hand, had put all my energy into finding a counterexample and had one within an hour.
My single (quite small) contribution to mathematical research was a counterexample because it was all I could do. The story does illustrate that it can be helpful to have people with different tools, hopes, and motivations working on a problem, though. I was not, and will never be, even a shadow of that great mathematiciam I studied under, but on that occasion, I had reason to look in a different direction than he did.
Saw the window was a bit laggy so thought I'd delve deeper to figure out what was going on.
This lib runs a a RAF animation loop every 8ms across every component on the page that causes the entire document to repaint.
The comment above appears of the AI generated sort: // One shared animation frame: step every live component, park when idle. // The delta is capped so a background-tab pause never becomes one giant step.
The "JellyEngine" instead of just calculating the jelly animation on pointer events is recalculating for every active component on the page every frame.
This is the kind of thing usually a human notices and says 'dont do that, that is kind of crazy'.
Try instructing Codex to (say) fine-tune a language model based on a collection of books you've got saved. You will find yourself admonished, repeatedly and at length, not to utilize copyrighted materials to train language models, by an AI who owes its entire existence to that very act.
These models might be smart but they're not close to being able to savor irony.
What's interesting/funny is that the American LLM companies took from the public domain and copyrighted work to close all that content into a box they charge for.
Then the Chinese took the distilled stuff out from that box and released it into the world for everyone.
The lesson of the last 50 years of the computer and software marketplace is that free and low-end eventually wins.
- PCs destroyed minicomputers. Mainframes survive, but serving a much tinier portion of the market than they used to.
- PC office productivity software destroyed expensive professional products.
- Windows (low end) and Linux (free) completely destroyed the UNIX marketplace, and again, have taken huge market share from the mainframe world.
Ignoring the huge Chinese open-weight models for a moment:
- The training costs and resource requirements for frontier models are unsustainable. The high price, and social pushback, mean that the American companies producing these models are precarious.
- There are enormous financial incentives for research results allowing for cheaper, less resource-intensive models of high quality.
- Local LLMs on consumer hardware are akin to the PC hobbyist world of the 70s and 80s.
Put all of these trends together, and I think that in 10-15 years, we are going to have consumer PCs (and phones!) running models doing pretty much anything that frontier models can do right now.
Getting back to the Chinese models: They allow for new competition against Anthropic and OpenAI, basically SaaS renting out these very capable AIs much cheaper. That will just accelerate trends.
This happened in a 50k people town where my father is from in 1982 with a BIG flood that destroyed the town land registry documents (among a lot of the town). Since he's a lawyer, had first hand experience and I was always curious I asked many things about this a while back. Basically, what happened is that they rebuilt it from proof of ownership and testimonies of the people. You can never get to 100% recovery like that, but everyone knows who their neighbor is, at least in a town that is small like this.
So they rebuilt it first from first hand proof, then by testimonies, with a period of counter claims available IIRC. For sure there were some false claims, but given the magnitude of the disaster, this is the best solution within that context.
I’m suspicious of some quotes here, “80% of startups using Chinese models,” doesn’t seem quite right to me. I just interviewed at several startups and they were all using the US models. Maybe they have some minor use of Chinese models but the bread-and-butter of most of these businesses model use is the Claude and Codex subscriptions.
> Since the hack, officials restored their website and posted a message announcing they are rebuilding the agency's entire network from scratch. Even if the hacker claims they deleted backups, the agency appears to have had an offline copy, otherwise things would have gotten really messy over the coming months in Romania.
So it seems not all has been lost. I was worried about the societal implications of being unable to prove land ownership but it seems that may be avoided.
There is no evidence that $500k has been paid or would be paid for an exploit like this one.
Given that the article says that prompts are modified like they are holy scripture, perhaps sell the prompt for $500k.
The author works for https://www.assetnote.io/ , which has AI products for automated scanning.
https://github.com/WordPress/WordPress/commit/3a640e1c5e39aa...
String concatenation SQL injection in the year 2026.
I'm not sure why some comments here are so pessimistic. I was grinning ear to ear while seeing the video. You're telling me we've finally got robots that can do our laundry? And the model is at least as free as beer?
To quote the lyrics/meme, we used to pray for times like this. This is what robotics should be used for.
I have been slopfolding since before it was cool
A little over 10 years ago I remember meeting a postdoc who believed he had something close to a counterexample to the Jacobian Conjecture. He and another person was bruteforcing polynomials in about 16 variables, something like 80 - 700 terms each, using binary trees for mapping coefficients.
They were guessing, at the time, that the lower bound of a counterexample (P, Q) for max(deg(P), deg(Q)) would go up to 200.
To think that Claude Fable was able to find a counterexample in degree 7 is insane to me. We are truly in a new era.
This is a rare instance where feeding this groundbreaking information into an LLM gives _them_ psychosis. I fed this to claude code and watched it verify the result in 7 different ways to be 100% certain, and it was just flabbergasted. Quite remarkable.
So, to sum up:
First there was Nvidia Gamestream, which was proprietary and later deprecated by Nvidia themselves.
Then came Sunshine and Moonlight, open source server and client implementations of the protocol to allow low latency streaming for all platforms.
Along the way the Game on Whales project started, to allow multi seat streaming plus virtual displays so currently logged in user sessions aren't impacted. Basically this is a whole "host your own Stadia/Geforce Now" solution. But instead of running already setup applications as an existing user, you run these curated containers of Steam, Firefox, etc.
Then someone forked Sunshine and Moonlight into Apollo and Artemis, to make streaming from a virtual display turnkey and OOTB easy. Sadly the virtual display feature of Apollo is in practice Windows only.
And then there's this, Moonshine, in a way doing what Apollo brings to the table but for Linux servers.
Oh, and along the way someone forked Apollo into Vibepollo, an almost fully vibecoded "enhancement". Personally not touching that.
Did I miss anything?
I’m a developer from China. So, is this what Hacker News is all about? Whenever a model comes from China, the comments section stops discussing its technical architecture, optimisation points or real-world performance, and instead starts going on about politics, human rights and all that rubbish? To be honest, we Chinese IT professionals possess a genuine geek spirit. That’s why you’re lagging behind in open-source competitions—it’s got nothing to do with politics; you’ve simply lost sight of your original aspirations.
This study is pretty bad. The comment (https://news.ycombinator.com/item?id=48970182) on the other link with the direct PDF explains the problem well, which is that nothing here being tested is specific to AI systems.
This study gave people access to an LLM that the researchers knew would give incorrect answers to certain questions, and then quizzed people on those questions, with the option to not respond to a given question if they are unsure about the answer.
This is akin to giving someone a textbook on an obscure subject that has certain factual errors, letting them know they can use that textbook in a quiz on that subject, and then quizzing that person on those facts that the textbook gets wrong.
Obviously that person is both more likely to be willing to respond to the question and is more likely to get it wrong!
There are a lot of things I'm very interested in that are specific to modern LLMs and how they affect learning and confidence (sycophancy, cognitive helplessness, etc.).
This study tested none of those. Its experimental setup is not very different than simply substituting the LLM with a textbook with errors.
Advice and information subreddits have gone to shit because of AI usage. A large number of people seem to think that when someone asks a question, what they really want is not someone with direct knowledge, but instead someone to relay the question to ChatGPT and post the result as if it is their own hard earned knowledge and insight. I have no idea about the quality of this research but in the real world (well, real-ish, as real as Reddit can be) it is stark, people aren’t just refusing to say “I don’t know” they’re actively seeking out opportunities to pretend they know things.
Thank you for posting this, it reaffirms what I've been thinking for so long. There are many opportunities to retrofit old systems of all types with modern low-cost embedded technologies.
Around 2019 or so I was approached by an engineer who had a small business retrofitting very old machine tools with modern motion controls. Think very large lathes and planers. The problem they had was that in order to get these systems working with newer controls, they had to make time-consuming modifications to the old machines, in some cases modifying the axis motors and that cost added up quickly. The engineer realized that it was theoretically possible to take the old analog position signals and convert them into something a modern motion controller could read. That converter box would make the retrofit pretty much plug & play, but he didn't have the programming expertise to make it happen.
We probably built the first iteration of the converter for under $50 in parts and less than 50 hours of development time. That had me searching for other similar opportunities. I have found a few, but they tend to be one-offs that aren't worth the time unless you're already building something similar. Either that or my ability to see opportunity sucks!
> Over the past 48 hours, demand has pushed close to the limits of our current capacity. To protect the experience of existing subscribers, we're temporarily pausing new subscriptions and prioritizing compute for current members. Existing subscribed users are not affected.
Such a beautiful paragraph to read, a company that prioritizes their current customers and focus on keeping them satisfied instead of just focusing on fast growth.
Lol, nice! It depends on what you mean by "owning a bowling center," but it looks like there are at least two of us into this :D
I bought a really old fully mechanical (and automated!) mini bowling lane. It works without a CPU, except for the score display, which originally used a 1970 Intel D8749H (MCS-48)!
Just like yours, the only thing that turns this machine on is a single relay :D On my model, I also get feedback on the pin status and a "ball received" signal, so I can trigger the scoring.
I dumped the firmware and replaced the display PCB with a more recent DIY PCB with an Arduino that speaks a modern, documented protocol. It's now compatible with ScoreMore software, and I can do a lot more with it.
Here are some pictures and more info on the Bowltech forum (you should post your stuff here too!):
* https://www.bowltech.com/forum/small-scale-bowling/small-sca...
@vik8 on discord if you need :)
Drilling into the original article where Jarred explained the reasoning behind the change, It's pretty clear that under zig the team was doing things by hand that are automatic in rust.
Humans and agents share one thing: they are both non-deterministic. He talks about the issue of tracking memory lifecycles manually in zig so it can be explicitly freed. As expected, this leads to a long list of bugs where people missed things.
Rust does this automatically. It removes an entire class of errors from his backlog. From an engineering management perspective, this looks like a pretty good trade.
The bonus here is that compiler errors are exactly the kind of deterministic guardrail you need to put around coding agents. Claude works really well if you give it a way to test for correctness and "make it compile" is a pretty good target.
There's a general version of this: the artifact you expose plus the test you run on it. Deterministic tests turn stochastic output into a hard guarantee. Wrote it up here if useful: https://michael.roth.rocks/blog/verification-surface/
Hardware has a reputation for being hard for three reasons. First, it scales differently than software. It's far harder to design something you want to make a million of than something you want to make ten of. Second, it's harder to anticipate, test, and correct all the things that can go wrong on the user end. Some people will put batteries the wrong way, some will drop the device on the ground, some will connect it to some vintage equipment you have never seen in your life, etc. And third, there are just more failure modes in an unfamiliar domain - sometimes, your code will intermittently crash not because you have a software bug, but because you put the decoupling capacitor too far from the chip. Or, just as you finish your design, the chip you designed it around becomes obsolete, or impossible to find because a factory in Indonesia is on fire.
Another complication is that at least in theory, if you're selling electronics, there are actual regulations and third-party testing that needs to happen, and if you fail emissions, you might have to redo your design from scratch. Imagine we had that for software - "your JS is too big, you can't ship until you get it under 50 kB".
So, I'm happy for the author, but I think he had an outlier experience. When you look at Kickstarter stories, people repeatedly stumble over this. Manufacturing / cost difficulties, supplier issues, reliability issues, etc.
>It largely works and it's a massive business success. This is the classic engineer asking the 'why this technology?' to what amounts to a business question.
Your counter argument would be valid for a 2000 or a 2020 business decision about some tech stack.
But the whole point of their product is that it supposedly nullifies such "business" concerns around the use of technology, by making it cheap and fast to build whatever you like automatically.
That they wont, or worse, couldn't, speaks against that.
> It's hard to say what their motivation is.
Feels pretty easy to me.
They want to turn LLMs into a commodity, and watch the US AI labs crash and burn.
There will still be plenty of customers who will pay them to host the models and run inference, even if the weights are open and others can offer competing products. (If necessary, the Chinese government can ban use of foreign inference services by Chinese citizens and businesses to give their own companies a domestic monopoly.)
When their models equal or surpass those from the Western AI labs, they can even stop releasing weights for new models, and keep all the inference revenue for themselves.
Meanwhile, they're still manufacturing much of the hardware that everyone in the world needs in order to run datacenters (see also: Spolsky's "commoditize your complement" essay).
Beyond that, it's a soft-power play. As the world keeps looking at the US more and more skeptically as an ally and superpower, Chinese companies releasing weights for competitive models is a way for China to look better and more world-minded.
It largely works and it's a massive business success. This is the classic engineer asking the 'why this technology?' to what amounts to a business question.
They chose it early on, it works, and it makes obscene amounts of revenue. End of story. That doesn't mean it was the "greatest" choice, or has a perfect technical architecture.
Rewrites are never easy, even the bun rewrite. But a non-UI developer tool with a rigid API surface contract (and associated tests) will always be easier to trust after a rewrite than a partially tested UI tool with ambiguous functionality.
Right now I'm working on adding LED + DMX DJ light control - I kinda want to be able to order LED strips to "chase" a ball as it goes down the lane or back up the return. I plan on triggering laser-light shows and such with the DMX controller.
Eventually, I want to allow a customer walk up to the lane, tap to pay and start bowling immediately, too. Kiosk-ize bowling alleys, yknow?
I'm pumped. So much room for activities!
Maybe I’m taking crazy pills, but I’m still stuck on “why the hell does a TUI need to run in terminal React by way of JavaScript”
The fact that Anthropic felt the need to buy a runtime so they could make their TUI better speaks more to the quality of engineering than anything else IMO.
If rewrites are so easy, why not rewrite CC in a native language? Would’ve been a hell of a lot cheaper.
- stop using ollama
- https://sleepingrobots.com/dreams/stop-using-ollama/
It’s made absolutely no negative difference, as we’ve seen in the real world in the last 60 days since the merge.
I feel weird having to defend reality; reality being that it was merged nearly 2 months ago and tons of people have had their pitchforks out without a shred of actual evidence that this made bun worse in any measurable way. But they still insist it was a mistake.
I’ve never met Jared or the bun team but I don’t understand all the personal attacks, I just feel the need to correct the facts. Literally who cares what language a JS toolset is written in?
It’s not like they ported JavaScriptCore (the actual JS runtime) to rust even. All that stuff is largely untouched.
Bah.
Personally my take on the entire affair is quite negative, whatever Jarred or Simonw says about it.
I think Bun owned by Anthropic and the entire rewrite with AI is not the real point (even if it's quite interesting, though).
My take is that Jarred, and Bun,didn't demonstrate a serious, adult approach, from "this is my branch, you are overreacting" message to just proceeding with a 1mil+ PR merged in less than month.
The communication is the issue, and it was handled very badly, in a way that impacted trust and divisions.
Was it so difficult to adopt the approach that the TS team adopted for 7.0?
It's hard to say what their motivation is. The Chinese firms seem to be working hard to commoditize intelligence which may be the most effective way to debase American frontier labs. And yeah: it also happens to be really good for humanity.
I assume that this announcement has been prompted by that of Moonshot AI, which has just announced a 2.8T parameter open-weights LLM, Kimi K3, to be published on Huggingface by 27 July.
Now the response of Alibaba is that they will also publish soon a big open weights LLM, the 2.4T parameter Qwen 3.8.
I wonder if Alibaba has always planned to make this big LLM open weights, or they have chosen to do this now, to better compete with Moonshot AI.
In any case, from this competition in LLMs, we win.
For a no hacks alternative, I built TV Explorer. It puts the channel's published HLS stream into your browser with no interim steps. Uses the public GitHub list of more than 10,000 free channels.
HN title is missing the operative word "secretly". The real title:
> Mayor Mamdani Says Landlords Can’t Secretly Use AI Images to Advertise Properties
The article contents align with the real title: you just disclose AI usage when advertising rentals.
This is awesome! StreetEasy is how many New Yorkers find apartments. In the past few years, it has been flooded with AI-staged apartments. The AI stagings warp the room to fit furniture that would 100% certainly not fit there. It’s deceptive, and I’m glad it at least requires disclosure now (although I wish it were fully banned)
I strongly agree with the premise that distillation is not an “attack”.
But that said: K3 is not a distilled version of Fable or Sol. Fable has been barely available and Sol was just released! Moreover, K3 is superior to both models in some domains, according to user scoring on the Arena.
API distillation can’t give you these results anyway. All it is useful for is bootstrapping RL in new domains to get past the “cold start” problem faster. By far, what matters more is the quality and variety of RL environments the model learns from.
Regardless of whether they achieved parity via distillation, or whether they got here via independently constructing a model from scratch, it was always going to end this way for the frontier American labs. Distillation “attacks” are not attacks. The frontier labs “distilled” all existing human written knowledge into their models, there was always going to be a second class lab that would distill that model into a cheaper version of it. There was never any plausible explanation for why this wouldn’t happen. There was never any practical mechanism to prevent someone from saving a conversation and using it to train their own model.
Even if it didn’t happen here, it was still the case that it was going to happen going forward. It was always going to end like this. Invest in the hardware companies, not the model companies.
// Lots of people have a sort of consumer attitude towards their communities, where they take everything for granted. I saw things this way when I was young. A social scene is an automatic feature of the world that appears on its own, like a wild blueberry bush. It starts sprouting parties and dinners and conferences and reading groups as naturally as the bush sprouts berries
True in general. As a kid you think of things as bigger than you. Like whoever maintains a hiking trail or runs your towns diner is "big" compared to you.
As a grown up you hopefully realize that it's the other way - the work and effort to make and maintain those things is vulnerable and fragile.
I think about this whenever I see someone hop over the subway turnstile. The transit system is "for granted" - it's you and your few bucks that matters. But of enough ppl feel that way it all goes away via decay eventually.
This post needs a bunch more context; right now it's only immediately accessible to people who don't need the announcement [1].
[1] https://knowyourmeme.com/memes/curtains-for-zoosha
If your country’s industrial and defense policy relies on individual consumers making choices that are worse for them on almost all metrics, it’s time to think about on worse payroll your politicians are.
GoPro is a US company designed in U.S. with manufacturing in Thailand, China, and Mexico.
Insta360 is a Chinese company designed in Shenzhen and built there, too.
People think this doesn’t matter, but GoPros are used all over in aerospace. If we replaced the brand with Insta360, that puts a big attack vector all over the place.
A similar pattern happened with drones with DJI, intentionally killing all non-Chinese drone brands. And with BambuLabs (founded by ex-DJI) with 3D printers (the only good non-Chinese printer that doesn’t cost 10-100x as much is Prusa, and they’re facing extremely strong headwinds).
Legitimately better Chinese products (incredible engineering) that have massive industrial policy support, probably industrial espionage support (as in the case of DJI for certain), massive influencer marketing campaigns, and near zero cost of capital. When China wants to deindustrialize non-Chinese industries for strategic and/or natsec reasons, they are incredibly good at it. (And note it’s not US-only, China targets basically ANY brand that isn’t Chinese. China absolutely does this to Europe as well… and you can see them doing it in real-time with automotive.)
The only surprising thing to me is how people just act like it’s not happening. I guess for people who don’t have any experience working on federal government adjacent aerospace stuff, the idea of natsec considerations for IT hardware seems entirely abstract, but it’s incredibly real if you do.
I know a bit about this field. This conjecture reads as somewhat more niche than the cyclic double cover conjecture recently proved by OpenAI, but nevertheless represents a real contribution.
You want to know how long it takes to solve an optimization problem, in this case over convex, lipschitz functions. (The restriction to a spherical domain is not really a restriction, you can just change variables for any bounded domain.) Anyway, showing upper bounds on time complexity is "easy" because it's just the runtime of your algorithm. Showing (nontrivial) lower bounds is usually much harder because it requires constraining all algorithms.
This proof apparently shows that the lower bound time complexity is equal to the time complexity of an existing 30-year old algorithm: it requires Omega(d^2) function evaluations to solve over this class of functions.
My gut says likely implies that d is the minimal number of evaluations if you have a gradient oracle because you can approximate a gradient with d function evaluations, but I'm not sure how hard it is to make that rigorous.
I’ve owned a lot of Gopro cameras, having done video capture for a variety of motorsports, and they just got too expensive for what you get.
You can be more expensive if you’re better, or you can be worse if you’re cheaper, but they’re both the downsides while living purely off brand recognition.
They also blew up in a time where there wasn’t any real competition. Sony had action cameras but they were bulkier and expensive, and didn’t have the features of GoPro.
These days other brands give better quality video in better quality hardware and more functionality, for cheaper.
>This situation has.. no precedent as far as I can tell..
Printer, mouse, tablet and display tablet makers use this to insert their crapware since at least Windows Vista or Windows 7, I think. The last one I remember is plugging a Razer mouse just to watch it instantly pulling 1.5GB of bloated junk with "telemetry" exfiltrating the data from my gaming PC in realtime. At least it doesn't leave my mouse in a non-working state when I disconnect the internet, like it used to. Thanks, Razer!
Microsoft is to blame here, really. They have a mechanism to block any vendor (supposedly to avoid reputational risks to their brand due to buggy drivers, at least that was their excuse back in the day), but aren't even using it to block these contraptions. Entire businesses are built on this, e.g. Razer is probably more of a marketing/data company now rather than a hardware shop.
That basic idea is what made SO attractive in the first place, compared to forums where you had to scroll through pages and pages of in-jokes and tangents and animated-GIF signatures just to try and see if there is an answer.
Where they went wrong, in my opinion, is in the implementation details.
It's mostly death by a thousand cuts: Requiring reputation to gain the ability to post comments, then having one's answers deleted as "this should've been a comment". Overeager marking of questions as duplicates, e.g. despite the equivalence between two situations being non-obvious (e.g. someone asks about data type A, and it turns out that it's a subtype of B for which an answer that applies to both exists; that should not be a duplicate, the fact that it's a subtype is the answer!). Endless other decisions like that, which wouldn't have taken any extra effort to implement correctly.
One feature they could've built that would have taken effort but also greatly helped against the common newbie complaint of "hostility" would've been a "newcomer track", which would've been more forum-like and guided them towards either formulating a good question or seeing that's it's already answered. In the latter case, some of the keywords that came up during this process should've been fed back into SEO so that future newbies would become more likely find the answer via a search engine despite using clumsy terms. I think they tried a simpler and worse version of this idea towards the end with "staging ground" but by then it was too late.
Any social organization needs to carefully consider their inclusion-exclusion curve with intentionality.
I think a lot of people might balk at the word "inclusivity" today, but StackExchange had ridiculously high barriers to participation, making it inclusive to the long-time users on the site, but exclusive to the newbie participants who found themselves blocked for asking questions. They slowly killed the site in this manner.
The community might have survived this folly, even with AI, because it was still the best place for people with qualms about AI to ask questions... Except until StackOverflow management alienated those users, too, by shoving AI down their throats in every facet of the site.
Even I had internalized the vagaries and neuroses of the SO community but I had heavy reticence to ask questions, knowing I'd have to consider all the ways a bully eager to use their powers might misunderstand me. I can't imagine asking a question there without having had lurked for longer than a typical Bachelor's + Masters program.
Peak at 207K, minimum at 588. That might be an incomplete date point, so using the next most recent value 1226, StackOverflow has lost 99.41% of its activity.
SO did that all to themselves when they decided they didn't want a community to form and that only question and answers mattered. The moment something else allowed to have a better way to get your answers, there was no reason to go there, because there was no community.
I still don't understand why anyone would go with that whole "no conversation please"
This is so much worse that the title makes it out to be:
1. Your OS installs malware (technically manufacturers software) from a 3rd party vendor in background, zero user interaction
2. Happens as soon as you or anyone with physical access plug in a device into the HDMI port
3. That malware has internet and full system access, no sandboxing
4. It starts with every system boot
5. This software gets installed when you plug in a new LG monitor
6. OR ALREADY HAD AN OLDER LG MONITOR PLUGGED IN, BECAUSE LG APPARENTLY ROLLED THIS OUT FOR MANY OLDER MODELS TOO!!
7. And yes, if you think that's horrendous, as mentioned in the video below, that also applies to 'Professional' LG monitors!
GamersNexus has a video diving deeper into what LG did here - https://www.youtube.com/watch?v=Q9uefFYe6bM
Workaround:
gpedit.msc
Computer Configuration > Administrative Templates > System > Device Installation
Prevent automatic download of applications associated with device metadata
Set to enabled
OK
sysdm.cpl
Hardware tab
Click Device Installation Settings
Under 'Do you want to automatically download manufacturers' apps for your devices?', select 'No'
Save ChangesThe idea that a state court in one particular state can enforce such an absurd law against a company that likely has no business operations or servers in the state is ridiculous. I don't care if you like the porn site in question or not, or condone or endorse its content. This is a slippery slope towards every regional tinpot dictator legislature attempting to censor the internet by having an entity's domain name revoked.
.com in particular has also been well proven over the past 5 to 10 years to be vulnerable to federal court orders to seize domains at the registrar level. That's not really anything new. It's a known risk for anyone building a corporate brand/identity around a specific .com domain name. What's new is this is being done from the state court level. (Edit: To be clear, in my opinion, a US State court completely lacks jurisdiction on this matter).
I RFTA and the majority of the complaints are about call center metrics and the pressure to ration care. These are real concerns about misuse of metrics, but not AI. The AI empathy thing was a 2024 pilot that was discontinued.
FWIW my wife works for Kaiser and finds a lot of value in the the medical LLM tools available to her. She tells me being able to do live translation, summarize notes, and quickly get comprehensive answers save her time and help her give better care. Her older patients also frequently come in bringing AI-powered alerts from their apple watches that detected cardiac events.
It's annoying that we use broad terms to describe a set of technologies that in some ways can be problematic and in another ways are very beneficial. We gotta evaluate each of these as they come rather than talk about blanket bans.
If you think using a machine to evaluate how well a human is showing empathy is a good idea, you probably shouldn't have any position of power.
No tests? Just mess up some mundane detail [1] and voila! Wake-up calls and heart attacks for 100,000s of administrators?
1: "Oh, well, this is not a mundane detail, Michael!" https://www.youtube.com/watch?v=3fGHaVn5rGo
Ive dealt with this error at AWS. It’s a unit error. In my case we _meant_ to charge like 5¢/GB, but missed the unit (GB), and then the billing system defaults to bytes. 5¢ per Byte of data transferred meant some customers were seeing MM bills within hours. Got paged by support around 2am, had it fixed and amendments issues by 3-4am, apology emails shortly after.
Services emit metering values that arent directly tied to prices. Every SKU/line item is defined in a “pricing plan”, with a unit type, regions, and price per unit. The metering records are joined to a pricing plan based on account id, region, sku, etc. mess up the unit type in the pricing plan and the metering data conversion doesnt work, and you get crazy bills.
It's incredible Simon still believes pelicans on bikes aren't part of the training set, despite hundreds of them on blogs, forums, and Github. Stuff we put in our company blog shows up known by LLMs 6 months later, and we have 1000x less traffic than Simon's own website
It's crazy enough this will be fixed soon.
Years ago I found an actual hidden error in my bill. (This was early 2010s). The system was calculating the EC2 reservation savings incorrectly for some of my servers. I was crunching all their detailed usage data on a regular basis in an 18 tab spreadsheet and couldn't get it to fully reconcile. I spent months trying to track down the discrepancy. Once I found it, I had to convince AWS their system was wrong, which took another big chunk of time. Meanwhile the discrepancy continued to accumulate.
After 14 months I got a $7,000 refund. I was told it had to be approved by the head of AWS. I've never seen a calculation error on their part since.
Wow:
In this role you will:
- Design and build agentic AI systems that analyze, generate, and validate...
- Build agentic architectures that compose specialized AI agents dynamically...
- Build AI-driven continuous validation frameworks powered by agentic workflows and large language models that autonomously manage...
Speculation: open models is what will kill Anthropic and OpenAI. Hyperscalers can run the models without a licensing fee. Apple can make them smaller and put them on the device.
The frontier models are an edge and a liability. They're astronomically expensive to train. Without them, their models will fade into obscurity. Their marketing depends on people believing the models are meaningfully different, as people have sweatily argued on this forum. Personally, I'm not convinced there's much of a difference between these models at this point. The harness is what takes these random and hallucinogenic models and make them into something deterministic and useful.
FT frames this as some aggressive escalation tactic, but document retention letters are extremely standard practice. At this point they're basically a formality, as any former Apple employee at OpenAI really ought to know by now that they could get dragged into this. Hold letters can be aggressive if you send them before you've even filed a complaint, but if anything, Apple is late to the party with these.
I think we need to address the underlying causes of people outsourcing their thinking like that. And a big contribution is “move fast.” No one has time to read, process, and think, because The Powers That Be (capital) want their results now.
AI is useful. But the amount of people that are simply offloading all of their thinking to AI and blindly accepting the answer is absurd. Kaggle is most likely using ai to assess the submissions and are not using any common sense by blindly accepting the results.
Woke up to a billing alarm email. Thought I had leaked my AWS keys accidentally and somehow run up 437 billion dollars of charges. Joke's on them though, I don't have 437 billion dollars
Anyways I didn't need coffee. That produced an adrenaline release unlike any I've experienced before. Thanks AWS
Ask for some leniency. Let your account rep know about your budget difficulties and ask if you can make good faith payments of a few billion per month until you get back on your feet.
I got 3 consecutive emails warning that my budget crossed its $18 threshold. Opened it up: cost was 78 million. Thought it was a phishing attempt, logged into my actual account, and... still 78 million. EMOTIONAL DAMAGE.
Related, but this reminds me of the story by Richard Feynman [1] when he practices counting up to 60 seconds in his head, and after many experiments around what he can do simultaneously conclude that he can simultaneously count and read but not speak. Later sharing this to John Tukey, he's told that Tukey can't read while counting but could speak while counting.
Turns out Tukey is visualizing looking at a tape, while he counts, while Feynman imagined himself talking to himself, so he couldn't speak while counting but Tukey couldn't read while counting
>By that experience Tukey and I discovered that what goes on in different people's heads. when they think they're doing the same thing - something as simple as counting - is different for different people. And we discovered that you can externally and objectively test how the brain works: you don't have to ask a person how he counts and rely on his ownobservations of him-self; instead, you observe what he can and can't do while he counts. The test is absolute. There's no way to beat it; no way to fake it.
>It's natural to explain an idea in terms of what you already have in your head. Concepts are piled on top of each other; this idea is taught in terms of that idea, and that idea is taught in terms of another idea, which comes from count- ing, which can be so different for different people!
>I often think about that, especially when I'm teaching some esoteric technique such as integrat- ing Bessel functions. When I see equations, I see the letters in colors-I don't know why. As I'm talking, I see vague pictures of Bessel func- tions from Jahnke and Emde's book, with light- tan j's, slightly violet-bluish n's, and dark brown x's flying around. And I wonder what the hell it must look like to the students.
[1] https://calteches.library.caltech.edu/3591/1/Feynman.pdf
Apparently what used to be `GB of storage consumed` is confused with `Bytes of storage consumed`, leading to a cool off by 2*30 error.
> You're right to question my calculation. The MCP server failed to connect when I tried to look up the field definition. I guessed instead of validating. This is on me. But look at all the revenue!
Yet if the average corporate person does insider trading it comes with a prison sentence not pricing.
It’s wild how banana republic level corrupt the US is all of a sudden. Really went from 0 to 100 in months
Like most of this stuff, it's obviously impressive technology compared to what existed a few years ago. But the end product has zero artistic value. It's a grey goo of the average of every concept picked up from the concept of the song.
A talented creative with a vision could make something more interesting and enjoyable in an afternoon with a $0 budget.
This might be the most impressive website generator demo I've seen: https://macos27.kimi.page
Context from the person who prompted it: https://x.com/mweinbach/status/2077827886149439547
> Here's a term for what I think is happening: the human reward function problem. In machine learning, a reward function tells an agent what good looks like. Writing code by hand was never easy, but it was full of small rewards. Solving a problem in your head. Understanding a gnarly bit of logic. Watching the code compile. The feeling of control. LLM-assisted programming has automated much of the work that generated those dopamine hits and replaced it with the cognitive load of review and supervision. The satisfying part shrank. The exhausting part grew. And there are no new rewards to fill the gap.
Say what you will about the Claudisms in this piece, this bit certainly rings true for me. With old school coding, there was always a reward at the end, the harder it was, the more satisfying it felt.
With agentic coding, I really doesn’t feel like that, at least not in the same way. It feels more like continually riding a wave of productivity, where small features or huge features have similar levels of interaction required. And that’s exciting in the beginning but quickly becomes very tiring.
If there was some grand strategy for all Chinese labs, surely it'd have leaked by now. I think its more likely that:
- Companies can still make money from commodities
- Chinese labs only have 5-10% the valuation of OpenAI/Anthropic, so massive monopoly profits aren't necessary. Profit expectations for tech companies in China are really low in general, complete opposite of the US.
- Open weighting is a great way to get talent/attention/reputation
So Chinese labs are driving essentially towards commodotized intelligence. Even if its a few months behind the US.
Is this a classic 'commoditize my compliment' situation? They want to sell the hardware and infrastructure behind AI and make the software part not the value driver / moat?
I can see it. But also even two Chinese labs sinking 100s of millions USD into training isn't exactly commoditization. It's still a ton of effort with dubious payoff.
> Chip Design
> As an early proof of concept, Kimi K3 designed a chip to serve a nano model built on its own architecture. In a single 48-hour autonomous run, K3 built, optimized, and verified the chip using open-source EDA tools on the Nangate 45nm library. Within 4 mm², the chip closes timing at 100 MHz and sustains over 8,700 tokens/s decode throughput in simulation, packing 1.46M standard cells, 0.277 MB of SRAM, and an INT4 MAC array with fused dequantization. A chip built by a model, for a model, reflects K3's long-horizon agentic capabilities.
Absolutely wild.
Me:
Ok so I'm going on a walk. I'll dump a link to a Hacker News
discussion about an article.
You have to read the article and the discussion and walk me thru
all the interesting details, nugget by nugget, and move on when
I'm ready for the next piece.
ok, Great show me the link, I'm waiting.
Me:
Ok I pasted it. Now go.
For the Socratic quiz I say:
I want to understand this more deeply. So instead of you just telling me
everything, lay out the problem and a question for me to think about, and
I'll try to answer. Even if I answer wrong, you should resist giving me the
answer, and instead keep digging with more questions, so that I eventually
arrive at the answer myself.
https://pchalasani.github.io/claude-code-tools/plugins-detai...
When notebookLM was new, it was interesting to listen to the podcasts. Then the novelty wore off, and I wanted something where I can interact with the podcasters but it was janky as hell.
My current “audio-learning” hack is ChatGPT Live which has become shockingly good after being awful compared to Claude Voice (Let’s not even talk about Gemini voice which is still bad).
I go on a walk and dump a paper or article link in the chat, and ask chatGPT Live to walk me through the content in small nuggets, so I can discuss them interactively. For deeper topics I have it quiz me Socratic style so I’m not just passively listening, and actually thinking through problems or ideas.
Hi, I'm Robert Standefer, the guy who made this happen, with lots of support. I'm excited to see the enthusiasm about Comic Chat being open sourced. How this came to happen is a very interesting story that spans a six-year period with success that hinged upon being in the right place at the right time, literally.
I want to point out that, while I (along with Scott Hanselman) made the Comic Chat open source release happen, I am not the original developer. That is DJ Kurlander, and he was very supportive of this project. He was even enthusiastic about it.
Is it useful? No. Does it stop AI from reading it? Also no. But is it cool? Yes, it is very cool.
> I think that for the hot binary patching / code reloading features, yes, that is going to need unsafe. But for regular old "producing an executable" compilation? Emitting machine code isn't the part that requires unsafe. The language's runtime is a more likely site to find unsafe.
Agreed! Emitting machine code is not unsafe, since it's just writing bytes down - it's only once you execute that machine code that there's potentially unsafety. The reason I said "a big part of the job" is that in practice a lot of compilers both emit machine code and execute it - but you're totally right that it's not a requirement that a compiler do both.
In addition to the examples you gave (hot binary patching/code reloading, language runtime, etc.), others would be things like evaluating userspace code at compile time (e.g. const fn in Rust, or in Roc any expression that could be hoisted to the top level), running tests and inspecting their output to decide what to display to the user, etc.
Those are the types of things I had in mind when I wrote that.
Pelican: https://tools.simonwillison.net/markdown-svg-renderer#url=ht... - rendered via the OpenRouter API: https://openrouter.ai/moonshotai/kimi-k3
95 input, 16,658 output = 25 cents! https://www.llm-prices.com/#it=95&ot=16658&ic=3&oc=15 (13,241 of those were reasoning tokens.)
I think that's the most expensive pelican I've rendered through a Chinese model so far.
> its overall intelligence ranks second only to Claude Fable 5 and GPT-5.6 Sol
Pretty sure ranking “second” to two others means ranking third.
I think this is a fine post. But one comment:
> remember that for compilers which emit machine code, like roc and rustc, doing memory-unsafe things is a big part of the job
I don't really think that this is true, in the way that it's written.
I think that for the hot binary patching / code reloading features, yes, that is going to need unsafe. But for regular old "producing an executable" compilation? Emitting machine code isn't the part that requires unsafe. The language's runtime is a more likely site to find unsafe.
More details:
- https://platform.kimi.ai/docs/guide/kimi-k3-quickstart
- https://platform.kimi.ai/docs/pricing/chat-k3
1M context, pricing is $3/$15 for 1M tokens (cache $0.3), which is extremely high for a Chinese open-weight model, but if it's truly competitive with most of the current frontier and is only behind Fable/Sol, the pricing is justified.
This is 1:1 pricing of Anthropic's Sonnet series (except Sonnet 5 which is currently on discount), and very close to 5.6 Terra pricing (Terra's input is $2.5).
One thing to consider, though: reasoning efficiency matters directly for how expensive a model actually is in real use. GPT's models are extremely reasoning efficient, and some Claude models like Fable at lower effort are as well. So if Sol spends 10K reasoning tokens to do something (at $30/1M) vs Kimi K3 that spends 50K reasoning tokens, Sol would win on cost effectiveness.
California Assembly Bill 2426 (AB 2426), effective 1 January, 2025. Expands the state's false advertising laws to explicitly ban companies from using words like "buy," "purchase," "own," or "keep" if what the customer is actually getting is a revocable digital license governed by shady T&Cs.
OnePlus is one of the saddest stories out there. It was the hacker's choice for a while. It was originally the "Never Settle" phone that ran mostly stock android, had specs maxxed out, price was great, and bootloader was unlocked plus they provided factory images. Those were all reasons I bought a lot of OnePlus phones in the early years.
Then they flushed nearly all of it down the toilet. The day they stopped posting factory images was the day I saw the writing on the wall. Such a shame.
Former GOES engineer here. At this point I'd almost be surprised if 19 didn't have something go wrong. We had issues on almost every other satellite. GOES-17 had the loop heat pipe anomaly(Supposedly from someone stepping on it in the cleanroom...), GOES-15 (IIRC) had a micrometeorite strike, and GOES-13 had a fuel tank anomaly right before deorbit.
GOES-16 and GOES-17 are on-orbit spares, so in the extremely unlikely event of a total failure there's at least another spacecraft on-orbit ready to take up station.
That said, I have every faith in the GOES team to get to the bottom of this. They're the best, and I often wish I was back there working with them.
IANAL, but is it illegal to have a "Buy" button that is just a disguised "Rent" button?
If not, should we change the law?
Whatever you think of AI for your own work, the fact that the entire economy is betting everything on it is really concerning. It’s not just the fact that it may not work well economically speaking and would end up with a market crash, or all the negative externalities from AI development, it’s also the opportunity cost we are paying. With so much human capital and resources dedicated to developing and running LLMs all the other business, research opportunities aren’t being explored and invested in
“Shocking nobody” I would add… This is an obvious Musk scam and anyone with financial knowledge called it as such ever since it’s been on the table. Why else lobby and change the NASDAQ listing rules for instance?
Editorialised! No new products, not halts operations. Please be more careful.
OnePlus has decided to conclude new product rollouts in Europe and North America.
The difference matters for those of us on OnePlus devices:
Though we will no longer launch new products in Europe, our commitment to you remains unchanged. Backed by OPPO, existing OnePlus devices will continue to receive scheduled software updates and security patches within the support periods originally committed for each device model.
Etc.
Based on YC's directory, there are approximately 13,000 YC founders since YC started.
105/13000 is a very small number to focus on. This data doesn't really mean anything.
The thing I miss most, and the thing we’ll never get back was the cultural buy-in and network effects.
My music discovery then was different friend groups incrementally amassing large collections of albums in whatever sub-culture that friend groups had doubled down on. My iPod would be the culmination of my friendships. I would then fall in love with bands and albums and tracks on these albums without any influence before hand on their popularity or their algorithmic match to my music tastes.
The result was pure joy: my music taste would develop in all weird and wonderful directions, my favorite songs would be the one I hit back on to listen again while I moved through an album, songs that friends skipped over and didn’t know at all; bands that never charted anywhere but made interesting music… bands that never knew their music made it to an iPod in South Africa.
(I’ve got a song still stuck in my head from a Canadian indie band that made its way onto my iPod via via and I’ve done all the searching in the world for the lyrics I remember and have never found the band. I love this that I’ve never found them!)
I make an effort to use Spotify to find and listen to albums, but it wasn’t built for this, and invariably find 90% of my listening happening on algo-generated playlists of songs that sound exactly like a song I like. I never learn the names of the songs or the names of the bands as the songs go by, and I fall in love with none of it… It just vaguely sounds like stuff I like. It sucks.
I don’t listen to any AI generated music consciously, but given the music experience today I probably wouldn’t notice as these playlists, like a boiling frog, slowly became AI music dominated.
I bought a record player as my protest, and it gives me immense joy to find obscure records and play them through; but it’s really not the same thing, and I miss what we had.
> Bluesky recently acquired the rights to the trademark for “ATPROTOCOL” and its variants—including “AT Protocol” and “atproto”—from another company that was threatening to take legal action preventing the company and others from using the term. Now that Bluesky owns it, the atproto community’s continued use of the mark can be protected.
The policy around usage is shared in the rest of the post but the goal is to make this very simple for everyone
I had Fable 5 compile that Rust code to WebAssembly and build a browser-based playground for it, so you can try it out with Mermaid diagrams here: https://tools.simonwillison.net/grok-mermaid
A few more notes on my Grok code explorations on my blog: https://simonwillison.net/2026/Jul/15/grok-build/
There's some surprising stuff in this codebase. For example, https://github.com/xai-org/grok-build/blob/b189869b7755d2b48... is a "self-contained terminal renderer for Mermaid diagrams", which renders a subset of Mermaid chart types using Unicode box-drawing.
I'm not sure I like this idea. Braintree is a legit competitor to Stripe. I'm guessing they have some informal agreement to keep transaction fees about the same but if they become 1 company, what's to stop Stripe from raising fees even more?
I'm not a fan of either to be honest, PayPal once told me I was wrong with something related to taxes and a bunch of different reps told me what I was saying and reported was impossible. Their tax division specialists also replied by email with big bold red letters outlining how it's not possible and that I'm wrong multiple times. They were contacted through support cases I opened with other reps on the phone since they aren't directly accessible on phone.
Then I said I was canceling my account with them if this wasn't resolved since it would have resulted in me needing to pay $400 to have my taxes amended. Long story short, after being ghosted for 3 months they replied to me saying I was right and they indeed had the impossible problem, then fixed their tax forms a week before taxes were due.
It's really bad that a random person on the internet discovered a huge issue with one of their partners and their instinct was to require ~10 hours of back and forth phone calls, multiple emails, me giving them the likely problem and solution on day 1 only to be lead on and ignored for months until the very last second.
America needs its own DeepSeek or Z.ai, a lot of people (myself included) root for open chinese models to win because they have no other choice.
Thinking Machines might be it.
> My goals for the end of 2027 are as follows:
> Stop making stupid mistakes. I want to be able to finish a task fully without missing or skipping a step. One way to do this is to make a plan for everything you do, and only do that thing. Nothing else.
HN comments are _NOT_ going to help debugging your mental state. People here have trouble agreeing on engineering, product and business practices they specialise in. They are _NOT_ going to guide you in the right direction on mental health topics.
Please OP, close HN, reach out to people, get help, and (importantly) learn to navigate your mind, not fight with it.
I don't mind cosmetics, but noise is something some places fortunately started regulating and I hope it becomes more common:
https://nltimes.nl/2026/05/28/rotterdam-deploys-first-noise-...
I'm hearing someone gunning it through a neighboring road as I type this comment and I will be hearing such noise all night, because some people just can't help but make noise.
The other day I even saw a guy in a car with a modified exhaust and driver side window rolled down - apparently so that he would better hear the noise he's making. Considering the volume that had to have a negative effect on his hearing.
I don't understand and I will not understand.
More pertinently "the term is purely descriptive and therefore lacks the distinctiveness required for trademark protection." I.e. the problem isn't that OpenAI's products don't match their description, but that trademarking it would unduly prevent others from describing their openly accessible artificial intelligence as "open AI."
> The EUIPO found that the word "open" would be understood by the relevant public as meaning freely accessible, while the combination with "AI" (artificial intelligence) would be interpreted as referring to products based on openly accessible artificial intelligence.
> for certain software and information technology goods and services, the term is purely descriptive and therefore lacks the distinctiveness required for trademark protection
edit: add the latter statement
Someone finally asks some sensible questions, about hijacking of the term "open".
I love cars and driving them. But the modded Corolla/Civic/Accord/Camry (why) people have always driven me crazy because their mods often seem directed to inflicting their cars on everyone else, with loud exhaust, subwoofers, and (subjectively) garish cosmetics, rather than things that make it actually good to drive.
I recognize this is judgmental and it's unhealthy to always be annoyed at these people on the road, so I clicked the article looking for some empathetic understanding - and I really got it, UNTIL he told me about his "fire-breathing" exhaust and subwoofer. So it is about subjecting OTHER people to his car.
So, the inclusion rules are basically "these are the hard limits that specify which stocks are eligible, unless someone really big and lucrative comes along, in which case it's whatever and we'll just adjust the rules to make them eligible"?
The worst about the SpaceX IPO is Nasdaq changing their inclusion rules for the Nasdaq 100. The index fast-tracked SpaceX stock for inclusion 15 days after the IPO, instead of the normal three-month seasoning period. They also changed its 10% minimum float rule to a 3x weighting boost for low-float stockss. So many people will unwillingly and prematurely invest into SpaceX, before it has any chance to discover its real price. IE: The floating, 5% at launch, could attain 30% end august, if Nasdaq didn't change their rules it would have included SpaceX after this..
https://finance.yahoo.com/markets/stocks/articles/nasdaq-che...
Magnesium supplementation solved my sleep issues.
I have seen many doctors, including sleep specialists, regarding insomnia. They all pointed to one source as the reason for the sleep issues: stress. And they all wanted to put me on prescription sleeping pills. I said no to that. Sleeping pills can cause dependence, and they often treat the symptom rather than the underlying cause. As a software developer, I am used to finding and fixing the underlying problem instead of relying on the quick fixes these doctors were offering me.
After much research, I figured out what I believe was the underlying problem, and the fix for it. The underlying problem was magnesium deficiency. As a software developer, I spend much of the day doing mentally demanding work. This is the kind of stress the doctors were talking about. Stress can increase the body's demand for magnesium and may contribute to low magnesium levels.
The cells in our body depend on minerals such as calcium and magnesium for normal function. In muscle and nerve cells, calcium helps switch the cell into an active state, while magnesium helps keep that activation under control and supports the return to a resting state. When you are low on magnesium, your muscles may remain tense and your nervous system may have a harder time settling down. That can contribute to muscle stiffness and difficulty sleeping.
The solution, in my case, was magnesium supplements. They fixed my muscle stiffness issues and my sleep issues. A special form of magnesium called magnesium L-threonate may be especially helpful for the brain because it appears to raise brain magnesium levels more effectively than some other forms.
Doesn’t surprise me.
Yesterday I learned that people run AI agents on their system with full admin rights. No containerisation or anything. Wild. Like we forgot 50 years of computer security overnight.
> Some code associated with Nedryland is visible on screen. It looks like actual source code[9] with Classic Mac OS API functions calls
The source code shown is example code included with the Macintosh Programmers Workshop, Apple's original IDE for the Mac. Originally sold as a separate product, eventually it was provided on the Developer CDs and then as a free online download as serious developers had moved to CodeWarrior. https://en.wikipedia.org/wiki/Macintosh_Programmer's_Worksho...
One of the windows shows the example for how to make a HyperCard XCMD and the other one looks like an MPW script for using Apple's Projector source control.
edit: Found the files in question in a copy of MPW 3.1. Line endings have been converted from CR to LF and the character set from MacOS Roman to UTF-8 to display easily in modern browsers
MPW 3.1:Examples:HyperXExamples:Reduce.p https://kalleboo.com/linked/Reduce.p.txt
MPW 3.1:Examples:Examples:CheckOutActive https://kalleboo.com/linked/CheckOutActive.txt
MPW 3.1:Examples:Examples:DerezPict https://kalleboo.com/linked/DerezPict.txt
> It is unclear how Jurassic Park crew got their hands on a Motorola Envoy
The head of frogdesign (Hartmut Esslinger) ended up running into Spielberg on a plane and showed it to him. The one in the movie is an original mockup.
Source: https://www.therpf.com/forums/threads/jurassic-park-tablet-d...
Discussion: https://news.ycombinator.com/item?id=46752261
The gov.uk Design System calls this the "Exit a page quickly" pattern [1], with an associated component [2]. It can be activated by clicking the Shift key three times.
There's this nice blog [3] that explains why they chose Shift instead of other keys, and also gives a nice overview of the pattern.
[1] https://design-system.service.gov.uk/patterns/exit-a-page-qu... [2] https://design-system.service.gov.uk/components/exit-this-pa... [3] https://beeps.website/blog/2024-10-09-why-govuk-exit-this-pa...