skysight-inc/HackerNews huggingface dataset:
Measure measure measure measure. Each case is different.

But more seriously I think tree based algos tend to be overhyped, and people get a bit absorbed into thinking about big-O behavior when the constant factors are super important even when you’re looking at hundreds of thousands of elements. Not to mention stuff like data locality. Like sometimes your computer will be faster at just looking in a seq scan rather than dealing with the bookkeeping of a fancier structure. Sometimes.

I think a nicer argument overall is to build a tiny wrapper around your operations, build out what is easy, and then figure it out through measurements.

Worst case you end up entirely rewriting your program to accommodate a different structure to try for better perf but in my experience rewriting entire files from scratch tends to get you a good number of improvements for free.
It is not that simple, because a large part of the genes that originally belonged to the mitochondria or to the chloroplasts have been transferred into the nucleus and they are now completely integrated into it, even if evolution trees will show that those genes have a different history than the remainder of the nucleus.

So even if you want to use only the DNA inside the nucleus for a cladistic classification, that does not produce a tree of evolution, but only a directed graph of genetic information flows, with many important hybridization events. While initially mitochondria and chloroplasts were just symbionts, like the useful bacteria in the human gut, eventually that symbiosis has become a full hybridization, with mixing and integration of the genetic information.

The official cladistic classification produces a tree from the directed graph of the evolution by cutting the branches that are considered to be less important.

Sometimes this is indeed the best choice, but there are contexts in which the genetic information brought through the minor branches is actually that which determines most of the importance of an organism in an ecosystem.

E.g. in many contexts the most important feature of a living being is whether it is an oxygenic phototroph due to inheriting genetic information from some blue-green algae, i.e. that it is a primary producer in the ecosystem, and not the features that depend on which is the exact eukaryotic group from which most of its nucleus has been inherited. For instance, it is more frequently useful to group together brown algae with red algae (whose chloroplasts share a common ancestor), than to group brown algae with some non-phototrophic stramenopiles (which share a common ancestor for most of the nuclear DNA), with which they share only inherited characters that need an electron microscope for detection.
Pool of ideas, where to find them?
My discoveries are not enough. I see opportunities all around me, but there are currently many good projects around us. It is often a complicated task to make full use of them. But it is the only way I see of discovering new ideas, testing and observing where the good opportunities are.

Have you used any kind of technique or database to obtain ideas that can be reproduced to launch competitive products?
Not going to disagree that it's exhausting! I've been trying to stay on top of new developments for the past 2.5 years and there are so many days when I'll joke "oh, great, it's another two new models day".

Just on Tuesday this week we got the first widely available high quality multi-modal image output model (GPT-4o images) and a new best-overall model (Gemini 2.5) within hours of each other. https://simonwillison.net/2025/Mar/25/
we used to output C for native backend support
"How to ask for it" is the most important part. As soon as you realize that you have to provide the AI with CONTEXT and clear instructions (you know, like a top-notch story card on a scrum board), the quality and assertiveness of the results increase a LOT.

Yes, it WON'T produce senior-level code for complex tasks, but it's great at tackling down junior to mid-level code generation/refactoring, with minor adjustments (just like a code review).

So, it's basically the same thing as having a freelancer jr dev at your disposal, but it can generate working code in 5 min instead of 5 hours.
America as a whole benefits from being the world hegemon. Having the dollar as the reserve currency has allowed the US to run massive deficits, impose economic sanctions, and get cheaper resources (especially oil). All Americans have benefited from this - even the poorest American state would count as one of the richest nations in the world if it were independent.

If the people at the bottom don't see that, then its a fault of inequality in the American system. All nations and societies need to distribute wealth in some way, and there's nothing that says America needs to be high unequal to maintain its empire (or says tht having an empire implies inequality). That American society is so unequal is a decision that Americans have made. I doubt this is really because of the elites - America makes a big deal out of its democracy and even party leaders are elected by the people. But it is still a choice Americans have made.

Reliniquishing the empire will not help the people at the bottom. A world in which China dominates, in which the global reserve currency is the yuan or the euro, is not one in which Americans of any wealth prosper.
> Ultimately, the biggest price is paid by those on the bottom, with the least power.

What price specifically has or is being paid by those in the U.S. with the least power? That price whatever it is, is 100% due to U.S. foreign policy decisions? It's really not clear to me how decades of mostly stable global relations has concretely hurt the average American. Their wages have been depressed by domestic capitalism. The lack of housing can be largely attributed to bad local and domestic policy. The cost of groceries if anything are as low as they are because of global trade, not in spite of it. These are the things I hear people concerned about, I don't think I've ever in my life heard an average person express the sentiment that everything would just be better if we fucked over all our allies.
it is not the optimial, for fast native mode, we rely on tcc for fast interpretion
how does this compare with heat dissipated per square cm when you compare with desktop CPUs?
Debunking native in-browser spell-jacking
"an old poorly implemented model can't do item X well therefore the technology is garbage"

Likely the most accurate measure of progress would be watching detractors goalposts move over time.
the model is for me. I wrote a crude btc trading bot, and I had three major objects: Market(), TradingStrategy and SimulatedMarket which used historical data.

I did not model individual transactions, fees, etc as objects. The idea was that I encapsulated all the stuff that's relevant to a strategy in one object, and the market object would give me things like get_price(), buy(), sell(), which would also be available in the simulated version.
aye, to me they’re just a different interface to the same information publicly available via a search engine.

for folks who haven’t spent the last 15 years honing their finding out technical information with a search engine craft i can see why they might be useful.

but a search engine won’t sometimes mangle the output and provide an incorrect answer — it only provides a link to the raw data (webpage), rather than trying to create a paragraph of text about it.

i’d rather have access to the raw data guaranteed unmangled. i’m fast enough using that method.
It also can be used here:https://www.smoldocling.net, works well!
I honestly believe GP comment demonstrates a level of gullibility that AI hypesters are exploiting.
Generative LLMs are text[1] generators, statistical machines extruding plausible text.
To the extent that it a human believes it to be credible,
the output exhibits all the hallmarks of a confidence game.
Once you know the trick,
after Toto pulls back the curtain[2],
its not all that impressive.

1. I'm aware that LLMs can generate images and video as well. The point applies.

2. https://www.youtube.com/watch?v=NZR64EF3OpA
AI sludge in, AI sludge out.

It's just another version of someone who is relativity incompetent but can produce something vaguely convincing.
Do you have kids ?
> Bezos and musk don’t have to conspire together to oppose unions and squash them. They both gladly do it on their own and would do so without needing to conspire.

> But by framing it as a conspiracy that they work together, you can now dismiss that the fact that the activity is actually happening by simply saying that there’s no proof they are working together and that it’s just a conspiracy theory.

So basically, it's a straw man. Concoct a story where it's being done in a smoke-filled back room, then say it can't be true because neither Bezos or Musk are smokers.

Though I do wonder if there's a more indirect conspiracy going on. Business elites all have the same interest to oppose unions: maybe they don't often get together in smoke-filled back rooms, but they can pump money into the same anti-union think tanks and consultancies, which could have a similar effect.
Big thread some months ago https://news.ycombinator.com/item?id=40802557
How is the state of the various other bridges beside Saigang (eg. Chauk, Pakokku, Magway, Pyay, Tigyaing)?

Much of Saigang, Rakhine, and Kachin might be cut off from the rest of Myanmar, dramatically affecting logistics (though I think land logistics to Rakhine have already largely ended before the earthquake)

Also, I hope your family hasn't been drastically impacted.
I've been looking into what it would take to "theme" LibreOffice into something more Gnome-ish, less jarring to new users, for some reason there's been many project with that in mind and they all seem abandoned and / or in limbo
It mostly says that one of the seriously difficult challenges with LLMs is a meta-challenge:

* LLMs are dangerously useless for certain domains.

* ... but can be quite useful for others.

* The real problem is: They make it real tricky to tell, because most of all they are trained to sound professional and authoritative. They hallucinate papers because that's what authoritative answers look like.

That already means I think LLMs are far less useful than they appear to be. It doesn't matter how amazing a technology is: If it has failure modes and it is very difficult to know what they are, it's dangerous technology no matter how awesome it is when it is working well. It's far simpler to deal with tech that has failure modes but you know about them / once things start failing it's easy to notice.

Add to it the incessant hype, and, oh boy. I am not at all surprised that LLMs have a ridiculously wide range as to detractors/supporters. Supporters of it hype the everloving fuck out of it, and that hype can easily seem justified due to how LLMs can produce conversational, authoritative sounding answers that are explicitly designed to make your human brain go: Wow, this is a great answer!

... but experts read it and can see the problems there. Which lots of tech suffers from: as a random example: Plenty of highly upvoted apparently fantastically written Stack Overflow answers have problems. For example, it's a great answer... for 10 years ago; it is a bad idea today because the answer has been obsoleted.

But between the fact that it's overhyped and particularly complex to determine an LLM answer is hallucinated drivel, it's logical to me that experts are hyperbolic when highlighting the problems. That's a natural reaction when you have a thing that SEEMS amazing but actually isn't.
>[Christopher Null] has himself had to deal with countless annoyances, from American Express dropping his last name altogether, to Bank of America refusing to accept emails from his "nullmedia.com" domain.

I believe the first one but likely BofA refusing to accept emails from his custom domain has nothing to do with it starting with null and everything to do with anti-spam.
But is destroying illegally stored records relevant? I don't know the legal precedents
I bet they could get it even smaller for the 6809
That's awful in itself, but the one with Trump and Zelensky is the most disrespectful.
AWS DynamoDB reduces cost for on-demand throughput by 50% & global tables by 67%
Socially, emotionally, physically for example are ways people can be intelligent that is ignored in regular schooling.

Intelligence is largely related to STEM and memory in most instances. But there are a vast number of other ways to be intelligent. Perhaps you excel at emotionally connecting with people, maybe you're really good at cooking or tooling approaches. All of these are ignored in school.

School is nothing more then a checkbox along your path, you need to be able to read, write, do math, etc. But we ignore a large amount of our populace who may excel at grunt work, or maybe they are really good at leadership.

Just because you don't know y=mx+b or struggle at reasoning/logistical challenges does not mean you are not valuable to society. Maybe your 300lbs of rock solid muscle and in a past live would have been a top tier hunter. We do appreciate some amount of sports, but even that stops unless you're in the top 1-2% of the country.
The problem isn't that you're visible, or that what you're doing should be private, it's that any cop can access your location history for any reason, at any time, with no scrutiny. Cops are known to be abusive, violent thugs, and giving them this ability is definitely a dangerous route.

IMO these recordings should be kept by a third party, and cops should need to appeal to that third party to access it. Going before a judge to get a warrant would be preferred.
Sure, there may well be various structural factors which may explain some or all of the disparity - but it's worth noting that whenever there's an attempt to fix this, we hear endless complaints along the lines of "it's wrong to change selection procedures, there just aren't enough women or minority candidates applying, it's a pipeline problem".

Well, these comic books are an attempt to fix the pipeline problem.

In reality, there are likely multiple factors in play. But if you believe that, after removing "anything specifically targetting women" from their communications, NASA are going to alter downstream selection criteria in order to compensate then I suspect you are going to be disappointed.
Will it change?

Uber drivers are already paid low wages and any price competition can lower their wages further.

Waymo has to pay for things that “come with” uber drivers: the cars, storage for the cars, employees to clean and maintain the cars, extra infrastructure to support the self driving cars like cellular data for each car, data centers, engineers, customer service to interact with police and resolve edge cases (will never go away). Waymo also has to pay all these people healthcare benefits and pay W2 payroll, not a thing for Uber.

Waymo is like a professional moving company competing on price with an army of lowest bidder independent contractors who already have a beat up graffiti van.
I agree with the conclusion but I’m confused about the study…

It sounds like the author effectively spent a day at a children’s museum grocery exhibit and wrote a paper about it.

Is there more to the underlying paper than the summary suggests?

Anyone who has watched a 4-year-old for any length of time would conclude that at least some of them are capable of classification.
I love the idea that fungi house the Polises of Greg Egan.
i have had issues with clothing I think is inferior quality and likely counterfeit from amazon -- including when buying from what looks like "official" brand stores on Amazon. One example is Gold Toe socks.

I have wondered if even when buying from what looks like an official amazon brand store, you can still get product from multiple suppliers/locations, including some that have counterfeits? Anyone know if this is feasible?

It doesn't seem likely to me that (eg) Levi's or Gold Toe are doing this on purpose. It would also mean it would be hard to 'test' because you might get different things on different orders, it's not that the entire amazon supply is counterfeit, but that counterfeit stuff is in there somehow.
And uber is profitable. Waymo burns $2 billion a year.
I’m sorry but the experience of coding with an LLM is about ten billion times better than googling and stack overflowing every single problem I come across. I’ve stack overflowed maybe like two things in the past half year and I’m so glad to not have to routinely use what is now a very broken search engine and web ecosystem.
Next Uber will be pitching a privacy-centric upgrade, similar to VPN positioning today, to preserve privacy in the face of mass roadway surveillance.
I´m in the same boat and I think it boils down to this: some people are actually quite passive, while others are more active in their use of technology.

It`d take more time for me to flesh this out than I want to give but the basic idea is I am not just sitting there "expecting things". I´ve been puzzled too at why so many people don´t seem to get it or are so frustrated like this lady, and in my observation this is their common element. It just looks very passive to me, the way they seem to use the machines and expect a result to be "given" to them.

PS. It reminds me very strongly of how our parent generation uses computers. Like the whole way of thinking is different, I cannot even understand why they would act certain ways or be afraid of acting in other ways, it´s like they use a different compass or have a very different (and wrong) model in their head of how this thing in front of them works.
I do the opposite
SoftBank May Pledge $1T for AI Effort in US, Nikkei Says
I’m skeptical of the claim that Claude “plans” its rhymes. The original example—“He saw a carrot and had to grab it, / His hunger was like a starving rabbit”—is explained as if Claude deliberately chooses “rabbit” in advance. However, this might just reflect learned statistical associations. “Carrot” strongly correlates with “rabbit” (people often pair them), and “grab it” naturally rhymes with “rabbit,” so the model’s activations could simply be surfacing common patterns.

The research also modifies internal states—removing “rabbit” or injecting “green”—and sees Claude shift to words like “habit” or end lines with “green.” That’s more about rerouting probabilistic paths than genuine “adaptation.” The authors argue it shows “planning,” but a language model can maintain multiple candidate words at once without engaging in human-like strategy.

Finally, “planning ahead” implies a top-down goal and a mechanism for sustaining it, which is a strong assumption. Transformative evidence would require more than observing feature activations. We should be cautious before anthropomorphizing these neural nets.
For what came up to me when searching for Python info before I blocked it, they still have plenty of incorrect information or information that's useless for the tutorial page it's on
Yeah independent of commuting, I'd not want to work for my company if I had to spend a lot of time with my coworkers in person. You want people to gel like that in person and I'd need really different demographics. Online it's fine.
I've skimmed the post, and I've clicked through to the license[0], but I'm not clear on what is meant by "firewall license"?

Is it just that the license doesn't allow use by corporations, and that's why they say the target audience is:

> Those who reject genocide-friendly software licensing

Can someone help me grok it a little better?

[0] https://github.com/LGUG2Z/komorebi-license
The question I ask afterwords then is: is solving some leet code brilliant? Is designing a simple inventory system brilliant if they've all been accomplished already? My answer tends towards no, since they still make mistakes in the process, and it harms newer developers from learning.
This is more a lack of understanding of it's limitations, it'd be different if they asked for it to write a python script to collate the data.
What does the article have to do with Trump? He won't be president forever.
If you have the first trait but not the second then you are pretty much doomed to misery (unless you happen to be very lucky).
Government defining Truth is about as Orwellian as it gets
https://nitter.net/search?f=tweets&q=myanmar
Yeah I'm curious now.

If you have a lot of GPU's and you're doing massive text processing like spam detection for hundreds of thousands of users, sure.

But "as a single developer", "value for me and my team"... I'm confused.
It seems most organizations naturally become more risk-averse as they age and grow since the business becomes more well-defined over time and there is more to lose from risky ventures. The culture has to reward meaningful risk-taking even when that risk-taking results in a loss, which can cause issues when people see the guy who lost a bunch of money getting a bonus for trying (not to mention the perverse incentives it may create).
It says we don't have a lower bound on the effectiveness.

It's (currently) like an ad saying "this product can improve your stuff up to 300%"
> Nothing is changed by creating a `const newStroke` and pushing it to the array.

Not true. If you look carefully you will see the `const` and everything after it is wrapped in curly braces, and those braces create a block...

> Traditionally (before ES6)... blocks with curly braces do not create scopes... [but] blocks are finally treated as scopes in ES6, but only if you declare variables with let or const. — https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guid...

So the curly braces with the use of const/let creates a new lexical scope, hence solving the issue. You can test it in the browser console to confirm;

var stack=[], cmd="";
cmd="success"; stack.push(()=>cmd);
cmd="fail"; stack.push(()=>cmd);
stack[0](); /* returns "fail" */

var stack=[], cmd="";
cmd="success"; {const c=cmd; stack.push(()=>c);}
cmd="fail"; {const c=cmd; stack.push(()=>c);}
stack[0](); /* returns "success" */

It's probably not a good idea to do it this way, because it's easily "overlooked". I would probably use a class or factory-function if I had the need.
LLMs as a tool that you use and check can be useful, especially for code.
However, I think that putting some LLM in your customer-facing app/SaaS/game is like using the "I'm feeling lucky" button when Google introduced it. It only works for trivial things that you might not even had to use a search engine for (find the address of a website you had already visited). But since it's so cheap to implement and feels like it's doing the work of humans for a tiny fraction of the cost, they won't care about the customers and implement it anyway. So it'll probably flood any system that can get away with basic mistakes, hopefully not in systems where human lives are at stake.
Really well said:

> “ Good thing I have this blog. Here is where I make the rules. Maybe this will get a lot of readers, maybe it won’t. I don’t make any money with it either way. It’s out of my head now, and that is what counts. Do wonderful things that make you happy, folks. Chasing the numbers will not give you any fulfilment. Quite the opposite.”
> Unrelated to the article, but related to the topic, the compliment that gives me the most dopamine is when somebody I respect and is above my level of knowledge tells me “that’s a great question”. It just makes me realize that I’m closer to their level if I’m asking questions that stumped them or that they are already thinking of but surprised I asked.

I don't know this for a fact, but, I'm thinking there must be a lot of books on public speaking that tout this "trick".

Once, I noticed that an exec started constantly prefixing her every answer with "Yeah that's a great question" and I said to myself, huh she must have just finished some leadership book!

Of course, it quickly becomes pretentious, if used on every mundane question.