gwern

Also, PDF caught up on size with JBIG2, and tooling/support keeps getting worse.

(Not so fun fact: if you punch "filetype:djvu" into Google right now, you can easily page through what supposedly is every DjVu file on the Internet as far as Google knows, which is not many: "In order to show you the most relevant results, we have omitted some entries very similar to the 300 already displayed." I learned this the hard way when I began wondering why a bunch of DjVu fulltexts I hosted never seemed to show up in Google or Google Scholar...)

An idea the website could borrow from video games is removing elements after a while, like _n_ page views. (You can store the state in cookies, LocalStorage, or perhaps track server-side by IP+useragent.) The reader enjoys the dancing jelly for a few pages, and then as it gets old, it goes away automatically.

(On Gwern.net, we call this 'demo mode', and we use it to hide some UI elements after a certain number of interactions or page-views, under the theory that if you've, say, uncollapsed a collapse region a few times, you've gotten the idea, and you no longer need a big obtrusive text label saying 'click or hover to uncollapse'.)

Is Kimi still non-sloppy? When I switched to 2.5, it suddenly felt noticeably less creative and base-model-like, more sycophantic, and it hasn't gone aggro at all. Feels like a lot of the magic is gone.

> I kept a running log for each sibling as I was manually doing the labeling, knowing what they'd want to see, which presumably is only possible for me and my siblings to do with any accuracy.

But you could feed that back in! Just write it down. It's all tokens. As you read over descriptions and note down key pieces of family history or per-sibling details, that provides information about better annotating the next video for possible points of interest. And you can chat with the LLM and write down more general principles. It's not like a LLM like Gemini doesn't know an enormous amount about family life and things of sentimental value, and can't make good initial guesses. And when you do this, you still haven't used up more than a small fraction of the context window with these image references and text profiles and principles...

> My siblings are very much not developers. That's a lot of data for them to download, store, and figure out a way to view.

I wasn't suggesting anything about your siblings, but you, who are a developer. I was just talking about the actual download step, not what you did after that. (Obviously you were going to host them somewhere else in some other form. Probably not DVDs but a little quickie website or maybe just a Flash drive with a HTML file index, say, I don't know, lots of options here to make it user-friendly for your siblings on Christmas Day. The hard drive or Flash drive idea has the benefit of LOCKSS, especially if you use up the spare space providing PAR2 FEC.)

> I doubt any model could effectively label locations and people over 20 years of video.

Actually, Gemini is highly promptable with a large context window and a single still image only takes up ~300 tokens IIRC, so I think that you could probably do so! Just include, say, 3 photos of each person over time with a natural language description, and 1 photo of each location, and that might be enough to get back useful labels. Gemini can even do bounding boxes. (Google is quite proud of its vision and video analysis capabilities.) And you can run multiple passes or split up videos etc.

A Dododo Land on that premise would be more interesting than what is described, which is weak tea social commentary. A Dododo Land where the doors are confusing and you have to pull rather than push - where there's typos everywhere and the kerning is always inconsistent or sometimes the font randomly changes and everything is hung 1 degree off level - where you pay for a ticket but then it errors out at the entrance and the clerk tells you that your payment must not have gone through - where a few lights just flicker once in a while and there's an odd high-pitched sound that half your group can't hear but sounds like tinnitus - where the employees are reading manga and you have to get their attention by coughing loudly - ...

I'm not familiar with 'AWS datasync', but isn't the point of Glacier that it's really expensive and slow if you retrieve everything? It sounds like a bad idea for videos he planned to download in order to catalogue them. (He might want to delete them or could safely infer that 'no, neither me nor my siblings will want to watch this on Christmas Day', yes, but he still has to look at them first since he doesn't know what's on them at all.)

> I searched for services which offered to digitize Video8 tapes. Most services cost about $20 per tape. Even with discounts for bulk amounts, it would likely have cost about $2k! I considered paying it (how exactly do you value a few hundred hours of childhood video?) but then I noticed how they delivered the videos - a private media hosting solution for 60 days. I knew this would be a huge amount of data, and only giving me and my siblings two months wasn’t sufficient.

I'm not following here. Even if it was several terabytes of video (digitized at high resolution and minimal lossiness for archival purposes), that's plenty of time to download. Especially if you're a developer who can casually spin up a cloud or dedicated server to proxy through if need be? (And $2k sounds reasonable once you start going through "hundreds of hours" at a bare minimum, and again especially if you're a developer with real opportunity cost.)

Also, as far as the video analysis goes, Gemini might've been a better idea?

(An example of something which may already exist but I didn't see in my demo - more thoughtfulness on how to handle long-running tasks, and let us switch to something else, instead of us busy waiting on CC. For example, perhaps use of the system bell? That's usually set to flash or update the terminal title, and you can set your window manager to focus a window on the bell. I have my XMonad set to jump to a visible bell, which is great for invoking a possibly slow command: I can go away and focus completely on whatever else I am doing because I know I will be yanked to the backgrounded command the instant it finishes. I even set up a Bash shortcut, `alert () { echo -n -e '\a'; }`, so I simply run stuff like `foo ; alert` and go away.)

> The amount of output this generates can quickly become overwhelming in a terminal, and is something we hear often from users. Terminals give us relatively few pixels to play with; they have a single font size; colors are not uniformly supported; in some terminal emulators, rendering is extremely slow. We want to make sure every user has a good experience, no matter what terminal they are using. This is important to us, because we want Claude Code to work everywhere, on any terminal, any OS, any environment.

If you are serious about this, I think there are so many ways you could clean up, simplify, and calm the Claude Code terminal experience already.

I am not a CC user, but an enthusiastic CC user generously spent an hour or two last week or so showing me how it worked and walking through an non-publicly-implemented Gwern.net frontend feature (some CSS/JS styling of poetry for mobile devices).

It was highly educational and interesting, and Claude got most of the way to something usable.

Yet I was shocked and appalled by the CC UI/UX itself: it felt like the fetal alcohol syndrome lovechild of a Las Vegas slot machine and Tiktok. I did not realize that all those jokes about how using CC was like 'crack' or 'ADHD' or 'gambling' were so on point, I thought they were more, well, metaphorical about the process as a whole. I have not used such a gross and distracting UI in... a long time. Everything was dancing and bouncing around and distracting me while telling me nothing. I wasted time staring at the update monitor trying to understand if "Prognosticating..." was different from "Fleeblegurbigating..." from "Reticulating splines...", while the asterisk bounces up and down, or the colored text fades in and out, all simultaneously, and most of the screen was wasted, and the whole thing took pains to put in as much fancy TUI nonsense as it could. An absolute waste, not whimsy, of pixels. (And I was a little concerned how much time we spent zoned out waiting on the whole shabang. I could feel the productivity leaving my body, minute by minute. How could I possibly focus on anything else while my little friendly bouncing asterisk might finish at any instant...?!) Some description of what files are being accessed seems like you could spare the pixels for them.

So I was impressed enough with the functionality to move it up my list, but also much of it made me think I should look into GPT Codex instead. It sounds like the interfaces there respect my time and attention more, rather than treating me like a Zoomer.

I don't know, this one is a little novel. I've never seen the developer of a Buddhist meditation app discuss whether to use LLMs with a paragraph like:

> Pariyatti’s nonprofit mission, it should be noted, specifically incorporates a strict code of ethics, or sīla: not to kill, not to steal, not to engage in sexual misconduct, not to lie, and not to take intoxicants.

Not a whole lot of Pali in most LLM editorials.

Fulltext: https://gwern.net/doc/longevity/glp/semaglutide/2026-qin.pdf

No, I think I'm mistaken (and confusing it a little bit with the autobiography of Aleister Crowley, who was also something of an explorer and which I read around the same time - it is also interesting and untrustworthy but not as good overall IMO). I don't recall if it was the Farwell, Hastings, or Rice, unfortunately.

The autobiography of Burton is one of the great ones in English. Is it all true? Who knows, but Burton sure told his yarns.

You don't even need to do git or a tarball! HTTP/HTML already has an "API" for serving Markdown to any agent like a LLM which wants it, because you can easily set a server to return Markdown with an accept-encoding (kinda why that functionality exists in the first place).

I set my nginx to return the Markdown source (which is just $URL.md) for my website; any LLM which wants up-to-date docs from my website can do so as easily as `curl --header 'Accept: text/markdown' 'https://gwern.net/archiving'`. One simple flag. Boom, done.

It seems like the lesson of vibecoding et al is that you want to disable pulls for code but you want to keep them for bugs, test-cases, and requirements. Because that is now what is scarce.

You want people to keep contributing things like a unit-test that the current codebase fails on, or a design rationale for a feature, or an unenforced invariant. Then, after the expert human signs off on that, verifying that the new unit-test is in fact correct, then your trusted LLMs can solve any coding from there.

So, the ad hoc short-term Github solution is probably something like leaving pull requests enabled, but figuring out how to auto-reject ones which touch any implementation code. Depending on how inconvenient that is (maybe code/doc/tests are too intermingled, like typing declarations), you might try to channel everything through an issue.

Previously discussed (and criticized) at https://news.ycombinator.com/item?id=46722853

Thanks for the LLM comment, but that's dumb. If the problem really was as bad with humans (it obviously is not), then OP wouldn't've happened:

> For most of the articles Pangram flagged as written by GenAI, nearly every cited sentence in the article failed verification.

I don't get it. Embeddings don't prioritize, or even necessarily encode, truth value as a dimension. And even if they did, if you simply accept based on some hyperparameter of distance, it sounds like this procedure just leaves you vulnerable to problems like salami-slicing where you reach 'the sky is green' (which after all, it is sometimes) by multiple steps just below the tolerance.

OK, this is AI slop ("fracture" alone gives it away). But maybe there's still something of value here? Can you explain it in actual human terms, give a real example, and explain what you did to test this and why I shouldn't flag this like I did https://news.ycombinator.com/item?id=46701114 ?

A discount they get to set on a subset of miles of their choice may just be a marketing expense for an insurance startup which makes losses and relies on VC capital and needs growth: https://en.wikipedia.org/wiki/Lemonade,_Inc.#2015%E2%80%9320... I was impressed by this until I looked Lemonade up.

(To stop being lazy, the 2020 reference is: https://news.ycombinator.com/item?id=25426329 )

> E.g. gemini-3-pro tops the lmarena text chart today at 1488 vs 1346 for gpt-4o-2024-05-13. That's a win rate of 70% (where 50% is equal chance of winning) over 1.5 years. Meanwhile, even the open weights stuff OpenAI gave away last summer scores between the two.

Why do you care about LM Arena? It has so many problems, and the fact that no one would suggest using GPT-4o for doing math or coding right now, or much of anything, should tell you that a 'win rate of 70%' does not mean whatever it looks like it means. (Does GPT-4o solve roughly as many Erdos questions as gemini-3-pro...? Can you write roughly as good poetry?)

Hm... I think I would predict that it would depend on speed because querying prices reveals information, but not accepting also reveals information, so I would expect that it would go up initially due to an expected shortage, but then when it becomes clear that no one is accepting, it reverts to normal or lower, because that suggests low urgency or willingness-to-pay compared to what the models had forecast for that exact location & time, so they have to be offered lower prices to accept at all.

(This is the flipside of personalized pricing: it's also lower prices, as noted in some of the anecdotes, although he mostly emphasizes the potential for higher prices.)

Well, whichever one checked first, the point still holds. Checking is not a free operation and you should expect it to have consequences and it to affect Uber's demand forecasts etc., and affect other price quotes. You do not have independence here and so the comparison is not as meaningful as it seems. As the Roman wit said, "when two people do the same thing, it's not the same thing."

(The right way to do this is to randomize multiple independent occasions - wait until one of you was about to call an Uber, immediately flip a coin to decide who does, each time checking you or your wife's Uber, and never both, and compare the long-run average.)

> with an apologetic confirmation dialog, possibly only after some holding period has timed out

Right. I've seen the same thing myself. They would prefer not to apologize to the customer because they changed the price, because it is in fact annoying and a bad customer experience. So the prices are surely carefully set in many ways with an eye towards not changing as much as possible.

> This enables people to construct a plausible story to explain any price.

Indeed. So you should mention one of the most plausible stories if you're going to list a bunch of them.

Not going far enough - why would applications be written in either 'systems languages' or 'agent languages' if you have superintelligence too cheap to meter and you will amortize the costs over more than, say, a few days? Just write in raw assembler from a domain-specific design hyperoptimized for solely the task, the way Donald Knuth on steroids would.

> Who knows why? I’m usually more willing to spend than she is, and I bet that's represented on my user profile. I was paying with a gift card, which surely contributes. Maybe it was a price scraping update, comparison shopping detection, or a system that explores “face-in-the-door” high prices before backing down. From the outside, no one really knows.

The most obvious possibility omitted is that your wife got the first, easy, cheap car and then Uber had to quote you a higher price to get a second car. Cars don't fall from the sky; if two people successively ask for bids, how else could it work? What if the app quoted you both the cheap price for the only car within X blocks, and you bought it before she did? Is it suddenly going to go 'oops sorry, changed my mind, it now costs twice as much'? Sounds like a very bad experience to me! More sensible to give the first person a low quote and then when - unexpected and unpredictably - someone requests something similar, quote them the higher price reflecting the sudden local micro-shortage.

> It's like how software engineers who are at Google are worse if they're better competitive programmers.

That's not true. It didn't replicate and Norvig has said as much somewhere on HN, IIRC.

(I also agree with the other criticisms that this 'old vs young' setup in OP is obviously at least partially, and perhaps entirely, regression to the mean and Berkson.)

> I mean, its open source so people can create benchmark and independently verify if the AI was wrong and then have the claims be passed to the author.

Thank you for volunteering. I look forward to your results.

It makes no sense because it's some degree of AI slop: https://reddit.com/r/selfhosted/comments/1qi64pr/i_got_into_...

Note that he doesn't quite say, when asked pointblank how much AI he used in his erroneous microbenchmarking, that he didn't use AI: https://reddit.com/r/selfhosted/comments/1qi64pr/i_got_into_...

Which explains all of it.

Kudos to /u/teraflop, for having infinitely more patience with this than I would.