Bjorkbat

I was about to post a snarky comment along the lines of "Sierra? The publishers of Homeworld and Homeworld 2?"

I always got the impression that the only way a relatively average software developer could make a “successful” SaaS is if they built something weird and niche that appeals to an audience of <1000 paying customers. In that sense, it doesn’t really matter if your competition is better at SEO since your competition never even thought to build something like this, never cared, and not to mention that the market for this thing is so small that SEO is arguably a wasted skill. You’ll need to acquire these people by finding them directly or through word of mouth.

This blog post seems to fundamentally misunderstand the nature of solo-developer SaaS, but then again arguably mostly software developers also fundamentally misunderstand it.

To me demoscene is kind of synonymous with the Amiga, so I would argue that peak demoscene lines up with the rise and fall of the Amiga brand.

So I think that's maybe the other differentiator between web experiment and art, because demoscene has a very distinct but difficult to describe cultural element that makes me identify it as art.

I'm keenly aware, I have a pretty extensive collection of Hacker News bookmarks. It's hard to articulate why I think these are different, but I think the best way to put it is that cachemonet feels a lot more avant garde, and perhaps also a reflection of a very particular form of "web culture" that has no clear successors.

People are experimenting with what you can do on the web, but the experiments aren't very "aesthetically inspiring". For that reason I'm kind of lukewarm on neal.fun.

EDIT: so I think a better way to describe it is that when artists experiment with technology, you get something like cachemonet. When developers experiment with technology, you get a web experiment that challenges conventional notions of what you can do with the web, but with varying degrees of creativity. I think terra.layoutit.com is best appreciated by other web devs who can appreciate the sheer amount of work required to figure out how to render a terrain map in CSS, but otherwise it's basically just a tool to generate terrain height maps, and not a particularly good one. Generating terrain maps in CSS is not a feature, but a handicap.

Finding out that this is over 10 years old has made me profoundly sad. Despite the age of LLMs arguably unlocking massive amounts of productivity and agency for developers and non-developers alike, it feels as though we are living in a dark age of creativity on the web, maybe even a dark age for computer culture in general.

Ironically the physics are kind of my biggest criticism. They call these "world models", but I think it's more accurate to call them "video game models" because they employ "video game physics" rather than real world physics, among other things

This is most evident in the way things collide.

I’m sure there’s some boring neuro-chemical explanation for this, and I won’t doubt or deny the neuro-chemical explanation, but the fact that there’s a mushroom that consistently brings about hallucinations of tiny people is so bizarre that I kind of want to indulge in equally bizarre explanations. Maybe it’s not a hallucination and this mushroom simply allows us to see the tiny people all around us. Maybe mushrooms are intelligent and are intentionally making us hallucinate tiny people.

It’s a little bit crazy, I know, but it’s odd to me that evolutionary forces would produce a mushroom that makes you have some specific hallucinations, rather than simply make things swirl together or simply produce intense feelings of euphoria or dread. I mean, marijuana just gets you high and that’s that.

Oh yeah, funny enough even though I’m a bit of an AI art hater I actually thought very early Midjourney looked good because of all had an impressionistic, dreamy quality.

Funny enough that had crossed my mind with the woodchuck example, because at a glance I can't see any weird artifacts, but I felt confident I could tell it was AI generated immediately if I saw it in the wild, and I couldn't really explain why. My immediate guess was "well, who the hell would actually bother to make something like this?"

Something I find weird about AI image generation models is that even though they no longer produce weird "artifacts" that give away that the fact that it was AI generated, you can still recognize that it's AI due to stylistic choices.

Not all examples they gave were like this. The example they gave of the word "Typography" would have fooled me as human-made. The infographics stood out though. I would have immediately noticed that the String of Turtles infographic was AI generated because of the stylistic choices. Same for the guide on how to make chai. I would be "suspicious" of the example they gave of the weather forecast but wouldn't immediately flag at as AI generated.

Similar note, earlier I was able to tell if something was AI generated right off the bat by noticing that it had a "Deviant Art" quality to it. My immediate guess is that certain sources of training data are over-represented.

Reminds me of the old gem of the Web 1.0 internet that was Exit Mundi

One of my most frustrating things regarding the potential of an AI bubble was some very smart and intelligent researcher being incredibly bullish on AI on Twitter because if you extrapolate graphs measuring AI's ability to complete long-duration tasks (https://metr.org/blog/2025-03-19-measuring-ai-ability-to-com...) or other benchmarks then by 2026 or 2027 then you've basically invented AGI.

I'm going to take his statements at face value and assume that he really does have faith in his own predictions and isn't trying to fleece us.

My gripe with this statement is that this prediction is based on proxies for capability that aren't particularly reliable. To elaborate, the latest frontier models score something like 65% on SWE-bench, but I don't think they're as capable as a human that also scored 65%. That isn't to say that they're incapable, but just that they aren't as capable as an equivalent human. I think there's a very real chance that a model absolutely crushes the SWE-bench benchmark but still isn't quite ready to function as an independent software engineering agent.

So a lot of this bullishness basically hinges on the idea that if you extrapolate some line on a graph into the future, then by next year or the year after all white-collar work can be automated. Terrifying as that is, this all hinges on the idea that these graphs, these benchmarks, are good proxies.

And if they aren't, oh wow.

I definitely agree with you there. I contracted with a company that had some older engineers who were in largely managerial roles who really liked using AI for personal projects, and honestly, I kind of get it. Their work flow was basically prompt, get results, prompt again with modifications, rinse and repeat, it's low effort and has a nice REPL-like loop. Paraphrasing a bit, but it basically re-kindled the joy of programming for them.

Haven't gotten the chance to ask, but I imagine managing a team of AI agents would feel a little too much like their day job, and consequently, suck the fun out of it.

That said, looking back, I think the reason why generative AI is so fun for so many coders is because programming has become unnecessarily complex. I have to admit, programming nowadays for me feels like a bit of a slog at times because of the sheer effort it can sometimes take to implement the simplest things. Doesn't have to be that way, but I think LLM copy-paste machines are probably the wrong direction.

I think people underestimate the degree to which fun matters when it comes to productivity. If something isn’t fun then I’ll likely put it off. A 15 minute task can become hours, maybe days long, because I’m going to procrastinate on doing it.

If managing a bunch of AI agents is a very un-fun way to spend time, then I don’t think it’s the future. If the new way of doing this is more work and more tedium, then why the hell have we collectively decided this is the new way to work when historically the approach has been to automate and abstract tedium so we can focus on what matters?

The people selling you the future of work don’t necessarily know better than you.

Yeah, I thought about that after I looked at the SWE-bench results. It doesn't make sense that the SWE results are barely an improvement yet somehow the model is a more significant improvement when it comes to long tasks. You'd expect a huge gain in one to translate to the other.

Unless the main area of improvement was tools and scaffolding rather than the model itself.

Practically speaking, we’ve observed it maintaining focus for more than 30 hours on complex, multi-step tasks.

Really curious about this since people keep bringing it up on Twitter. They mention it pretty much off-handedly in their press release and doesn't show up at all in their system card. It's only through an article on The Verge that we get more context. Apparently they told it to build a Slack clone and left it unattended for 30 hours, and it built a Slack clone using 11,000 lines of code (https://www.theverge.com/ai-artificial-intelligence/787524/a...)

I have very low expectations around what would happen if you took an LLM and let it run unattended for 30 hours on a task, so I have a lot of questions as to the quality of the output

I used to make Dragonball Z fan sites...

Based

I'm working on a revamp of my personal site. I do a lot of creative coding, most of them are throwaway experiments, so I thought I'd showcase more of them there. Besides that though, I have some "rare pepes" that I've been meaning to put somewhere. What I like about these is that they're highly polished, animated gifs that imitate the sort of "holographic" effect you'd find in rare collector's cards, but at the same time you can't track down who originally made them, they aren't part of some professional's online portfolio. In that sense they feel like a special piece of internet folk art, made by some complete rando.

Nowadays we have Pinterest and the like, but I really like the idea of creating my own little online space for images I like.

It really is crazy how much was lost when Apple killed Flash. Absolutely miss Newgrounds. It's still around of course, I'm reflecting more on the vibes when it was in its heyday. Unbelievable the games people were making with Flash back then and how it spawned the careers of a ton of indie darlings. Also, not Flash at all, but does anyone remember Exit Mundi? Absolute gold.

Honestly, I kind of look back on blogging unfavorably. Before that people made websites to showcase their interests and hobbies, and because of that even the most basic looking websites could have a lot of "color" to them. Then blogging became a thing and people's websites became bland and minimalist. Arguably blogging culture is as responsible for the death of creativity on the internet as much as the constraints of mobile-friendly web design and Apple's aforementioned killing of Flash.

My thoughts as I reconcile my conflicting feelings on this. I think it should be objectively cool that Meta has finally managed to come out with a pair of smart glasses that come incredibly close to being a practical wearable.

The thing is, it's honestly hard to imagine doing anything cool with them. I think this has less to do with hardware limitations and more to do with vendor restrictions.

I think Meta is fundamentally incapable of making anything cool. Hence why they had to partner with Ray-Ban to make these glasses rather than making their own. I think Meta's failure to realize their version of the metaverse had to do with their inability to recognize coolness and taste as much as anything else. I think any and all apps Meta ships with these glasses are cursed to be a mediocre experience.

I think Apple could do a better job but at the end of the day I think the most interesting (not necessarily best) would be ones with the most developer freedom.

My personal favorite from that time was a website builder called "The Grid" which really overhyped on its promises.

It never had a public product, but people in the private beta mentioned that they did have a product, just that it wasn't particularly good. It took forever to make websites, they were often overly formulaic, the code was terrible, etc etc.

10 years later and some of those complaints still ring true

Ooh, fun, a FizzBuzzFeed quiz!

Sure, but if you're trying to get there by training a model on video games then you're likely going to wind up inadvertently creating a video game simulator rather than a physics simulator.

I don't doubt they're trying to create a world simulator model, I just think they're inadvertently creating a video game simulator model.

Also, to drive my point further home, in one of the demos they were operating a jetski during a festival. If the jetski bumps into a small Chinese lantern, it will move the lantern. Impressive. However, when the jetski bumped into some sort of floating structure the structure itself was completely unaffected while the jetski simply stopped moving.

This is a pretty clear example of video game physics at work. In the real world, both the jetski and floating structure would be much more affected by a collision, but in the context of video game physics such an interaction makes sense.

So yeah, it's a video game simulator, not a world simulator.

Genuinely technically impressive, but I have a weird issue with calling these world simulator models. To me, they're video game simulator models.

I've only ever seen demos of these models where things happen from a first-person or 3rd-person perspective, often in the sort of context where you are controlling some sort of playable avatar. I've never seen a demo where they prompted a model to simulate a forest ecology and it simulated the complex interplay of life.

Hence, it feels like a video game simulator, or put another way, a simulator of a simulator of a world model.

Somewhat related, but I’ve been feeling as of late what can best be described as “benchmark fatigue”.

The latest models can score something like 70% on SWE-bench verified and yet it’s difficult to say what tangible impact this has on actual software development. Likewise, they absolutely crush humans at sport programming but are unreliable software engineers on their own.

What does it really mean that an LLM got gold on this year’s IMO? What if it means pretty much nothing at all besides the simple fact that this LLM is very, very good at IMO style problems?

Alright, it does look pretty charming, and I especially like that it's open-source since pretty much anyone buying a domestic robot is likely to be a tinkerer of some sort, but at the same time it reminds me of the Jibo (https://robotsguide.com/robots/jibo).

For those who don't remember (I couldn't remember the name, only the face, had to look hard for it) it was a desktop robot released in 2014 that was hyped pretty hard at the time. It didn't help that the company that launched it was founded by a fairly well-known MIT professor.

And yeah, it was a flop. The $900 price tag wasn't helping things, but neither was the fact that it didn't really do anything that an Alexa couldn't. You bought it solely because you really liked the idea of robots and thought it was cool, not at all for its value around the house.

I'm not gonna dunk on this too hard since it's probably just a fun company side-project, but I might change my tune if they get too high on hype.

Yeah, this is something I find kind of tricky. I definitely believe that AI companies should get permission from rightsholders to train on their works, but actually compensating them for their works seems pointless. To make the royalties worthwhile you'd have to raise the cost per query to an absolutely absurd level

I recall it as less an evolution and more a complete tonal shift the moment o3 was evaluated on ARC-AGI. I remember on Twitter Sam made some dumb post suggesting they had beaten the benchmark internally and Francois calling him out on his vagueposting. Soon as they publicly released the scores, it was like he was all-in on reasoning.

Which I have to admit I was kind of disappointed by.

Personally I think a more effective analogy would be if someone used a textbook and created an online course / curriculum effective enough that colleges stop recommending the purchase of said textbook. It's honestly pretty difficult to imagine a movie having a meaningful impact on the sale of textbooks since they're required for high school / college courses.

So here's the thing, I don't think a textbook author going against a purveyor of online courseware has much of a chance, nor do I think it should have much of a chance, because it probably lacks meaningful proof that their works made a contribution to the creation of the courseware. Would I feel differently if the textbook author could prove in court that a substantial amount of their material contributed to the creation of the courseware, and when I say "prove" I mean they had receipts to prove it? I think that's where things get murky. If you can actually prove that your works made a meaningful contribution to the thing that you're competing against, then maybe you have a point. The tricky part is defining meaningful. An individual author doesn't make a meaningful contribution to the training of an LLM, but a large number of popular and/or prolific numbers can.

You bring up a good point, interpretation of fair use is difficult, but at the end of the day I really don't think we should abolish copyright and IP altogether. I think it's a good thing that creative professionals have some security in knowing that they have legal protections against having to "compete against themselves"

Something missed in arguments such as these is that in measuring fair use there's a consideration of impact on the potential market for a rightsholder's present and future works. In other words, can it be proven that what you are doing is meaningfully depriving the author of future income.

Now, in theory, you learning from an author's works and competing with them in the same market could meaningfully deprive them of income, but it's a very difficult argument to prove.

On the other hand, with AI companies it's an easier argument to make. If Anthropic trained on all of your books (which is somewhat likely if you're a fairly popular author) and you saw a substantial loss of income after the release of one of their better models (presumably because people are just using the LLM to write their own stories rather than buy your stuff), then it's a little bit easier to connect the dots. A company used your works to build a machine that competes with you, which arguably violates the fair use principle.

Gets to the very principle of copyright, which is that you shouldn't have to compete against "yourself" because someone copied you.