In case anyone has a fuzzy memory, back during peak NFT hype grifters would take art made by other artists and attempt to tokenize it as NFTs without the consent of the original artist, or otherwise possibly copy said artist's work and make a collection of it.

It was disgusting and parasitic then and it's disgusting and parasitic now.

They may be some of the smartest people in the industry but they're clearly too incompetent and/or negligent to be allowed to develop more intelligent AI. This is ridiculous.

Do you think that this package manager could potentially be a problem? Do you think it might be worthwhile to host the software packages themselves on an internal, sandboxed network, just to be extra certain? Or would you dismiss this as a needless precaution?

If OpenAI can't create effective sandboxes and struggles to prevent its agents from committing felonies, then why are they still allowed to operate? Why are the employees who are responsible for these lapses in AI security still employed?

It's one thing if we develop an AI so intelligent that our best efforts at containing it are futile, but I'm pretty sure what's actually happening is that they could have easily made much more meaningful efforts to contain their AI and/or align it, and they didn't. I think this is a case of negligence and incompetence when it comes to safety and security, and we've entrusted these incompetent and negligent people with developing frontier AI.

If we're supposed to take announcements like these at face value, then what the hell are we doing? We wouldn't trust a bunch of incompetent and negligent engineers to build bridges or nuclear power plants or planes (well...not so sure about that last one), so why are we letting people who are demonstrably negligent and incompetent when it comes to safety and security build the thing they assure us could cause massive damage if not properly controlled/aligned?

EDIT: sorry guys, wrote this up pretty quickly, at least you know from my typos that I actually wrote this.

And, you know, maybe also some funny business. I think it's good to be a little suspicious of a model that happens to shoot upwards in performance on a specific benchmark while also kind of keeping up with the pack on a bunch of other benchmarks.

From experience I can say that it seems like a lot more common sense to simply replace the front wheel of your bike with a wheel containing an electric motor, rather than attaching whatever Asus is selling to your bike.

Anyway, the actual theory is that Google and Meta have fallen behind because they've been playing by this playbook of focusing on scale and training data, whereas OpenAI and Anthropic have done so well because they are likely doing much more interesting things to improve their models over time. It makes sense when you realize that one of Google's key strengths, besides talent, is that they have an incredible amount of data they can use for training due to being both the world's leading search engine as well as having all that video data from YouTube. Scaling the training data makes more sense to them than it does to Anthropic and OpenAI, who are both relatively data-disadvantaged.

You can kind of see this when you look at the Gemini 3 scorecard when it came out (https://blog.google/products-and-platforms/products/gemini/g...) and notice that while it wasn't as good as Claude And GPT at coding, it scored higher on a bunch of other non-coding benchmarks, and I think the reason why is simply because of Google's data advantage.

If true, I feel even more vindicated for believing that the "scale is all we need" narrative was bullshit.

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

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.

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.

This is most evident in the way things collide.

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.