Because almost everyone involved in AI race grew up in "winner takes it all" environments, typical for software, and they try really hard to make it reality. This means your model should do everything to just take 90% of market share, or at least 90% of specific niche.

The problem is, they can't find the moat, despite searching very hard, whatever you bake into your AI, your competitors will be able to replicate in few months. This is why OpenAI is striking deal with Disney, because copyright provides such moat.

OpenAI is (was?) extremely good at making things that go viral. The successful ones for sure boost subscriber count meaningfully

Studio Ghibli, Sora app. Go viral, juice numbers then turn the knobs down on copyrighted material. Atlas I believe was a less successful than they would've hoped for.

And because of too frequent version bumps that are sometimes released as an answer to Google's launch, rather than a meaningful improvement - I believe they're also having harder time going viral that way

Overall OpenAI throws stuff at the wall and see what sticks. Most of it doesn't and gets (semi) abandoned. But some of it does and it makes for better consumer product than Gemini

It seems to have worked well so far, though I'm sceptical it will be enough for long

Because as with the internet 99% of the usage won’t be for education, work, personal development, what have you. It will be for effing kitten videos and memes.

Because OpenAI stands for AI leader.

If Gemini can create or edit an image, chatgpt needs to be able to do this too. Who wants to copy&paste prompts between ai agents?

Also if you want to have more semantics, you add image, video and audio to your model. It gets smarter because of it.

OpenAI is also relevant bigger than antropic and is known as a generic 'helper'. Antropic probably saw the benefits of being more focused on developer which allows it to succeed longer in the game for the amount of money they have.

Because the general idea here is that image and video models, when scaled way up, can generalize like text models did[1], and eventually be treated as "world models"[2]; models that can accurately model real world processes. These "world models" then could be used to train embodied agents with RL in an scalable way[3]. The video-slop and image-slop generators is just a way to take advantage of the current research in world models to get more out of it.

[1] https://arxiv.org/pdf/2509.20328

[2] https://deepmind.google/blog/genie-3-a-new-frontier-for-worl...

[3] https://arxiv.org/pdf/2509.24527

Because there is only so much programmers and companies will pay for AI coders. The big prizes is AI-generated TikTok.

The entertainment industry is by far the easiest way to tap into global discretionary income.

I get the allure of the hypothetical future of video slop. Imagine if you could ask the AI to redo lord of the rings but with magneto instead of gandalf. Imagine watching shawshank redemption but in the end we get a "hot fuzz" twist where andy fights everyone. Imagine a dirty harry style police movie but where the protagonist is a xenomorph which is only barely acknowledged.

You could imagine an entirely new cultural engine where entire genres are born off of random reddit "hey have you guys every considered" comments.

However, the practical reality seems to be that you get tick toc style shorts that cost a bunch to create and have a dubious grasp on causality that have to compete with actual tick toc, a platform that has its endless content produced for free.

When they released their first good image model is when they got a new 100 million users in a week.

Because for all the incessant whining about "slop," multimodal AI i/o is incredibly useful. Being able to take a photo of a home repair issue, have it diagnosed, and return a diagram showing you what to do with it is great, and it's the same algos that power the slop. "Sorry, you'll have to go to Gemini for that use case, people got mad about memes on the internet" is not really a good way for them to be a mass consumer company.

Because those and world models are the endgame, way way more than text is.

The fact that they do this isn't very bullish for them achieving whatever they define as AGI.

Because their main use is for advertising/propaganda, which is largely videoSlop & imageSlop even without AI.

But how much more profitable are they? We see revenue but not profits / spending. Anthropic seems to be growing faster than OpenAI did but that could be the benefit of post-GPT hype.

because these are mostly the same players of the 2010's. So when they can't get more investor money and the hard problems are still being cracked, the easiest fallback is the same social media slop they used to become successful 10-15 years prior. Falling back on old ways to maximize engagement and grind out (eventually) ad revenue.