Not sure why they put so much investment into videoSlop and imageSlop. Anthropic seems to be more focused at least.
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.
Will they really be able to replicate the quality while spending significantly less in compute investment? If not then the moat is still how much capital you can acquire for burning on training?
Been saying this since the 2016 Alice case. Apple jumped into content production in 2017. They saw the long term value of copyright interests.
https://arstechnica.com/information-technology/2017/08/apple...
Alice changed things such that code monkeys algorithms were not patentable (except in some narrow cases where true runtime novelty can be established.) Since the transformers paper, the potential of self authoring content was obvious to those who can afford to think about things rather than hustle all day.
Apple wants to sell AI in an aluminum box while VCs need to prop up data center agrarianism; they need people to believe their server farms are essential.
Not an Apple fanboy but in this case, am rooting for their "your hardware, your model" aspirations.
Altman, Thiel, the VC model of make the serfs tend their server fields, their control of foundation models, is a gross feeling. It comes with the most religious like sense of fealty to political hierarchy and social structure that only exists as hallucination in the dying generations. The 50+ year old crowd cannot generationally churn fast enough.
But really, so has everyone else. There's two "races" for AI - creating models, and finding a consumer use case for them. Apple just isn't competing in creating models similar to the likes of OpenAI or Google. They also haven't really done much with using AI technology to deliver 'revolutionary' general purpose user-facing features using LLMs, but neither has anyone else beyond chat bots.
I'm not convinced ChatGPT as a consumer product can sustain current valuations, and everyone is still clamouring to find another way to present this tech to consumers.
Good lord, expressing that kind of sentiment does not make for a useful and engaging conversation here on hacker news.
Plus moving all that data about is expensive. Keeping things in the datacenter is means its faster and easier to secure.
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
Normal people are already getting tired of AI Slop
Going viral as a billion dollar company spending upward of 1T is still not sustainable. You can't pay off a trillion dollars on "engagement". The entire advertising industry is "only" worth 1T as is: https://www.investors.com/news/advertising-industry-to-hit-1...
And there's something else about the diminishing returns of going viral... AI kind of breaks the usual assumptions in software: that building it is the hard part and that scaling is basically free. In that sense, AI looks more like regular commodities or physical products, in that you can't just Ctrl-C/Ctrl-V: resources are O(N) on the number of users, not O(log N) like regular software.
(The obvious well-paying market would be erotic / furry / porn, but it's too toxic to publicly touch, at least in the US.)
As for photo/video very large number of people use it for friends and family (turn photo into creative/funny video, change photo, etc.).
Also I would think photoshop-like features are coming more and more in chatgpt and alike. For example, “take my poorly-lit photo and make it look professional and suitable for linkedin profile”
Even if developers are 1:1000 of your users, I'm going to guess that ratio shifts a lot when you look at subscribers.
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.
I think you are confusing generation with analysis. As far I am aware your model does not need to be good at generating images to be able to decode an image.
Now there are all sorts of tricks to get the output of this to be good, and maybe they shouldn't be spending time and resources on this. But the core capability is shared.
I think that hasn't been the case since DeepDream?
I think it's important to OpenAI to support as many use-cases as possible. Right now, the experience that most people have with ChatGPT is through small revenue individual accounts. Individual subscriptions with individual needs, but modest budgets.
The bigger money is in enterprise and corporate accounts. To land these accounts, OpenAI will need to provide coverage across as many use-cases as they can so that they can operate as a one-stop AI provider. If a company needs to use OpenAI for chat, Anthropic for coding, and Google for video, what's the point? If Google's chat and coding is "good enough" and you need to have video generation, then that company is going to go with Google for everything. For the end-game I think OpenAI is playing for, they will need to be competitive in all modalities of AI.
An AI!
The specialist vs generalist debate is still open. And for complex problems, sure, having a model that runs on a small galaxy may be worth it. But for most tasks, a fleet of tailor-made smaller models being called on by an agent seems like a solidly-precedented (albeit not singularity-triggering) bet.
> But for most tasks, a fleet of tailor-made smaller models being called on by an agent seems like a solidly-precedented (albeit not singularity-triggering) bet.
intuitively it sounds akin to the unix model...
> you just prompt engineer a bit and it often magically works
i just get the feeling reproducibility, performance and cost will start to become more and more important as time goes on... jmo tho
It'll just end up spreading itself too thin and be second or third best at everything.
The 500lb gorilla in the room is Google. They have endless money and maybe even more importantly they have endless hardware. OpenAI are going to have an increasingly hard time competing with them.
That Gemini 3 is crushing it right now isn't the problem. It's Gemini 4 or 5 that will likely leave them in the dust for the general use case, meanwhile specialist models will eat what remains of their lunch.
The entertainment industry is by far the easiest way to tap into global discretionary income.
[1] https://arxiv.org/pdf/2509.20328
[2] https://deepmind.google/blog/genie-3-a-new-frontier-for-worl...
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.