Let's not do this again, please - blog article on Sora and OpenAI

[BootinUp]

But let’s take a breath here, and look at what’s actually happening — both in terms of the technology itself, and in terms of the wider context in which this announcement is taking place.

First, as the Alex Kantrowitz reported today, OpenAI’s flagship product, ChatGPT, is stagnating. Thats the conclusion of a SimilarWeb report that found that web traffic for the once-world-beating tool has declined in five out of the eight last months; it’s down 11% from its May 2023 high.

Meanwhile, OpenAI is desperately searching for a revenue model to support the energy- and compute-intensive business. As of last year, it cost well over a million dollars a day to run its servers, and that cost has almost certainly risen as it trains its models for video products like Sora, and will rise further still if it continues to expand.

If we accept OpenAI’s promotional narrative and get swept up in Sora, if we tremble at the forbidding power of its reality-distorting abilities, we make it much, much easier for the company to cash in on its still-proliferating mythologies.

https://www.bloodinthemachine.com/p/lets-not-do-this-again-please

[highplainsdem]

1. Thanks for posting this! OpenAI CEO Sam Altman was getting so carried away by his own hype

the other day that he even tweeted something about changing his fundraising goal to 8 instead of 7 trillion dollars, as if Sora was automatically worth another trillion or more (and his Twitter fans were urging him to go higher).

Interesting blog post. I'd also noticed Nick St. Pierre'a Twitter thread about how similar Sora's responses were to Midjourney's when given the same prompts.

I've mentioned before on DU that people getting AI to generate anything for them have no way of knowing how many other people might be getting similar or even identical results from that AI, anywhere that AI is used. The AI doesn't save and make any of those results exclusive to any users. And now it's obvious that the same is true with AI models from different companies, if their training datasets have similarities.

[BootinUp]

2. Glad to nt