So they need to be able to do image generation, for which they need image data. They also need to be able to analyze videos for more and better training data like learning or teaching there models from yt and other sources.
So they have image generation, image dataset and video dataset. Its not far fetched ata ll or desperate to leverage this base for playing around with video generation.
And despite how much money they burn, for a company that size, trying out video generation wasn't that high of a goal post.
I'm really surprised by there move and can only imagine that the progress of other models from google and antrophic pulls their teeth and no longer want to invest the compute (not money) to leverage their compute for their main models.
Nano Banana created a lot of noise.
But the reasoning of Gemini 3.1 Pro is really really good. Its hard to describe how good it became. I do not see the same quality from openai. Openai though is also super fast in response. A lot faster than just a few month ago.
For example: some german guy used the wrong word in describing an advantage of having a silencer and missuesd a word. Openai just said its nonsense, gemini suggested that its a typo and he wanted to write something else (gemini was correct).
It could also be that we are in a moat between "why is AGI not here yet" and "we need to build now the agentic platform stuff, that takes time".
Gemini pro is def slower than openai and I do not know if its because I use the pro version of gemini but not from openai. But it could also be that OpenAI has to work on subagents because Gemini def uses subagents and i was not able to find a source that OpenAI is doing this too.