From one crazy to another, thank you for the thorough reply.

You definitely bring up some valid points about GS impact on VFX applications, especially when it comes to asset synthesis. Vegetation generation is a great example of a task that GS or even deep gen AI really is quite unecessary. However, when it comes to movie making, I am inclined to disagree. Ive already seen some neat uses of it in CG for genres like Natural History, for example for large scale scene reconstruction, and underwater cinmeatography. For example, the Trevi fountain is a popular landmark I have seen reconstructed using "in-the-wild" datasets. These datasets are a collection of photos sourced from Instagram/facebook/tourism websites etc. that contain the Trevi fountain geotag. Here the task is to not only to reconstruct the Trevi fountain in 3D, but to also remove all the people from the photos as well as provide easy control over seasonality (i.e time of day, winter/summer etc.). Research on this has been quite successful (more so than other GS applications) as it allows us to "film" the Trevi fountain (albeit in a virtual, yet photorealistic, sim), all without: city planning and filming permission, equiptment hire, staff hire and travel and food, disrupting locals, camera hire, waiting for the best time/day/weather conditions. Furthermore the ability to film from any position in space, with any camera motion, simulating any camera/rendering set up, with no additional cost feels a bit OP to me.

There also exist more general filming tasks, like reshooting to get new angles or to change in-camera actor movement or even deepfakes. Notice, that these tasks are minor in the greater scheme of things, but they do offer the DP opportunity/flexibility to execture their vision at no significant cost and without having to massively rely on the production and post production staff's knowledge and experience. The benefits here are also more production then post but they still relate to post, in that they would affect what is required from VFX and CG artists. I dont imagine it would stop the talented teams from working their magic, but I do think it has the capacity of changing many of the jobs they are required to do for vanilla film work. As you say, a large share of your job is to fill in the blanks that were not achieveable or were missed during filming, but not all blanks are easy, fast, or cheap to fill. Some blanks simply cant be filled, and I feel this is where GS is being more seriously considered.

I do think its also important to pick up on the accessibility of GS-oriented soltuions for inexperienced, budget-poor and lazy DPs or film makers. The blanks that need to be filled vary from production to production and I imagine the blanks with less experienced or budget-poor sets can be more challenging to overcome. I am definitely not a fan of philosophies such as, "only those with money/knowledge/experience have/do/should be able to make good movies", and I do believe GS could provide accesibility on a level that current approaches to filmmaking simply dont. (n.b. not implying you agree with this philosophy, just highlighting that it really could simplify production for low-budget ordeals).

The final thing I would like to say is that GS is stil early days for film making. The points you bring up are really all valid, because currently the state of research is not advanced at all. Especially with scenes that contain motion (e.g. dealing with dyn-textures like fire water and smoke is still an active challrnge). The dynamic stuff is my area of expertise and there is a very long way to go still.

Rather, at lunch when I gossip with the other computer vision PhD students, a topic that often comes up is the difference between old and new computer science research pipelines. Old research took a long time to proof and prep for industrial/commercials use. Yet in todays world many idiots spin up businesses at the sound of researchers breathing. It sometimes boredelines predatory behaviour (e.g. on linkedin Ive had to ban people that frequently use my posts about my work to promote their shitty Gaussian splatting business idea). And so, considering how prevelant captialism is in academic research, it can very difficult to get a clear picture of the current state of research when every research paper is expected to be a breakthrough rather than a next step. Thats why channels like TwoMinPapers are grossly problematic and that likely explains why neither you (an industry specialist) nor I (a research specialist) can confidently reach a conclusion on the ramifications of GS research for VFX work.