and a limited FOV.

Not for movies. Modern VR headsets have around 100°, comfortable movie viewing distances only needs 30-60° (+ a couple degree for head movement). The resolution is a far bigger problems, with VisionPro being the first one that can do about 1080p at 50° FOV. Most other headsets are stuck with 720p or below when they emulate 2D display.

Also VR can effortlessly do 3D movies and Apple is the first to actually offer them out of the box, finding those for other headsets has always been a huge struggle (i.e. piracy or ripping them yourself).

One thing I haven’t yet seen on VisionPro is if it has any form of multiplayer. Watching movies together with other people (VRChat, BigScreen), was one of the more interesting things VR can do, so far VisionPro looks like a single-player device. Outside of video calls, I have seen no indication that it has full avatars or how it behaves when multiple people in the same room wear a VisionPro.

It’s a bit different for MidjourneyV6, previous AI models would create their own original images based on patterns learned from the data. MidjourneyV6 on the other side reproduces the original images to such a degree where they look identical to the originals for the average observer, you have to see them side by side to even spot the differences at all. DALLE3 has that problem as well, but to a much lesser degree.

That means there is something going wrong in the training, e.g. some images end up being duplicated so often in the training data that the AI remembers them completely. Normally that should be reduced or avoided by filtering out duplicate images, but that seems to not be happening or the images slip through due to small changes (e.g. size or crop will be different on different websites).

Note this doesn’t just impact exact duplication, it also impacts remixing, e.g. when you tell it to draw Joker doing some task, you’ll get Joaquin Phoenix’s Arthur Fleck, not some random guy with clown features.

All of this happens with very simple prompts that do not contain all those very specific details.

In AI’s defense: All the examples I have seen so far are from press releases of movie stills. So they naturally end up getting copied all over the place and claiming copyright violation for your own material that you released to be reused by the press wouldn’t fly either. But either way, Midjourney is still misbehaving here and needs to be fixed.

More broadly speaking, I think it would be a good time to move away training those AI almost exclusively on images and start training them on video. Not just to be able to reproduce video, but so that the AI get a more holistic understanding of how the world works. At the moment all its knowledge is based on deliberate photo moments and there are very large gaps in its understanding.

Completely impractical. If something is AI generated, or manipulated with Photoshop or in the darkroom really doesn’t make a difference. AI isn’t special here, photo manipulation is about as old as the photograph itself. It would be much better to spend some effort into signing authentic images,including a whole chain of trust up to the actual camera. Luckily the Content Authenticity Initiative is already working on that.

It’s not about the ads on Google.com, but the ads on the SEO sites themselves, those are also served by Google. Ever heard of DoubleClick? That’s also Google. If Google Search would give you good clean non-commercial sites without ads, they would lose money.

It’s much simpler than that. Google is an ad company, not a search company. SEO spam gives them ad clicks just the same as quality content, if not more so. As long as they don’t became bad enough that everybody switches to the competition, they simply don’t have to care.