In the video they mention that the "heavy geometry" you are talking about is 100s of billions of triangles. Storing 1 billion triangles using 32-bit floats takes ~12 Gb, so we are talking about N * 12 Tbs only in triangle storage for this demo. Building an acceleration data-structure on top of this would also take up a lot of storage, so I don't think how you can make this approach successful on a PS5 with limited GPU memory.

To me this tech sounds more like they finally figured out all the quirks around how to properly construct "seamless geometry atlasses" (geometry images) and reconstruct geometry from them, and managed to bring that to production. It required quite a bit of compute, and there were also a lot of quirks about how to automatically "cut" an input geometry so that you can put it in a 2D image, how to compress and decompress the image or parts of it without artifacts (such that you don't get jumps across triangles), etc.

That approach doesn't store any triangles, but a 2D xyz (rgb) image that you can use to reconstruct the original geometry from, and to which you can apply all usual image compression algorithms, use all GPU texture features (but for geometry), etc.

That's ~15 year old tech, and they mention they have been working on this for over 10 years, so timeline-wise it would fit (search for geometry images, texture atlasses, etc. there was a siggraph talk from ~2005 about wavelet compression of geometry images).