I'm not sure how prominently something like neural texture compression will feature in these conversations?!
Nvidia's history of multiple proven incidents of false advertising and releasing half-baked features that required significant refinement before they became useful or have their serious problems solved makes planning to use neural texture compression or any other promised Nvidia feature in real games moot until the feature is demonstrated and proven useful. Nvidia has often been innovative, but has often failed to fully develop its ideas before releasing them in a ready-to-use state.
Examples of false advertising from Nvidia include asynchronous compute support in Maxwell (though I believe that this was an accidental case because Nvidia did make a genuine try at asynchronous compute in Maxwell, but did not include enough scheduling hardware to allow the feature to work as intended), the GTX 970 having only 3.5 GB of usable VRAM when Nvidia advertised the GTX 970 with 4 GB of VRAM (technically true, but the last 512 MB was practically unusable due to the way a GTX 970 was die harvested so it is practically false), and the RTX 5070 having the same performance as the RTX 4090 (proven blatantly false because frame generation worsens frame latency because it depends on AI generating and displaying frames in between the rendered frames, forcing the rendered frames to be held back until the generated frames have been displayed).
Examples of features that were half-baked and required refinment included Nvidia's implementation of asynchronous compute, ray tracing, and DLSS. Asynchronous compute was one thing that AMD invented that Nvidia had to copy in a hurry since asynchronous compute created a big speedup in AMD's GPUs in Direct3D 12 by helping the GPU maximize utilization. As seen above, Nvidia made a try at it in Maxwell and completely failed due to inadequate hardware. Nvidia did disclose that it tried to make it work in Maxwell by using its then-usual software driver wizardry when its driver quality was unquestionably good, but found out that it did not have good enough hardware to make it work and speed things up. Instead, things slowed down. Nvidia added more scheduling hardware and made it work in Pascal and later GPUs. Later, Nvidia disclosed several security vulnerabilities in Maxwell, Pascal, and Turing involving microcontrollers in those GPUs as seen in
https://nvidia.custhelp.com/app/answers/detail/a_id/5263 . I suspect that these microcontrollers are meant to manage asynchronous compute in those GPUs and that later GPU generations starting with Ampere fixed the hardware security vulnerabilities. Ray tracing in the RTX 20 series was half-baked, too slow, and inefficient to be of much use in games, and games that used it got slammed for poor performance. Ray tracing in the RTX 30 series became useful in games if used judiciously. RTX 40 refined it further, improving its speed, allowing it to enhance scenes further. There are scenes that are truly impossible to properly render in real time without ray tracing. DLSS 1.0 got all sorts of negative press due to being half-baked garbage that required AI training for each game, requiring DLSS 2.0 before people accepted DLSS. Newer versions of DLSS improved image quality. Newer versions of DLSS introduced frame generation which can be useful in games that are not too sensitive to latency but is worse than useless in latency-sensitive games such as esports like
Street Fighter 6,
Tekken 8,
Counter-Strike 2, or
Valorant. Some features and versions of DLSS require newer hardware to run.
If neural texture compression works better than most GPUs' native texture compression hardware and does not make most GPUs lag from using AI hardware in novel ways that it was not originally designed for, that would be great except for those who own GPUs without AI hardware that is good and flexible enough to be repurposed towards neural rendering. However, like other new features that Nvidia is promoting, game developers should not plan to depend on it until experiments show that it is much better than dedicated texture compression hardware algorithms that are already baked into today's GPUs to make neural texture compression worth the effort, storage costs, and memory to add them and the required fallback paths for GPUs that can't or shouldn't use neural texture compression.
I don't think way overkill VRAM helps a card in longevity. Sufficient - the word describes itself - is just that. Sufficient. The fact an odd game is coded and ported like absolute shit does not make a case for a different kind of GPU. In fact, it explicitly makes a case for such a product to NOT exist, because if they do and become mainstream, devs have no reason to not port and code like absolute shit. That's basically the counter point to
@Dr. Dro 's argument about having the hardware on tap for a poorly coded game. There are limits to this. And we should guard them - because what developers love to do in our space, is pass part of the burden of 'work' to the end user.
No longer do we pre-cook the lighting, no, let's do it on the fly, so you get to pay for it instead of the developers' time. This is why RT is lauded as an improvement on their end. Not having to do work, and passing the bill on to you, us. A balance must be struck here, as clearly, heavily expanded hardware requirements aren't exactly helping anyone either. Look at the mess that is UE5 performance - it backfires on those same devs too.
First, some kinds of effects are only able to be done with ray tracing. There is no way for developers to pre-cook every possible scenario without blowing your storage to infinity. However, such ray tracing effects need to be judiciously used to where they are truly needed.
Second, there are some well-optimized Unreal Engine 5 games.
Tekken 8 is a very well-optimized Unreal Engine 5 game in terms of graphics. To be fair, its initial Season 2 patch has totally wrecked the game balance to make it way too overly offensive without sufficient defensive options, and the developers are trying to fix that balance mess and tone down the offense. Those who ship badly optimized Unreal Engine 5 games have more work to do.
Third, I would rather splurge now on a GPU that can last me a while rather than buy a GPU whose VRAM buffers have low margins from the get-go especially when a console transition is predicted to be relatively soon, which will be the start of games using more VRAM, forcing me to change my GPU and risk more damage to my motherboard due to changing the GPU. I already destroyed one motherboard when trying to remove a GPU from the motherboard because Corsair made a bone-headed design error in one of its cases to have some sort of non-screw pin in the motherboard's central motherboard stand-off hole that Corsair elevated so that a standard stand-off wouldn't fit. Combine that with the fact about multi-purpose monitors and TVs being 4K, and 8 GB is either barely sufficient or not sufficient anymore as seen in
https://www.techspot.com/review/2856-how-much-vram-pc-gaming/ even if low settings are used. At better than console settings, 12 GB or 16 GB is pushing it or barely insufficient to hold everything without swapping even if you are counting only memory that is actually filled with content. If you asked me at the beginning of the PlayStation 5 and Xbox Series S | X lifetimes, I could see 8 GB VRAM being sufficient. That does not feel true anymore with a console transition being predicted to be soon. This is why I am excited for the new AMD GPU.
I can see this rumored GPU being a backup plan in case UDNA fails graphics performance tests in the lab versus RDNA 4. At least it should have sufficient VRAM to last if UDNA needs much more time in development or fails in the lab and has to be sent back to the drawing board. AMD doesn't need another Bulldozer with no backup plan.
I'm not sure how prominently something like neural texture compression will feature in these conversations?!
I just found this video of neural texture compression in action on an RTX 4090. Neural texture compression can really cut VRAM usage, but also causes a big hit to the frame rate.
Neural texture compression has a very impressive compression ratio, but will require more experimentation to see which GPUs have good enough AI hardware to use this without too much of a performance hit.