We get to learn the foibles and language of Claude and ChatGPT as a result. The slop is almost detectable if you provide no steering prompts about story structure, narrative structure, or stylistic cues. And most writers are not finetuning the weights to their LLMs explicitly.

If you invest time into doing all that (not really trivial stuff), the results will be better.

Never quite got around to polishing it to the desired level (due to having kids), and Star Wars Squadrons ended up coming out before I even released the game.

I believe the XWA revamp project also has a VR mode

If Anthropic and OpenAI makes their own inference hardware, this is a shot across the bow for making their business worthless.

Expect the next NEMOTRON to top the AI performance indices.

I remember when Tesla was building its own inference chips, and after about 2 years and billions spent, the whole effort was scuttled b/c they simply could not keep up with the iteration and R&D cycles of dedicated chip companies. I suspect the same will be the case with OpenAI vs Cerebras + Nvidia/Groq

There are other types of models like diffusion models right now that are showing more efficiency and have a higher ceiling for improvement. Understanding math and fundamentals are more important.

I suspect the answer to that is probably nuanced. Spacetime probably gets more VC funding based on the DB rather than being a game. Trying to make a successful indie MMORPG without pre-existing IP is going to be an uphill battle in 2026 with or without fancy backend innovations.

The model of putting ECS like logic as code and putting all that code as stored procs solves a handful of db transaction issues that none of the major mmorpgs really had issues with 20 years ago when mmorpgs were all the rage and when computers were 100x-1000x slower than today. A lot of engineering is going to solving and cutting out these database round trips that were not even an issue 20 years ago and even less of an issue today.

On the other hand the actual hard parts about building a multiplayer game, such as roll back, physics, collisions, all of that sort of stuff, well this actually doesn't really help with any of that. If anything it makes all of those things even more difficult. I imagine that the developers of this game probably had to come up with some pretty interesting hacks that probably didn't benefit from their DB to get anything resembling physics to work.

Layered on top of that are the known anti-patterns around using stored procs within databases, which spacetimedb does't address at all. You can't really run your tests just on your client because the application logic is split between client and db-server leading to spaghetti code and poor iteration cycles for game design. The database itself also doesn't horizontally scale beyond a single node.

Just take a peek at the steam reviews for BitCraft. The recent ones are actually pretty scathing and it seems like, despite all this engineering, the developers haven't really listened to their playerbase. With all of this effort centered around building a custom database, users still can't, say, build homes for themselves in this game, something that you can certainly do in probably most all other MMORPGs.

I think this will go down as a cautionary example of not listening to your users and spending engineering effort on the wrong types of problems. I think one of the most important skills for an engineer is actually not just having good technical ideas but knowing the right types of problems to solve and, most importantly, listening to your audience, your users, and your stakeholders. I wish the developers the best of luck and hope they can pivot successfully.

Simply predicting the surface of the data you are trying to generate is far more representationally efficient, and perhaps in the next few months we'll see a version of that for LLMs

The inference cost must be extremely high compared to diffusion based approaches. I wonder if this would ever be useful for more organic sculpting type workflows. E.g. for organic non-hard surface models, use a diffusion model for generation, and leverage this LLM codegen and tool call approach for retopology and cleanup.

Stack on top of that the fact that diffusion based models like the ones made by Inception Labs are far faster and more efficient than autoregressive LLMs and have an even higher ceiling of optimization (single step path prediction via model distillation versus 50 step denoise is currently an active area for image diffusion)

The human brain is soon neither going to be more powerful nor energy efficient than the stuff we use to run AI.

A really, really well designed engine is just going to be a library of highly modular components with a nice editor or two thrown in.

As the old adage goes "Build libraries not frameworks"

The idea that the layer above your own is trivial to build (e.g. biology is just chemistry, or chemistry is just applied physics)

At some point I built a little 2d game engine, but the same amount of time would have been better served actually building a game in Unity. Eventually I solo developed a full 3d VR app for the MetaQuest.

Virtually all the dominos have fallen except good topology at the moment, and unfortunately that's the biggest domino there is.

AI videogen and image gen will hollow out a lot of 3d work that isn't explicitly gaming oriented IMO, and eventually even that work may go away once better World-Action-Models come online.

Honestly more of a reinforcement learning AI problem than a generative AI problem IMO