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Maybe related: LLM can actually learn the world map from texts https://medium.com/@fleszarjacek/large-language-models-repre...


Glad to see that Adobe is still investing on the alias-free convolutions (as in StyleGAN3), and this time they know how to fill the lost high frequency features

I always thought that alias-free convolutions can produce much more natural videos


When can we have a PDF reader where we can hover over a symbol and see its definition?


What kind of symbol?



If natural language can't exactly describe what you want, just generate more variations and let Monte Carlo sampling cover the way you want


Should I perhaps feed the results back to some generative method and genetic algorithm supported by decision support and crossanalyze the optimal choices too instead of simply making what I need? Too simple right, wallow in the plethora of tools to fascinate the world with my full technological skills and sophistication at once is much better, right?! : )


Humans have been known for successfully using tools to complete their tasks in a more comfortable and efficient manner for quite some time now, even at the cost of introducing additional complexity. So if the results seem promising and the increased cognitive load isn't too much to bear, then the answer is perhaps yes? If not, then fortunately no one is forcing you to use AI tooling! Just make it :)


Shameless plug: We're building a dataset of visual novels for AI training https://huggingface.co/Synthia/ChatGalRWKV

Visual novels are multimedia data with thorough plain-text annotations, and generative AI will greatly accelerate their development


I've had the idea for a long time but never managed to try it: Alias-free convolutions (like StyleGAN3) may help with temporal cohesion.

The StyleGAN3 project page shows some good videos: https://nvlabs.github.io/stylegan3/


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