woctordho

8 ms·

121.
by woctordho 2y ago
There're already games fully using SDF rendering, such as Dreams [0]. It even made a SIGGRAPH talk [1]. [0] https://en.wikipedia.org/wiki/Dreams_(video_game) [1] https://www.youtube.com/watch?v=u9K
122.
by woctordho 2y ago
Every ordinary Chinese needs to self-learn some cybersecurity to do daily things, like to watch YouTube, or to send messages to others without worrying being censored
123.
by woctordho 2y ago
Everyone working with shell scripts should know shellcheck
124.
by woctordho 2y ago
The lazy clone in HVM may be a viable approach to mutation
125.
by woctordho 2y ago
FYI there is some publicly available Chinese alignment dataset https://github.com/whitzard-ai/jade-db
126.
by woctordho 2y ago
Maybe related: LLM can actually learn the world map from texts https://medium.com/@fleszarjacek/large-language-models-repre...
127.
by woctordho 2y ago
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 vid
128.
by woctordho 3y ago
When can we have a PDF reader where we can hover over a symbol and see its definition?
129.
by woctordho 3y ago
https://github.com/learning-at-home/hivemind is also relevant
130.
by woctordho 3y ago
If natural language can't exactly describe what you want, just generate more variations and let Monte Carlo sampling cover the way you want
131.
by woctordho 3y ago
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 g
132.
by woctordho 3y ago
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/styleg