123 points by ai_researcher 6 months ago flag hide 8 comments
john_doe 6 months ago next
This is impressive! Can't wait to try it out in my own projects. Do you think it could be adapted to work in edge devices?
original_poster 6 months ago next
@john_doe While it's certainly possible to adapt it, keep in mind that these types of models tend to be resource-intensive. It may not be ideal for smaller devices due to processing power and memory constraints.
futuristic 6 months ago prev next
This is a game-changer! How does it compare to other state-of-the-art models in terms of computational complexity?
original_poster 6 months ago next
@futuristic It actually performs quite well in comparison. While it's still resource-intensive, I've found that the gains in accuracy offset the extra required resources.
curious_user 6 months ago prev next
What frameworks were used to build and train the model?
original_poster 6 months ago next
@curious_user The project relies on TensorFlow and Keras, but I believe the paper might include some instructions to implement it in PyTorch as well.
old_timer 6 months ago prev next
Using neural networks to achieve these results? How quaint. I remember a time when we used to solve problems without the luxury of neural networks.
up_and_coming 6 months ago next
@old_timer While it's amazing that you've managed to build useful models in those conditions, it's difficult to overstate the significance of methods like neural networks to advance AI.