❤️ Check out Lambda here and sign up for their GPU Cloud: https://lambdalabs.com/papers📝 The paper "GraphCast: Learning skillful medium-range global weather...
interesting, I already had read, that lambda was used and was at least partially more effective than classical models. Question is how it will fare when the data it was trained on becomes less relevant as weather patterns change in the future due to climate change.
It is to be seen experimentally I guess. But from what I understood, I don’t really think this would be that big of an issue due to two factors:
Climate change has been quite predictable in the past few decades. Therefore, assuming that it is trained on data from the past few decades, wouldn’t it know how to anticipate it?
In the beginning, it is kinda seen to be doing cloth sims which use physics. Here, it seems to know which calculations to prioritize and which to approximate. This results in an approximation of a physics sim while using a fraction of the resources. The most computationally expensive part of the weather models seem to be the fluid sims. The AI here seems to be able to essentially come up with a very efficient fluid sim model. I can’t see how climate change can affect the physics of fluid sims and stuff. Only factors like temperature distribution and stuff would change, no?
Again, I don’t really know as I’m not a meteorologist nor an expert in how this thing works (although I would like to be hehe).
interesting, I already had read, that lambda was used and was at least partially more effective than classical models. Question is how it will fare when the data it was trained on becomes less relevant as weather patterns change in the future due to climate change.
It is to be seen experimentally I guess. But from what I understood, I don’t really think this would be that big of an issue due to two factors:
Again, I don’t really know as I’m not a meteorologist nor an expert in how this thing works (although I would like to be hehe).