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Really glad you like it! We've been working hard on it.
by tome 3y ago
Really glad you like it! We've been working hard on it.
- jonplackett 3y agoIs this useful for training as well as running a model. Or is this approach specifically for running an already-trained model faster?
- frozenport 3y agoIn principle, training is basically the same as running inference but iteratively, in practice training would use a different software stack.
- robrenaud 3y agoTraining requires a lot more memory to keep gradients + gradient stats for the optimizer, and needs higher precision weights for the optimization. It's also much more parallelizable. But inference is kind of a subroutine of training.
- tome 3y agoCurrently graphics processors work well for training. Language processors (LPUs) excel at inference.
- lokimedes 3y agoThe speed part or the being swallowed part?
- tome 3y agoThe speed part. We're not interested in being swallowed. The aim is to be bigger than Nvidia in three years :)