Hacker News Reader

You certainly won't want to train on a DSP, but running them shouldn't be too much.

I too have nothing but great things to say about TI.

Would it be plausible to train slowly on a DSP, if the data is also being collected slowly, at the edge?

By the time you have a reasonable dataset, you've also had a reasonable amount of training... of course, with only a little training on the complete dataset.

Depends on your model - in the majority of cases training is a separate act from using the model, and just because you trained it doesn't mean it's well fitted. You end up caring about training speed because you don't know how many training runs you may have to do, grumpily fiddling with the model and hyperparameters after each training session trying to get a good model. Technically possible but probably not practical

Reply on news.ycombinator.com