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6/ there are so many things you can do with it." Yes. Exactly. It's a tool. The vast majority of us using it aren't parading it around calling it one step from AGI. We know better esp after dealing with it the realities of daily trial/error/nudging of hyperparameters, etc.
7/ Those who are overselling deep learning seem to be those who write books/articles that need views, or do PR, or are trying to sell snake oil. Yes that's bad. But creating drama out of thin air is just a waste of time and emotion (lots of Twitter fights over this lately!).
I think you know, things are maybe a little less ideal than how you've painted them. First, on hitting a wall on compute. Many results have depended on a large investment in compute to be achievable: top pretrained LMs, stylegan, RL game bots etc. Unless something changes, andpic.twitter.com/CoHcIVwlUE
barring some hardware innovation, this dependence on compute will result in a stall for topend performance. In Warstadt et al, it's interesting to find their tasks did not find a meaningful separation between TransformerXL & LSTMs. It was GPT2 with much more training data whatpic.twitter.com/RjV5S2unJk
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