It's good to be wary of hype, but this comment seems overly down on where we are by focusing on AI today doing 'curve fitting' ; sure, supervised learning is at

It's good to be wary of hype, but this comment seems overly down on where we are by focusing on AI today doing 'curve fitting' ; sure, supervised learning is at it's core that, but when it achieves things like image captioning or super accurate translation calling it just curve fitting is reductionist and downplays how powerful these techniques are. Furthermore, the notion that neural networks can only be used as part of supervised learning (and in particular with backpropagation) is totally off. Just to cite a few examples: http://proceedings.mlr.press/v48/taylor16.pdf http://proceedings.mlr.press/v48/taylor16.pdf https://arxiv.org/pdf/1908.01580v1.pdf https://arxiv.org/pdf/1908.01580v1.pdf And, well, all of deep RL and unsupervised learning is not 'curve fitting'. So yes, even if your 'model' (and really this should be 'objective' or 'loss', the neural net is the model, but whatever) neural nets can indeed help you. Though it's true they can't magically start doing super complicated things like app development yet ; the whole point is to understand how to use them and build hybrid systems that play to neural nets' strengths (as with eg self driving systems).