Read this article by F Chollet about the future of Deep Learning and its possibl

Read this article by F Chollet about the future of Deep Learning and its possible directions, enumerated below:The Future of Deep Learning II – F Chollet.pdfhttps://blog.keras.io/the-future-of-deep-learning.html (Links to an external site.)Models closer to general-purpose computer programs, built on top of far richer primitives than our current differentiable layers—this is how we will get to reasoning and abstraction, the fundamental weakness of current models.New forms of learning that make the above possible—allowing models to move away from just differentiable transforms.Models that require less involvement from human engineers—it shouldn’t be your job to tune knobs endlessly.Greater, systematic reuse of previously learned features and architectures; meta-learning systems based on reusable and modular program subroutines.1. In your own experience, how far do you think the industry and the research community is from getting there?2. Are you familiar with AutoML tools? If you are, can you name, comment or suggest one AutoML tool and its benefits?
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