The field of AI has undergone a revolution over the last decade, driven by the success of deep learning techniques. This post aims to convey three ideas using a series of illustrative examples:

There have been huge jumps in the capabilities of AIs over the last decade, to the point where it’s becoming hard to specify tasks that AIs can’t do.
This progress has been primarily driven by scaling up a handful of relatively simple algorithms (rather than by developing a more principled or scientific understanding of deep learning).
Very few people predicted that progress would be anywhere near this fast; but many of those who did also predict that we might face existential risk from AGI in the coming decades.

I’ll focus on four domains: vision, games, language-based tasks, and science. The first two have more limited real-world applications, but provide particularly graphic and intuitive examples of the pace of progress.

Original article:
https://medium.com/@richardcngo/visualizing-the-deep-learning-revolution-722098eb9c5

Author:
Richard Ngo

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