Theoretically, there are various applications for one-shot learning, but only recently has it started being used in real-world scenarios. Recent advancements have been made using one-shot learning, such as writing SQL codes, improving deformed medical images, and running signature verification. There are several other domains that are still under research. Companies such as OpenAI, Google, Microsoft, and Amazon are investing heavily in AI research. Solving one-shot learning would mean creating a mechanical brain with the abilities of a human. This advancement could save lives in a number of ways: it could pave the way for rare-disease detection, solve the global food crisis, or optimize supply-chain models.
In this book, we have explored a few of the possible approaches to one-shot learning. If you wish to explore more, please refer to the Further reading section...
