Getting started with Self-Supervised Learning
The future of Machine Learning has been hotly contested given the spectacular success of Deep Learning methods such as CNN and RNN in recent years. While CNNs can do amazing things, such as image recognition, and RNNs can generate text, and other advanced NLP methods, such as the Transformer, can achieve marvelous results, all of them have serious limitations when compared to human intelligence. They don't compare very well to humans on tasks such as reasoning, deduction, and comprehension. Also, most notably, they require an enormous amount of well-labeled training data to learn even something as simple as image recognition.
Figure 8.2 – A child learns to classify objects with very few labels
Unsurprisingly, that is not the way humans learn. A child does not need millions of labeled images as input before it can recognize objects. The incredible ability of the human brain to generate its own new labels...
