Chapter 1: PyTorch Lightning Adventure
Welcome to the world of PyTorch Lightning!!
We are witnessing what is popularly referred to as the Fourth Industrial Revolution, driven by Artificial Intelligence (AI). Since the creation of the steam engine some 350 years ago, which set humanity on the path to industrialization we saw another two industrial revolutions. We saw electricity bringing a sea change roughly 100 years ago, followed by the digital age some 50 years later revolutionizing the way we live our lives today. There is an equally transformative power in AI. Everything that we know about the world is changing fast and will continue to change at a pace that no one imagined before and certainly no one planned for. We are seeing transformational changes in how we contact customer services, with the advent of AI-powered chatbots; in how we watch movies/videos, with AI recommending what we should watch; in how we shop, using algorithms optimized for supply chains; in how cars are driven, using self-driving technology; in how new drugs are developed, by applying AI to complex problems such as protein folding; in how medical diagnoses are being carried out, by finding hidden patterns in massive amounts of data. Underpinning each of the preceding technologies is the power of AI. The impact of AI on our world is more than just the technology that we use; rather, it is much more transformational in terms of how we interact with society, how we work, and how we live. As many have said, AI is the new electricity, powering the engine of the 21st century.
And this monumental impact of AI on our lives and psyche is the result of a recent breakthrough in the field of Deep Learning (DL). It had long been the dream of scientists to create something that mimics the brain. The brain is a fascinating natural evolutionary phenomenon. A human brain has more Synapses than stars in the universe, and it is those neural connections that make us intelligent and allow us to do things such as think, analyze, recognize objects, reason with logic, and describe our understanding. While Artificial Neural Networks (ANNs) do not really work in the same way as biological neurons, they do serve as inspiration.
In the evolution of species, the earliest creatures were unicellular (such as amoeba), first appearing around 4 billion years ago, followed by small multi-cellular species that navigated blindly with no sense of direction for about 3.5 billion years. When everyone around you is blind, the first species that developed vision had a significant advantage over all other species by becoming the most intelligent species, and in evolutionary biology, this step (which happened some 500 million years ago) is known as the Cambrian explosion. This single event led to remarkable growth in the evolution of species, resulting in everything that we currently see on earth today. In other words, though Earth is about 4.5 billion years old, all the complex forms of life, including human brains, evolved in just the last 500 million years (which is in just 10% of Earth's lifetime), led by that single evolutionary event, which in turn led to the ability of organisms to "see" things.
In fact in humans as much 1/3 of our brain is linked to visual cortex; which is far more than any other senses. Perhaps explaining how our brain evolved to be most intelligence by first mastering "vision" ability.
With DL models of image recognition, we can finally make machines "see" things (Fei Fei Li has described this as the Cambrian explosion of Machine Learning (ML)), an event that will put AI on a different trajectory altogether, where one day it may really be comparable to human intelligence.
In 2012, a DL model achieved near-human accuracy in image recognition, and since then, numerous frameworks have been created to make it easy for data scientists to train complex models. Creating Feature Engineering (FE) steps, complex transformations, training feedback loops, and optimization requires a lot of manual coding. Frameworks help to abstract certain modules and make coding easier as well standardized. PyTorch Lightning is not just the newest framework, but it is also arguably the best framework that strikes the perfect balance between the right levels of abstraction and power to perform complex research. It is an ideal framework for a beginner in DL, as well as for professional data scientists looking to productionalize a model. In this chapter, we will see why that is the case and how we can harness the power of PyTorch Lightning to build impactful AI applications quickly and easily.
In this chapter, we will cover the following topics:
- What makes PyTorch Lightning so special?
<pip install>—My Lightning adventure- Understanding the key components of PyTorch Lightning
- Crafting AI applications using PyTorch Lightning