Blueprint to understand recent advances in natural language technology in a hands-on manner. Topics covered include transformers, language models (BERT, GPT-2), evaluation benchmarks, and conversational interfaces/chatbots.
In early June 2020, I decided to learn about the current state of NLP and correspondingly, role of (narrow) AI. My usual approach to understanding a topic is bottom-up. Understand the fundamentals thoroughly before starting out with a project. Constrained by time and inspired by a pedagogy promoted by the likes of Fast AI, I decided to go project-first instead.
Musings about inspiration, its importance for technological progress and a call for action to inspire those around you.
It had been less than a week since I had entered college. I was standing in front of a crowded computer lab full of starry-eyed freshers. A senior (final-year student) drew a curve on the blackboard. It was either a parabola or a line. Truth is I don’t really remember. Over the next 30 minutes, I listened to the senior to explain how computer science is deeply intertwined with maths. I was surprised to learn that even those not from a computer science program could benefit from learning to code.