What is AI and Why Should We Learn It?

Unless you’ve been living under a rock, you probably have heard of the term “AI” and “Machine Learning”. Just as the name suggests Artificial Intelligence is any technology that mimics human intelligence. That being said, AI is a very, very broad term. Under AI, there is machine learning (ML), which quite literally means techniques, or machines, that can learn from data to better mimic human intelligence. Now, just as us humans learn from data with our brain, a subset of ML is Deep Learning (DL), which uses neural networks inspired from our brains. We could continue more, but let’s save that for later since this is a brief introduction.

AI has been studied, and will continue to develop. In October 2015, a legendary match between an AI model AlphaGo developed by DeepMind and one of the greatest Go player Lee Sedol was conducted. During the game, AlphaGo demonstrated its creativity through numerous moves including Move 37. Ultimately, AlphaGo won the game with 4-1 victory. More information can be found in AlphaGo.

Despite the long history, the modern AI boom in the public occurred from late 2022 when OpenAI released its GPT-3.5. Nevertheless, LLMs have significantly transformed the lives of countless people. For instance, as the concept of “vibe coding” emerged, the concept of “coding” became more accessible to the public. Moreover, job markets are transforming with the rise of AI. Now despite all “AI bubbles” concerns and anti-AI movements, it is somewhat self-evident that AI and the concept of AGI (Artificial General Intelligence) will not suddenly disappear in near future. Then, the real question is “do you want to become a consumer or producer?”

To briefly share why I began studying ML, the reason is quite simple. As a student who wishes to advance as a quantitative researcher, not learning ML is just not in the option. Moreover, learning to develop AI will widen the future opportunities even if I decided different path than quantitative finance. Although the ideas on an AI model developing another model is rising, it is imperative that a human engineer must superintend the architecture and development. Finally, it is fun to learn. I mean what is more intriguing than to learn about your favorite tool and how to contribute to its development?