Before we begin, Ordinary Analysis is totally free, and I’m happy to share it with you. If you want to receive every new post in your mailbox, you can subscribe by clicking on this cool button below.
Thermodynamics was one of the few subjects I genuinely enjoyed during my bachelor’s degree. In this field, we learned about two distinct types of functions used to describe a system’s properties: point functions and path functions.
To illustrate their essence, consider the process of booking a cab. If it’s a pre-paid or app-based cab, the fare for your trip is known before you even step into the vehicle. In most cases, it won’t change unless you take a significant detour. The fare is based solely on the start and end points of your journey, for a given time of the day. In this scenario, the trip fare behaves like a point function.
Now, imagine a trip where the fare is determined by the “meter.” Here, the start and end points aren’t the only governing factors. Many other elements, such as the trip’s duration and distance, will affect the pricing. These variables depend on the path you follow. In this case, the fare behaves like a path function.
Living alone for nearly two years has led me to discover the joy of cooking. I’ve grown fond of the entire process, and I’ve realized that I prefer cooking dishes that follow the characteristics of a point function rather than a path function.
For instance, I enjoy cooking Chicken Biryani (or Chicken Pulao, if you will) and Chicken Curry. Both dishes follow the characteristics of a point function. It doesn’t matter much when you add the spices, onions, or water. As long as the quantities are approximately correct, the dish will turn out tasty! Even if you forget to add something (like ginger-garlic paste, which happens to me often), it will still be quite delicious!
However, this point function method can’t be applied when brewing coffee. For almost a year, I’ve been using a French press to brew my coffee, a process that strongly follows the path function method. You have to be very careful about how much water you’re pouring, how much coffee you’re adding, and how long you’re brewing. I closely measure the water quantity and brewing time. While I don’t measure the amount of coffee powder and the water temperature as closely, trial and error have given me a pretty good idea of what and how much I need.
Interestingly, these point and path function characteristics are also prevalent in various job postings, especially those related to Data Science. Jobs that closely follow the point function characteristics tend to emphasize knowing the right algorithm, math, and stats behind it. In contrast, jobs that follow the path function characteristics generally emphasize more on knowing a particular tool (like Power BI) or language (like Python).
In my opinion, the number of point function jobs will significantly increase in a few years. With the advent of Generative Pretrained Transformers (GPT) and Large Language Models (LLMs), the value of path function jobs may diminish.
Did this blend of Biryani, Coffee, and Data Science perk you up? Don’t keep it to yourself! Share this post and let’s brew some conversations.
Hungry for more servings of thermodynamics, cooking, and data science? Subscribe now and never miss a post!