Powered by Artificial Intelligence

“Machine Intelligence is the last invention that humanity will ever need to make.” Let us dig deeper into this vast topic of machine learning.

On the 7th of November, 2022, the STEM CLUB of The Bishop’s Co – Ed School gathered in the biology lab to discuss a topic that will greatly excite all physics and techno geeks – Machine Learning. The presentation, which was delivered by our Head of Technology Akshaj Kashyap, explained Machine Learning as a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. This concept works on the basis of ETP which is simply explained as: A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P.

Several exciting recent developments like self-driving cars and virtual gaming bots have kindled the curiosity in this area even more, while several applications and implementations of machine learning like, recommendation systems used by Netflix and Amazon, Google Translate, Voice-Assistants like Siri, Alexa and The Google Assistant are already making our day-to-day lives way more convenient than they used to be a few years back.

Akshaj then went on to talk about how artificial intelligence is changing lives, business and nations across the world.

Scientists all around the world are trying to make computers which will work like a machine, but think like a human. The students were then educated on how machine learning has become a part of human anatomy as well where three-dimensional (3D) reconstruction and modelling of the human body and garments from images is a challenge, but possible.

A unique concept of supervised learning was learnt by the students. Supervised learning refers to a category of methods in which we teach or train a machine learning algorithm using data, while guiding the algorithm model with labels associated with the data. One practical example of supervised learning problems is predicting house prices. How is this achieved? We need data about the houses: square footage, number of rooms, features, whether a house has a garden or not, and so on.

The children discussed the use of machine learning in image recognition, speech recognition, banking and personal finance and much more. The session wrapped up with Akshaj asking all aspiring programmers to research into this topic deeply, with everyone secretly praying we have a machine to do our homework some day!

“Predicting the future isn’t magic, it’s artificial intelligence.” - Dave Waters