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Math is the DNA of AI and yet students are losing interest- why?
By: Er Umair Ul Umar
In childhood we love math because it’s introduced in a fun, playful way counting games, patterns, and simple puzzles. It feels like a discovery process, However, as we grow older, math becomes abstract and complex requiring more effort, memorization and problem solving. Contrastingly, Mathematics is the backbone of AI, enabling algorithms to process data, learn from patterns, and make intelligent decisions. Without mathematical foundations, AI would not be able to perform tasks like image recognition, speech synthesis, or autonomous driving.
In summary, mathematics provides the theoretical foundation and practical tools necessary for the development, optimization, and application of Machine Learning and AI technologies. It enables the creation of models that can learn from data, make predictions, and solve complex problems across various domains.
Mathematics plays a fundamental role in the development and functioning of Artificial Intelligence (AI). Here are some key areas where mathematics is crucial:
Linear Algebra which we study in 10th Class is used in neural networks, deep learning, and computer vision. Linear algebra is essential for operations like matrix multiplication, eigenvalues, and eigenvectors (studied in Engineering Mathematics), which are used in algorithms like Principal Component Analysis (PCA) and Singular Value Decomposition (SVD). Concepts which we study in 11th class like matrices, vectors, and tensors are essential for operations in AI models. Example: Google’s TensorFlow framework uses tensors (multi-dimensional arrays) extensively. AI models, especially in machine learning, often deal with large datasets represented as vectors and matrices.
Mathematical Analysis also known as Calculus which we study in 11th and 12th Classes helps in optimizing AI models, particularly in training neural networks. Gradient Descent, a key optimization method, relies on differentiation. Example: Backpropagation in deep learning uses partial derivatives to update weights. Calculus is used to optimize AI models.........
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