As we all know, new advances in Artificial Intelligence are making waves these days, there are rumours that its major reason for Layoffs in industry. Though nothing to fear, its a matter of realignment to explore new ideas of its use.
I have been playing with Machine Learning well before evolution of major frameworks like TensorFlow or PyTorch. Used to work at grass root level doing multidimensional Matrix & its Manipulation, Statistics & Probability.
Strangely during my formative years while learning CS & Algorithms, found the concepts were part of 1860’s Maths books in my library @St. Stephens.
New frameworks & libraries hide all these complexities under the hood & many a times we tend to ignore maths underneath.
However, to be successful, understanding basics will go a long way in this journey. , creating new systems & frameworks by hand helps in long run, builds solid foundation, specially research.
Based on my experiences, it’s Maths makes Machines Learn.
For example in LLMs, interpretation of words based on Vectors a the word tensor in Tensor Flow is matrices and its manipulation..
Numbers (Vectors) help in deciphering interpretation & relationship between words in a sentence, sounds amazing!
Path breaking Transformer Paper in 2017 is all about Maths under hood so is the case with Generative AI , like Diffusion Models & other innovations are basically Mathematics & Probability at play.
All those who want to jump on the new bandwagon, makes sense to brush class XII maths and focus on building blocks Matrices, Calculus, Probability and its Distributions, Statistics. This will makes your journey enjoyable.
You can contact me @ asheesh.mathur@gmail.com for any help and clarifications. I offer trainings and consultancy as well
RafaelEdide
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