Machine Learning (ML) has become a buzzword in the tech industry and beyond. Its applications range from recommendation systems to self-driving cars, and it’s revolutionizing the way we live and work. However, mastering ML can be a daunting task due to its complexity and the vast array of algorithms and...
In the realm of artificial intelligence, SHRDLU stands as a pioneering example of early attempts to imbue machines with natural language understanding and reasoning capabilities. Developed by Terry Winograd in the late 1960s and early 1970s at the Massachusetts Institute of Technology (MIT), SHRDLU marked a significant milestone in the...
Have you ever heard of an object defying gravity and levitating above a magnetic surface without any visible means of support? Welcome to the mind-bending phenomenon known as “quantum locking.” 🪄🔮 Quantum locking, also referred to as the “Meissner effect,” is a captivating manifestation of quantum physics that seems like...
The discriminator in Generative Adversarial Networks (GANs) has a crucial role, acting as a classifier to distinguish between genuine and fabricated samples. A perfect discriminator assigns a probability of 1 to true samples and 0 to fake ones. However, this ideal scenario can lead to a challenging problem known as...
When embarking on your research journey, a crucial step lies in presenting a comprehensive understanding of your subject area and the existing body of knowledge in your chosen field. The key to achieving this lies in crafting an effective literature review, serving multiple purposes that significantly shape the trajectory of...
In this study, researchers delved into the relationship between artificial intelligence and fake news, examining whether it serves as a friend or foe in such campaigns. Specifically, they focused on the influence of large language models in shaping the fake news phenomenon. To conduct their analysis, scientists curated an explicitly...
I have published my paper “Comparison of Optimisation Methods for The Knapsack Problem: Steepest Ascent Hill Climbing vs. Simulated Annealing” on ResearchGate. The paper explores the application of optimization algorithms, specifically Hill Climbing and Simulated Annealing, to solve the knapsack problem. The knapsack problem is a well-known combinatorial optimization problem...
In 1952, British physiologists Alan Hodgkin and Andrew Huxley conducted groundbreaking research on the electrical properties of neurons by simulating their model of the squid giant axon. This work laid the foundation for understanding how action potentials, or electrical impulses, are generated and propagated along nerve cells. The squid giant...
Introduction Artificial Intelligence (AI) optimizers play a crucial role in training and fine-tuning machine learning models. These optimization algorithms are designed to improve model performance, enhance convergence, and efficiently use computational resources. In this article, we will delve into the world of AI optimizers, exploring their importance, popular types, and...
Introduction In the realm of robotics, where precision and rigid structures have long dominated, a new wave of innovation is emerging: soft robotics. Inspired by the flexibility and adaptability of biological systems, soft robots are revolutionizing the field by offering a safer and more versatile approach to human-robot interaction. This...
