At MHTECHIN, we strive to develop AI systems that not only excel in performance but also offer insights into the underlying data. Eigenvectors and eigenvalues, fundamental concepts in linear algebra, provide a powerful framework for understanding the core structure and dynamics of data, aligning perfectly with our philosophy of data-driven insights. Core Concepts Eigenvectors:…

At MHTECHIN, we believe in developing AI systems that can effectively extract meaningful insights from complex, high-dimensional data. Matrix factorization techniques play a crucial role in achieving this goal by decomposing large matrices into smaller, more manageable components, revealing underlying patterns and latent factors. Core Concepts User-Item Matrix: In many applications, data can be…

At MHTECHIN, we believe in developing AI systems that are not only intelligent but also robust and adaptable to uncertainty. Bayesian Inference provides a powerful framework for achieving this by explicitly incorporating prior knowledge and updating beliefs in the face of new evidence. This approach aligns perfectly with our philosophy of building AI systems…

Information Theory, a field pioneered by Claude Shannon, provides a powerful mathematical framework for quantifying information, data compression, and communication. In the realm of Machine Learning (ML), these concepts offer invaluable insights into model design, feature selection, and performance evaluation. This article explores the key concepts of Information Theory and their applications within the…

Markov Chains, a mathematical concept rooted in probability theory, have found significant applications in the field of robotics. These chains provide a framework for modeling systems that evolve over time in a probabilistic manner, making them invaluable for tasks such as motion planning, decision-making, and control.   Understanding Markov Chains At its core, a…

Liquid State Machines (LSMs) are an exciting concept in the world of Machine Learning, inspired by the dynamics of spiking neural networks. Unlike traditional ML models, LSMs mimic the fluidity and adaptability of biological neural systems, making them particularly effective for temporal and sequential data analysis. Key features of Liquid State Machines include: At…

Introduction Humanoid robotics is a specialized field within robotics that focuses on creating robots that resemble humans in both appearance and behavior. These robots are designed to perform tasks that require human-like interactions and movements, making them suitable for a variety of applications, from customer service to healthcare. At MHTECHIN, we are at the…

Introduction Actuator control systems are fundamental in robotics and automation, enabling the movement and manipulation of robotic components. These systems are responsible for converting energy into mechanical motion, which allows robots to interact with their environment and perform tasks. At MHTECHIN, we specialize in developing advanced actuator control systems that are integral to the…

Introduction In robotics, perception and navigation in complex environments are critical. To achieve this, robots need to leverage advanced sensor technologies that can provide detailed and reliable environmental data. One of the most powerful tools for this purpose is LiDAR (Light Detection and Ranging). LiDAR uses laser light to map the surroundings with high…

Introduction In the realm of robotics, the ability to accurately perceive and navigate complex environments is paramount. One of the most advanced technologies enabling this capability is LiDAR (Light Detection and Ranging). Combined with sensor fusion techniques, LiDAR can provide precise 3D environmental mapping, helping robots better understand their surroundings and make informed decisions.…