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I. Executive Summary Real-Time Operating Systems (RTOS) are foundational for developing reliable embedded applications across diverse industries. Unlike general-purpose operating systems, an RTOS is specifically engineered to guarantee deterministic behavior, Read More …
I. Executive Summary RISC-V, an open standard Instruction Set Architecture (ISA), is fundamentally reshaping the semiconductor industry by offering a royalty-free, modular, and extensible alternative to traditional proprietary ISAs such Read More …
Executive Summary This report examines the pivotal role of automation, Adversarial AI (AAI), and Command and Control (C2) frameworks in modern red teaming operations. It highlights how these advanced capabilities Read More …
Executive Summary This report details the architecture, integration, and operation of a state-of-the-art Internal Developer Platform (IDP) built from three cornerstone Cloud Native Computing Foundation (CNCF) projects: Backstage, ArgoCD, and Read More …
I. Executive Summary Parameter-Efficient Fine-Tuning (PEFT) has emerged as a transformative paradigm in the era of large-scale Artificial Intelligence (AI) models, particularly Large Language Models (LLMs) and Foundation Models (FMs). Read More …
I. Introduction to Multimodal AI Defining Multimodal AI: Beyond Unimodal Systems Multimodal Artificial Intelligence represents a significant advancement in the field, characterized by its ability to process and integrate diverse Read More …
Part 1: The Foundations of Agentic AI The rapid evolution of artificial intelligence has reached a pivotal inflection point. The paradigm is shifting from passive, reactive models to proactive, goal-oriented Read More …
I. Executive Summary Hypersonic flight, defined as atmospheric travel at speeds greater than Mach 5, represents a frontier in aerospace engineering characterized by extreme physical phenomena and multidisciplinary complexities.1 This Read More …
Introduction Gradient Descent is one of the most fundamental optimization algorithms in machine learning and deep learning. It is used to minimize a cost (or loss) function by iteratively moving Read More …
Feature Engineering Techniques: Encoding, Scaling, and PCA Feature engineering is a critical preprocessing step in machine learning that transforms raw data into a more effective set of inputs for algorithms[1]. Read More …