Java-Powered AI: Using Code to Implement Intelligent Systems – Systematic Review

Abstract

The combination of Java programming and artificial intelligence (AI) creates a potent synergy that allows developers to design intelligent systems and applications that are scalable, reliable, and efficient. This paper examines how to combine the flexibility of Java with the cognitive powers of AI, offering a range of approaches, tools, and frameworks that make use of Java's advantages for developing AI-driven solutions. An introduction of AI ideas and Java's place in AI development is given at the outset of the paper. It explores basic AI techniques like computer vision, reinforcement learning, machine learning, and natural language processing (NLP), and explains how to implement them in Java using frameworks like Deep learning, Weka, and Apache Open NLP. It also goes over how to use Java to create intelligent agents and how to design expert systems, heuristic-driven algorithms, and autonomous decision-making systems. It emphasizes how Java may be integrated with AI-enabled tools and stresses the significance of feature engineering, model deployment, and data pretreatment. Additionally, the study looks at the difficulties and possibilities in developing AI using Java, addressing issues with interoperability of AI modules, compatibility with a variety of data sources, and performance optimization. The study culminates with a futuristic view of Java-powered artificial intelligence, imagining progressions in Java libraries, frameworks, and techniques that will encourage the development of increasingly complex and intelligent systems.