Shastra is a personal space for sharing and learning about artificial intelligence, computer systems, algorithms, and emerging digital technologies. This site reflects an ongoing process of independent study and long-term thinking about the future of computing.
Artificial Intelligence (AI) refers to the study and development of systems capable of performing tasks that typically require human intelligence, such as perception, reasoning, learning, and decision making. Modern AI systems often rely on statistical models, large-scale data, and computational optimization.
Machine Learning is a subfield of AI that focuses on enabling systems to learn patterns from data rather than being explicitly programmed. Key paradigms include supervised learning for prediction, unsupervised learning for structure discovery, and reinforcement learning for sequential decision processes.
Computer Systems form the foundation of all intelligent applications. Topics such as operating systems, concurrency, networking, and hardware–software interaction determine how efficiently AI models can be trained, deployed, and scaled.
Algorithms and Data Structures remain central to computing. Efficient algorithms reduce computational cost, while appropriate data structures enable scalable processing of large datasets commonly used in AI and data-driven systems.
This website is maintained as a personal learning log. The content emphasizes conceptual clarity, technical foundations, and long-term understanding rather than short-term trends. Notes, summaries, and reflections are written to support continuous learning in artificial intelligence and computer technology.