Research Article

Scientific models make prediction possible by selecting which features of a system to represent. Their usefulness depends on the question, the operating conditions, and the consequences of error. Measurement introduces a further layer: instruments and procedures connect model quantities to observations, with uncertainty that must be understood. Validation examines whether the available evidence supports using the model for its stated purpose. This article connects a classical pendulum approximation, modern robotics experiments, and the limits of detailed prediction to a practical discipline for research, education,…

Summary Applied physics and theoretical physics have different immediate purposes, but they do not advance independently. Theoretical work proposes general relationships; applied work tests, realizes, and extends physical knowledge under material constraints. Between them lie mathematical models, experiments, instruments, computation, engineering, and repeated revision. A useful framework is Theory -> Model -> Measurement -> System -> Revised theory. Historical cases such as thermodynamics and electromagnetism, and modern cases such as gravitational-wave astronomy and Physical AI, show that the cycle may begin with a practical…

Introduction Artificial intelligence in education is often discussed through generative tools: writing assistants, tutors, image generators, learning analytics, and automated feedback. This is Digital AI operating mainly through information. A second development is equally important. Physical AI connects computation to sensors, actuators, machines, and material environments. It may take the form of a robot, autonomous instrument, intelligent laboratory platform, or adaptive cyber-physical system. The two categories overlap and are not a hierarchy. Digital systems can create serious real-world consequences, while a moving robot may…

Physical AI is a systems problem Physical AI couples computation to bodies and environments. Its outputs may become motion, contact force, heat, resource consumption, and risk. Prediction accuracy therefore cannot be the only design criterion. A robot must act within equations of motion, geometric and contact constraints, uncertain measurements, closed-loop stability requirements, and finite energy. Mathematical physics supplies the language for connecting these requirements. It does not replace robotics engineering or machine learning. It makes their assumptions explicit and provides models that can be…

Introduction Artificial intelligence is often described through computational performance: what a model can classify, predict, generate, or recommend. When AI is connected to sensors and actuators, however, its outputs can change the physical world. The relevant questions then expand from informational accuracy to motion, stability, energy, timing, environmental interaction, safety, and recovery. This article uses digital AI and physical AI as a practical systems distinction. It is not a claim that the categories are universal, mutually exclusive, or hierarchical. Digital components are frequently embedded…

Introduction Intelligent systems are frequently evaluated by what they can recognize, predict, or generate. For systems that interact with the physical world, however, computational performance is only one layer of the problem. A robot, autonomous instrument, or AI-enabled laboratory platform must also operate under motion, contact, energy, timing, sensing, and safety constraints. Mathematical physics contributes a disciplined way to connect these constraints. It translates physical principles into mathematical models; links models to observable quantities; represents uncertainty; and establishes tests by which system behavior can…

Abstract As the lyrics said, “now, the end is near”. The last sunrise of 2025 has risen, and as the final sunset approaches, we reflect on a year of extraordinary scientific innovation and human experience. This article narrates the story of 2025 in a Nature-style review, mixing scientific breakthroughs with personal and philosophical insights in the exploratory tone of Dr. Albert Tan Lie Sing. 2025 was a year in which logic, imagination, and creativity merged into single contexts – from artificial intelligence designing new…