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Just about every electronic contraption you care to think of contains at least one printed circuit board (PCB), which serves to house and connect the various components that allow the device to ...
Electromagnetic field solvers (or sometimes just field solvers) are specialized programs that solve (a subset of) Maxwell's equations directly. They form a part of the field of electronic design automation, or EDA, and are commonly used in the design of integrated circuits and printed circuit boards. They are used when a solution from first ...
AI researchers have created many tools to solve the most difficult problems in computer science. Many of their inventions have been adopted by mainstream computer science and are no longer considered AI. All of the following were originally developed in AI laboratories: [375] Time sharing; Interactive interpreters
Physics-informed neural networks for solving Navier–Stokes equations. Physics-informed neural networks (PINNs), [1] also referred to as Theory-Trained Neural Networks (TTNs), [2] are a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process, and can be described by partial differential equations (PDEs).
AI already powers technology that allows phone batteries to last longer, improves movie and song recommendations, and enables more effective maps and translation.
Boolean logic expressions are delay-less functions that are used to provide efficient logic signal processing in an analog environment. These two modeling techniques use SPICE to solve a problem while the third method, digital primitives, uses mixed mode capability. Each of these methods has its merits and target applications.
A physicist considers whether artificial intelligence can fix science, regulation, and innovation.
The researchers showed that a feedback circuit with cross-point resistive memories can solve algebraic problems such as systems of linear equations, matrix eigenvectors, and differential equations in just one step. Such an approach improves computational times drastically in comparison with digital algorithms. [60]