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..That is the talk, but not the practice. It is faster to emulate the AI algorithm on a digital processor. Op-amps are good at linear operations, but AI requires non-linear functions, which are more quickly and more accurately emulated by the multiply-accumulate function in a digital processor.The Art of DHT said:
The AI related analog computing (the one I know about) is not exactly the opamp kind, and honestly, I would rather take that as some kind of hybrid or unique solution than 'real' analog.The Art of DHT said:
An analog computer is a type of computing device that uses continuously varying physical quantities, such as electrical or mechanical quantities, to represent and manipulate data. Unlike digital computers, which use binary digits (bits) to represent data, analog computers use physical quantities to directly represent and solve mathematical equations.
An analog computer works by using electrical or mechanical components, such as resistors, capacitors, and gears, to represent and manipulate data. These components are connected in a circuit or system that mimics the mathematical equations being solved. By continuously varying the physical quantities, the analog computer can solve complex mathematical problems in real-time.
Analog computers have several advantages over digital computers, including their ability to solve complex mathematical equations in real-time, their low cost and simplicity, and their ability to handle continuous data. They are also more resistant to external interference and can perform calculations faster than digital computers in certain applications.
Analog computers have several limitations, including their inability to store and process discrete data, their susceptibility to noise and errors, and their limited precision. They also require specialized knowledge and skills to design and operate, making them less accessible than digital computers.
Analog computers have been used in a variety of fields, including engineering, physics, and economics. They have been used to model and solve problems in fluid dynamics, electrical circuits, and control systems. They have also been used for weather forecasting, nuclear physics simulations, and economic forecasting.