Tester Architecture for Era of AI and Big Data
The broad application of Machine Learning and AI techniques to the real world problems of speech recognition, image recognition, industrial automation and autonomous navigation has accelerated the demand for more computing horsepower and introduced novel architectures. In turn, this demand has pushed the semiconductor industry to deliver new new process technology even faster than historical Moore's Law trends. These devices, in both cloud and mobile applications are placing new demands on automated test equipment. ATE must be rethought to align to the emerging requirements for devices that will exceed 100B transistors within a few years. This presentation will discuss these trends and changes needed in tester architecture so test does not become a roadblock to deploying the most advanced semiconductor technologies for AI applications.