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Is Analog Signal Processing the Future of AI?

NUREMBERG, Germany, Mar. 13, 2019 – 

Gene Frantz may have been the visionary for digital signal processing (DSP) back in the 1970s, but now he thinks we need to turn our attention back to analog to tackle the big challenges of artificial intelligence (AI).

Previously a principal technology fellow at Texas Instruments, Frantz is now a professor at Rice University. He is also the co-founder and chief technology officer at at Octavo Systems, a fledgling system-in-package (SiP) company based in Austin, Texas.

Speaking during the launch of Octavo's OSD32MP1 – the company's first SiP based on the newly announced STMicroelectronics STM32MP1 microprocessor – Frantz told EE Times that he believes SiP and analog processing will be the future. He said AI needs a better solution and suggested that we should consider going back to analog signal processing.

"When most people listen to the words 'analog signal processing' they probably think analog computing, but that's not really what I am saying," Frantz said. "If I can take the whole idea of signal processing and do an analog arithmetic logic unit (ALU) or mixed signal ALU, I can increase the performance by orders of magnitude, and at the same time reduce the power dissipation by orders of magnitude. And the only problem with that is that I have an issue with dynamic range, with accuracy and with linearity. Those are major issues. But the question is, if I can give you three or four orders of magnitude of higher performance, and three or four orders of magnitude lower power dissipation at the same time, do you think those three problems can be solved?"

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