Engineering and Technology

An analog-AI chip for energy-efficient speech recognition and transcription

S. Ambrogio, P. Narayanan, et al.

Discover how a groundbreaking analog-AI chip with 35 million phase-change memory devices achieves remarkable energy efficiency, boasting performance levels up to 12.4 TOPS/W. This technology not only ensures software-equivalent accuracy for keyword spotting but also approaches it for more extensive models, demonstrating significant potential for the future of speech recognition and transcription—all developed by S. Ambrogio, P. Narayanan, A. Okazaki, and their esteemed colleagues at IBM Research.