Artificial intelligence (AI) is expanding rapidly to the edge. This generalization conceals many more specific advances—many kinds of applications, with different processing and memory requirements, moving to different kinds of platforms.

PIMIC introduced the Clarity™️ NC100, a Deep Neural Network (DNN)-driven Environmental Noise Cancellation (ENC) chip that establishes a new standard for performance and edge AI computational efficiency.

Subi Krishnamurthy is the Founder and CEO of PIMIC, an AI semiconductor company pioneering processing-in-memory (PiM) technology for ultra-low-power AI solutions.

In a new release, PIMIC, a maker of ultra-low-power AI semiconductor technology, unveiled its Clarity NC100, a Deep Neural Network (DNN)-based Environmental Noise Cancellation (ENC) chip.

PIMIC aims to make AI more accessible for everyday applications. The company’s Jetstreme Processing-in-Memory (PIM) architecture enhances AI computing efficiency with low power and compact design.

PIMIC, a new company working on ultra-low-power AI technology, unveiled the Clarity NC100, a Deep Neural Network (DNN)-based Environmental Noise Cancellation (ENC) chip that sets a new benchmark for performance and edge AI compute efficiency.

PIMIC, a new company working on ultra-low-power AI technology, unveiled the Clarity NC100, a Deep Neural Network (DNN)-based Environmental Noise Cancellation (ENC) chip that sets a new benchmark for performance and edge AI compute efficiency.

PIMIC, an AI semiconductor startup, launched to develop advanced AI inferencing silicon for voice-activated edge devices.

AI chip startup PIMIC has taped out ultra-low power keyword spotting and environmental noise cancellation chips based on its Jetstreme AI accelerator IP. The company also has plans to develop silicon for LLMs and high-performance computer vision in the next couple of years.

Congratulations to our CEO Subi Krishnamurthy for being published in prestigious electronics industry publication EDN: Voice of the Engineer. His technical article explains how neural-network inferencing is enabling crucial functionality such as spoken word detection and environmental-noise cancellation in "edge" devices such as microphones and wearables.

Technological advancement responds to market needs and paves the way for new applications in industries such as automotive, Internet of Things (IoT), and electronics, redefining design standards and creating new perspectives for innovation.