Electronic Products & Technology

Putting the AI into Chip Processing

EP&T Magazine   

Podcast Electronics Semiconductors AI architectures chip Editor Pick processors semiconductor Untether

Chris Walker, CEO, Untether AI

Podcast Guest

Chris Walker, CEO, Untether AI


Podcast Description

In this podcast episode, Chris provides some insights on this Toronto-based artificial intelligence semiconductor start-up. The firm is currently developing a powerful new AI chip that eliminates the data movement bottleneck that costs energy and performance in traditional architectures. While elaborating on the real-world applications of Untether AI’s technology, Chris explains how his firm’s energy-efficient chip design translates into tangible benefits for designers. He also touches on the role Untether plays in shaping the future of AI-driven electronic devices, and how he anticipates the industry evolving in the coming years.

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Guest Bio

Chris Walker is an innovative and growth-driven semiconductor executive, having led major initiatives and business units throughout his 30-year career at Intel Corp. His expertise extends across operations, finance, business development/M&A, product, and marketing leadership. Recently, he has been a senior advisor with Cerberus Capital, supporting investments in technology fund and management consulting.

What is Untether AI?

Untether AI, a Toronto-based semiconductor firm that specializes in developing high-performance AI processors for various applications, particularly focused on deep learning and neural network tasks.

These processors deliver exceptional performance while minimizing power consumption, making them suitable for deployment in edge computing devices, data centres and other AI-driven systems. Untether AI’s technology often involves innovative approaches to parallel processing and memory management, enabling efficient execution of complex AI algorithms. Overall, the start-up firm aims to push the boundaries of AI hardware acceleration, facilitating faster and more energy-efficient computation for a wide range of applications.