Moore's Lobby Podcast

Pragmatic Semi is Breaking the Rules and Bending Silicon Electronics

Episode #74 / 57:58 / March 26, 2024 by Daniel Bogdanoff
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Episode Sponsor: Avnet Abacus

Pragmatic Semiconductor’s Founder and Executive Director joins us to discuss their thin-film, low-cost alternative to traditional silicon manufacturing and their aim to disrupt applications from smart labeling to IoT sensors and fingerprint sensors.

While Moore’s Law scaling has driven incredible advancements in computing, AI, and smartphones, many applications don’t need or benefit from the most advanced semiconductor nodes. From its inception, Pragmatic Semiconductor’s goal has been to take a…well, pragmatic…approach to develop an ultra low-cost, fast cycle time alternative to traditional silicon processing. Oh, and did we mention that the resulting chips and wafers are also flexible?

 

Thin-film silicon wafers and chips are thin and flexible. Image used courtesy of Pragmatic

 

You will definitely want to check out this Moore’s Lobby conversation between White and our host, Daniel Bogdanoff, as they dive into:

  • The technology and manufacturing of thin-film silicon
  • Europe’s largest-ever VC funding for a semiconductor company
  • The potential advantages of flexible silicon for building a more robust supply chain
  • White’s top priorities for improving the flexible silicon ecosystem

 

A Big Thank You to Our Sponsors! 

 

Meet Scott White

Pragmatic Semiconductor is Scott White’s sixth technology venture. Since founding the company nearly 15 years ago, Scott has led the development of a novel silicon thin-film technology and its associated manufacturing capabilities. Today, he is often focused on fundraising and leading new strategic initiatives.

 

 

Scott’s previous companies were in the fields of telecommunications, photonics, and machine learning. He has received a number of honors, including being named Deep Tech Entrepreneur of the Year in the 2022 Enterprise Awards and a Lifetime Fellow of the Bessemer Society in 2023. 

Scott has a 1st class degree in Pure and Applied Mathematics and Information Technology from the University of Western Australia, where he studied neural networks and syntactic machine learning. He has over 50 patents and has lived and worked in Australia, Japan, Singapore, Indonesia, the US, and the UK.