Unlock the secrets of AI innovation with our esteemed guest, Jem Davies, non-executive director at Literal Labs. Jem shares his transition from Arm to Literal Labs, revealing how the revolutionary Tsetlin machine sets new benchmarks in efficiency, power usage, and processing speed.

Jem is a highly experienced business leader and technologist having previously served 18 years at Arm. He is an engineer and was an Arm Fellow holding multiple patents on CPU and GPU design. Latterly, Jem's career moved into business management and he became a General Manager first in Arm's Media Processing Groups, then the founding General Manager of their Machine Learning group. In addition to setting future technology roadmaps, he also worked on several acquisitions leading to building new businesses inside Arm, including the Mali GPU (the world's #1-shipping GPU) and Arm's AI processors. Jem left Arm in 2021 and currently is chair of NAG and a non-executive director of Literal Labs, BOW, CamAI, and Cambridge Future Tech.

Explore the crucial role of explainable AI and why it matters more than ever in today's regulated industries like healthcare and finance. Jem discusses Lietral Labs' Tsetlin Machine, which offers an intuitive audit trail of AI decision-making through propositional logic. This approach is breaking new ground by enhancing model efficiency without compromising on performance. We also tackle the challenge of unbiased training data and how tailored levels of explainability can make AI accessible to everyone, from everyday users to industry experts.

As we gaze into the future of AI, we tackle the pressing issues of bias, energy consumption, and the potential impact of quantum computing. Jem provides insight into how Literal Labs is pioneering tools to promote ethical AI development, mitigate biases, and democratize AI innovation. From practical applications like water leak monitoring to the potential for AI to evolve into a tool of unimaginable uses, we reflect on how the intersection of explainability, energy efficiency, and bias shapes a responsible AI future. Join us for an episode that promises to broaden your understanding of AI's profound societal impact.

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Transform your understanding of semiconductor design and testing with the latest episode of Advantest Talks Semi. We are thrilled to introduce our new co-host, Don Ong, and welcome Ron Press, and Marc Hutner, from Siemens as they share groundbreaking insights into Electronic Design Automation (EDA).

Ron Press is the Senior Director for Technology Enablement at Siemens, where he leads a team dedicated to ensuring the successful implementation and use of Siemens' Tessent DFT and test product capabilities. His responsibilities include enabling application engineers, developing reference flows, and supporting customers in utilizing Siemens' released products effectively.

Ron began his career at Raytheon, working on AI and neural networks, and in 1993, he co-authored a paper on using neural networks to address built-in self-test (BIST) false alarms, highlighting his early contributions to AI in semiconductor testing. He worked as a Design for Test (DFT) architect at Raytheon before moving to Harris RF, where he focused on communication systems. Ron later joined Mentor Graphics, which was subsequently acquired by Siemens. Throughout his career, he has integrated AI and machine learning into semiconductor testing and design, significantly advancing the field.

Marc Hutner is the Director of Product Management for Yield Learning Products at Siemens. In his role, Marc focuses on yield learning and silicon debugging, aiming to identify yield limiters and improve semiconductor testing processes.

Marc joined Siemens over a year ago, bringing more than 20 years of experience in the semiconductor test industry. Before joining Siemens, he spent two years at proteanTecs as the Senior Director of Product Marketing for IP and Analytics for silicon health. Marc’s background includes working as an architect for test equipment and developing innovative concepts in semiconductor testing. His extensive experience positions him as a key figure in advancing Siemens' yield learning and debug capabilities.

Don Ong is the Director and Head of Innovation for the Advantest Field Service Business Group, a division of Advantest Inc. In his role, Don is responsible for driving the strategic development and implementation of innovative solutions that enhance Advantest’s Field Service business and operations. His responsibilities include identifying emerging technologies, leading cross-functional innovation projects, and fostering a culture of continuous improvement to optimize service efficiency, customer satisfaction, and business growth. Don works closely with internal teams and external partners, including startups, universities, and third parties, to ensure the successful integration of new technologies that meet the evolving needs of the semiconductor industry.

With over 20 years of experience in the semiconductor industry, Don has held multiple roles, including program management, product, application, and test engineering in both Silicon Valley and Asia. He holds a Bachelor's degree in Electrical and Electronics Engineering from Nanyang Technological University in Singapore and a Master’s of Studies from the University of Cambridge in the United Kingdom.

In this episode we will discover how scan technology and automatic test pattern generation (ATPG) have revolutionized the testing process, significantly boosting defect detection rates. Mark delves into digital twins, explaining their pivotal role in creating virtual representations for real-time system optimization.

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How is the semiconductor industry evolving in the face of global market trends and technological advancements?

Today, we are thrilled to welcome Pierre Cambou to our podcast. Pierre serves as the Principal Analyst for Global Semiconductors at Yole Group. With a rich background that includes founding a semiconductor startup and roles at notable companies like Thomson TCS and e2v Semiconductors, Pierre brings a wealth of industry knowledge. He is recognized as an expert in the semiconductor field, often cited by international media for his market and technology insights. Pierre holds an engineering degree, an MSc from Virginia Tech, and an MBA from Grenoble Ecole de Management.

Together we'll explore the industry's impressive annual growth rate of 6-7% and delve into the mobile market's fascinating journey from the late 90s to today. Discover how AI chips are revolutionizing smartphones and potentially transforming the sector.

We'll also uncover the cultural and practical reasons behind the persistence of feature phones in regions like India and Europe while they're nearly extinct in the US. We'll compare this trend to the automotive industry's ADAS level zero vehicles and assess how AI and edge technologies might shape future smartphone production. Moreover, we'll discuss the nuanced role of embedded AI in advancing mobile technology, predicting a slow but steady growth aligned with the global GDP.

Finally, we'll examine the global semiconductor manufacturing landscape, touching on government incentives, reshoring efforts, and strategic joint ventures like the TSMC and Sony collaboration in Japan. Pierre provides insights into the competitive dynamics among countries like Japan, Taiwan, and Korea, and the significant investments by China. We wrap up by discussing the industry's future, considering challenges such as managing energy consumption and the importance of green energy in mitigating environmental impacts. Tune in for a compelling dialogue packed with valuable perspectives and forward-looking predictions.

Thanks for tuning in to "Advantest Talks Semi"!

If you enjoyed this episode, we'd love to hear from you! Please take a moment to leave a rating on Apple Podcast. Your feedback helps us improve and reach new listeners.

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