tinyML Talks: Unlocking TinyML: A Cost-Efficient Approach to Custom Microcontroller Design for AI...
Unlocking TinyML: A Cost-Efficient Approach to Custom Microcontroller Design for AI Applications
Mohamed Shalan
Head of Design and EDA
Efabless Corporation
In the rapidly evolving field of Tiny Machine Learning (TinyML), custom microcontrollers offer unmatched performance and power efficiency for AI applications. However, the traditional route of designing and implementing custom ASICs (Application-Specific Integrated Circuits) often comes with prohibitively high Non-Recurring Engineering (NRE) costs, making it a daunting endeavor for many.
In this talk, we will unveil an innovative ecosystem that transcends the barriers posed by NRE costs. Our comprehensive solution comprises open-source tools, a robust methodology, a thriving community, and access to fabrication services. This ecosystem empowers you to design and implement custom microcontrollers optimized for TinyML applications without the financial burden of traditional ASIC development.
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