Food sciencelab1
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Kayla Lee conducted a food evaluation experiment where she tasted and described cheddar cheese, chocolate pudding, saltine crackers, and a Gala apple. She also evaluated granulated sugar, confectioner's sugar, honey, pure olive oil, and unsalted butter, rinsing with water between each food.
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For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2025/06/why-its-critical-to-have-an-integrated-development-methodology-for-edge-ai-a-presentation-from-lattice-semiconductor/
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The deployment of neural networks near sensors brings well-known advantages such as lower latency, privacy and reduced overall system costbut also brings significant challenges that complicate development. These challenges can be addressed effectively by choosing the right solution and design methodology. The low-power FPGAs from Lattice are well poised to enable efficient edge implementation of models, while Lattices proven development methodology helps to mitigate the challenges and risks associated with edge model deployment.
In this presentation, Hegade explains the importance of an integrated framework that tightly consolidates different aspects of edge AI development, including training, quantization of networks for edge deployment, integration with sensors and inferencing. He also illustrates how Lattices simplified tool flow helps to achieve the best trade-off between power, performance and efficiency using low-power FPGAs for edge deployment of various AI workloads.OWASP Barcelona 2025 Threat Model Library
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