![]() ![]() Positioning cells has a number of uses in the field: tissue growth, diagnosis, testing, and filtering. As Raymond explains, “This method enables biomedical engineers to design better devices more rapidly by leveraging the AI that has been imbued with the results of the simulations. In doing so, he has quickly and cost effectively built an environment that scales to accommodate a growing dataset and enables remote work, thus accelerating artificial intelligence (AI) research to develop new biomedical devices for organ cell growth. ![]() ![]() He has combined the flexibility of Amazon Elastic Compute Cloud (Amazon EC2) P3 Instances powered by NVIDIA V100 Tensor Core GPUs with MathWorks’ MATLAB’s deep learning capabilities to facilitate this work. In his bioengineering work, Raymond has used simulators to create a 20 GB dataset and deep learning to understand simulator input and output. To process the simulation and train the deep machine learning network needed to execute a proof of concept, Raymond, who began his project as a PhD candidate at the Massachusetts Institute of Technology (MIT), turned to the compute power of Amazon Web Services (AWS). Sam Raymond, who is currently a postdoctoral researcher at Stanford University and has been using MATLAB to develop new biomedical devices for organ cell growth. For 36 years, scientists, engineers, and researchers across various fields of study have used software provider MathWorks’ integrated development platform, MATLAB, to quickly, easily, and cost effectively build environments for research. ![]()
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