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Edge Computing - The Future of Embedded Systems
Himanshu Savargaonkar - Watch Now - EOC 2022 - Duration: 09:46
Edge Computing - The Future of Embedded Systems
Himanshu Savargaonkar
Until recently, the key platforms in the embedded space were the microcontrollers, microprocessors, and FPGAs. But now the playing field is changing. With the inclusion of GPUs, AI accelerators, Blockchain Chips within the embedded ecosystem the whole field is primed to explode into the new era. I believe that this new era of embedded will be powered by and based on Edge Computing.
Edge Computing can be described as a paradigm of traditional artificial intelligence. It aims at bringing AI and ML closer to the edge. Executing the models on the edge nodes rather than on the centralized servers. This idea has many advantages. Applications of the same have started popping up in the industry at various places.
This short talk introduces the concept and idea behind edge computing. We look at the advantages and disadvantages currently present in the technology. We further explore Fog Computing, a sub-part of edge computing in detail. Taking real-world examples, we predict the future of technology.
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How does Himanshu Savargaonkar define Edge Computing in the talk?
A
A paradigm in which substantial computing and storage resources are placed at the Internet's edge in close proximity to mobile devices or sensors.
B
A model where all computation and storage is moved entirely off the cloud to tiny microcontrollers.
C
A cloud-centric approach that centralizes processing in large datacenters to minimize edge complexity.
D
A method that only uses GPUs and AI accelerators inside the cloud to run embedded workloads.
E
A system that only stores sensor data at the edge but always sends it to the cloud for processing.
