Part 4/13:
One critical point raised was that AI is not a static code artifact; it is a "live wire" that continuously requires training, adjustment, and optimization. This ongoing process incurs substantial compute costs, especially when deploying AI in production environments. Remote areas with connectivity issues amplify these challenges, as data transmission becomes a bottleneck, leading to increased operational costs.
To address this, he advocates for edge computing solutions—processing data locally on sensors or devices and transmitting only essential information back to the cloud. This approach can reduce costs, improve efficiency, and mitigate connectivity issues, especially in remote or resource-constrained environments.