2. Executive Summary
• IoT today is all about reporting & alerting from edge devices to a cloud
• Edge computing promises the ability for the edge to act on what it senses,
turning IoT into actors, not just reporters
• Edge computing addresses the three key issues with cloud computing:
Latency, Security & Bandwidth
• Initial opportunities will be simple if-then-else scenarios until next gen
processors purpose built for AI functions are productized
3. Edge Computing – Simplified View
• Edge computing is pushing the decision back to the data source for
faster actioning
• The world has progressed from centralized computing, to
decentralized, to cloud computing
• Edge computing is the next wave, that is just beginning. Not all
systems are suited for a cloud computing model
4. Cloud Computing – A Venn of Challenges
• Latency
• The decision needs to be made
immediately for highest value
• Security
• Regulatory compliance concerns
regarding secure transfer of data
between on-premise systems & sensors
• Bandwidth
• The associated high cost of transferring
data to & from the cloud
Latency Privacy
Bandwidth
Edge
Computing
Sweet Spot
5. The future of Edge Computing will be
AI tuned chips embedded in devices
6. Edge Computing – Use Cases
• AR & Maintenance Operations – the IoT device communicates with the AR
device to highlight the problem and tell the maintenance operator how to fix it.
• Neuroimaging – the MRI machine has an embedded AI that can recognize
anomalies at scan time, enabling faster patient response
• Smart Scanners – a portable scanner has an AI engine embedded, enabling the
decision about how to classify content to happen at the edge
• Voice Assistants – The AI engine is embedded into the VA device, reducing the
transmission of private information and increasing the speed of responses
7. Processor Gold Rush
• The task of processing AI is very different from standard computing or
GPU processing
• Software companies now building their own AI chips:
• Microsoft is building HoloLens specific chip
• Google is building Tensor Processing chip
• Amazon working on Alexa specific chip
• Apple working on Neural Engine chip for Alexa
• …
• The AI chip on the edge won’t replace the AI chip in the cloud. They
will complement with specialized inputs, processing and outputs
8. Summary
• Cloud computing isn’t the answer to every processing question
• Where privacy, latency and bandwidth concerns converge, edge computing
should be where the business looks for options
• Edge computing doesn’t require specialized AI chips to provide
business value
• However next generation AI specialized chips will change the edge computing
landscape