2024-07-26 15:15:00 ET
Summary
- For AI to fully integrate into everyday consumer life, end-user devices must be able to process AI workloads, rather than solely relying on cloud computing.
- On-device AI can reduce costs and latency, improve personalization and privacy, and enable real-time processing, which are crucial to bringing AI to everyday applications and use cases.
- We expect edge AI, which is closely associated with the Internet of Things, to continue to gather momentum.
For AI to fully integrate into everyday consumer life, end-user devices must be able to process AI workloads, rather than solely relying on cloud computing. On-device AI can reduce costs and latency, improve personalization and privacy, and enable real-time processing, which are crucial to bringing AI to everyday applications and use cases. As a result, we expect edge AI, which is closely associated with the Internet of Things (IoT), to continue to gather momentum.
Edge AI spans various applications across IoT and consumer devices, such as smartphones, wearables, headsets, drones, industrial technology, and automobiles. By 2027, an estimated 62% of data will be processed on edge devices. And by 2028, an estimated 26 billion short-range IoT connections will be driven by on-device AI, benefitting various associated technologies that enable connected devices infrastructure. 1,2 As a result, we believe edge AI presents an attractive investment case for investors looking to find AI opportunities outside of semiconductor players and cloud hyperscalers that have dominated the AI story thus far. ...
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For further details see:
Internet Of Things And Devices Poised For Edge AI-Driven Upgrades