Edge AI is Coming to a Location Near you Soon!
Artificial Intelligence (AI) has been a transformative technological force, traditionally centered around cloud computing. However, a new frontier is emerging, known as Edge AI. This paradigm shift brings AI processing from centralized locations directly to the "edge" of the network - closer to where data is generated and utilized. This advancement rapidly changes how industries operate and interact with technology, making it more a part of our daily lives.
Edge AI refers to deploying AI applications in retail stores and factories to hospitals and even household appliances. This technology processes data locally, right at the source, rather than transmitting it back and forth to a distant cloud or data center. This proximity to data sources significantly reduces latency and enhances real-time processing capabilities.
The Benefits of Edge AI
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Edge AI in Action: Industry Applications
As technology continues to evolve, the potential applications of Edge AI seem boundless. From smart homes and cities to advanced manufacturing and healthcare, Edge AI is set to revolutionize various sectors, making technology more integrated into our daily lives.
Integrating Edge AI into more devices and systems indicates a future where real-time data processing and AI-driven decision-making become commonplace, bringing AI to locations near you.
Tony, I completely agree. With various suffixes, the market has been discussing the impacts on all this industries at on-prem and network edge while awaiting the "killer app" and experiencing the challenges of the "chicken and the edge" paradigm (as Joe Reele mentioned last year at PTC). It's essential for the distributed cloud and edge to be hybrid, and the impact of Edge AI will be significant. The industry's focus should be on standardization for hyperscale and new higher-density edge data center architectures.
Tech Executive | Investor | Board Member
11moTony, you are right but only for a fraction of the stack. Kubernetes can break down which portions of the workload are served directly at the edge. AI inference latency is awful if you are processing 100% in the core 🙂
General Manager, Australia, New Zealand and APAC, at Ekkosense.
11moAdding military applications to your 4 #edgeai list Tony.