Making The Case For Edge AI
RCRWirelessNews, Monday, January 13th, 2025
In the race to build-out distributed infrastructure for artificial intelligence (AI), there's a lot more glitz and glam around the applications and devices than around the cooling, rackspace and semiconductors doing the heavy lifting in hyperscaler clouds.
While that's maybe a function of what most people find interesting, it's also not misplaced. For AI to live up the world-changing hype it's riding high upon, distributing workload processing for AI makes a lot of sense-in fact, running AI inferencing on a device reduces latency leading to an improved user experience, it saves the time and cost of piping data back to the cloud for processing, and it helps safeguard personal or otherwise private data.
To say that another way, when you read an announcement for a new class of AI-enabled PCs or smartphones, don't think of it as just another product launch. Think of it as an essential piece of building out the connected edge-to-cloud continuum that AI needs to rapidly scale.