- Combined device AI computation could exceed 1,000 TOPS by the end of the decade
- Smartphones, wearables and earphones are becoming important distributed AI processors
- Average users likely carry hundreds of TOPS across multiple personal devices
Personal electronics is heading toward a point where combined AI computing across everyday devices rivals systems that once filled dedicated facilities, according to a Futuresource CE analysis tracks AI silicon trends through 2030.
The report examines how neural processors are spreading across smartphones, wearables and audio devices, and how performance growth across these categories may change our expectations of personal computing power.
Smartphones are of course central to all this, with flagship chips from companies like Qualcomm, MediaTek, Samsung and Apple now delivering up to 100 TOPS of neural processing power.
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Growing NPU performance
Forecasts suggest that smartphones alone could nearly triple their NPU performance by the end of the decade.
Smartwatches are also no longer quietly trailing smartphones, as dedicated neural processors are starting to appear in smartwatch chips, a step beyond previous designs that relied heavily on shared processing blocks.
Shipments of smartwatches reached around 94 million units globally by 2025, showing how widespread they are now.
Wireless earphones are also becoming increasingly popular with 360 million units shipped annually. Each earphone carries its own chip, so the silicon footprint reaches well over 700 million units each year.
This proliferation of AI-capable hardware across multiple devices supports a broader vision often described as the “walking supercomputer.”
“These are not speculative scenarios,” said Simon Forrest, Head of Core Technology at Futuresource Consulting. “They are the logical product of chip design trends already underway. Edge AI offers real advantages in terms of speed, privacy and cost, and traditional coded algorithms are being replaced by machine-learned versions that increase efficiency and expand capabilities. For CE brands, understanding where AI computing is headed and what silicon enables is becoming a fundamental strategic imperative.”
Forrest told us that by 2030 it would be possible for someone to wear personal electronics with a combined AI calculation of over 1,000 TOPS (1 POPS), though it wouldn’t be common.
He said: “Futuresource forecast modeling shows that the average is more likely to be in the range of 450 to 550 TOPS by the end of the decade, assuming a person carries a smartphone, laptop, smartwatch plus smart glasses and perhaps another wearable device. Nevertheless, this is still a significant amount of distributed AI computing capacity placed in and around the body.”
When combined with advances in wearables, smart glasses and wearables, the overall computing figure is more widely discussed alongside the performance of a single device.
Marketing parlance often leans on headline TOPS numbers, although raw numbers alone don’t capture the real world. Architecture design, memory bandwidth, and software optimization remain equally important when translating theoretical computing to practical AI tasks.
The move toward distributed processing across multiple devices reduces reliance on cloud services, improves response times, and keeps sensitive data closer to the device itself.
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