NEW YORK, May 7, 2024 /PRNewswire/ -- Smartphone and PC vendors have shifted focus to on-device generative Artificial Intelligence (AI). They have committed significant resources to producing chipsets that can handle inference workloads previously limited to the cloud. According to global technology intelligence firm ABI Research, this will unlock AI chipset shipments and revenue growth in these industries and extend to tablets and gaming consoles, reaching over 1.3 billion shipments in 2030.
"In the smartphone market, OEMs like Vivo and Samsung have started implementing heterogenous AI chipsets and investing in generative AI applications to deploy on their devices. While chip vendors Qualcomm and MediaTek have promoted their developer and optimization tools to kickstart application development," explains Paul Schell, Industry Analyst at ABI Research. The same applies to the PC market, where chip vendors like AMD and Intel have started shipping heterogenous AI chipsets for PCs, complemented by the concerted effort between OEMs and ISVs like Microsoft to build optimized AI software. "We can observe all corners of the ecosystem rallying behind the potential of low-latency, data-private AI applications that can scale beyond cloud environments, although we are still at a very early stage."
Heterogenous AI chipsets capable of distributing workloads between CPU, GPU, and NPU are highly effective architectures for tackling today's diverse AI workloads – including generative and multimodal AI – and these systems will be adopted across device markets at an accelerating rate. More demanding on-device AI workloads in PCs will be addressed by GPU cards, like NVIDIA's RTX, and AMD's high-end Radeon hardware. This is why these chipsets, which reside outside of heterogenous systems, will remain in the AI mix going forward.
For on-device AI in personal and work devices to fulfill its potential, application development incentives like Intel's AI PC Acceleration Program and the in-house work from captive vendors Apple and Google will need to bear fruit to convince consumer and enterprise customers to pay a premium. "ABI Research believes productivity AI applications can reduce refresh cycles of smartphones, notebooks, and desktops – as well as other AI applications in tablets and gaming consoles – and provide the incentive to bring about this uptick in demand," Schell concludes.
These findings are from ABI Research's Artificial Intelligence and Machine Learning: Personal & Work Devices market data report. This report is part of the company's AI & Machine Learning research service, which includes research, data, and ABI Insights.
About ABI Research
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