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The Alif Blog

How different should you want your AI MCU to be?

We are in the early days of implementing AI at the edge, and the market for edge AI processors has not yet settled into a stable, mature state. In an industry as dynamic and innovative as the semiconductor business, that means that competition is intense, and many companies with a wide variety of product concepts are emerging.

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A vision of the future: MCU-based edge AI devices to take center stage in consumers’ digital lives

AI offers the biggest opportunity for many endpoint or edge IoT device manufacturers to add value to their products and achieve meaningful differentiation. But because of edge AI devices’ limited resources – power, processor bandwidth and size – manufacturers are continually bumping up against the ceiling of what they can do in AI with a microcontroller.

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Understanding the Ensemble difference: An NPU choice to stand the test of time

Whether by accident or design, the microcontroller industry made a good collective decision when it standardized on the Arm® M-profile architecture. Today, all the world’s big microcontroller manufacturers use Arm CPU cores, which means that the M-profile architecture is here to stay.

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Understanding the Ensemble difference: MCU’s granular power management circuit produces extreme power savings

We have explained previously how Ensemble and Balletto microcontrollers pair a neural processing unit (NPU) with a CPU to produce very fast AI inferences in edge applications, while also performing system control functions as a conventional MCU does. At the edge, a small battery is the most common power source. Is this compatible with AI?

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