C h a p t e r 2 | D e s i g n C o n s i d e r a t i o n s f o r E m b e d d e d A I
Key Points
• As AI models grow in complexity, high-
performance memory is needed for handling
large datasets, particularly for edge AI
applications that balance power, cost, and
physical size constraints.
• Edge AI systems demand memory with low
latency and high bandwidth.
• Designers must make trade-offs when
selecting memory technologies to balance
performance, power consumption, and cost.
• Micron offers high-performance, low-
power memory solutions optimized for
edge AI, collaborating with chipset
manufacturers to ensure compatibility,
performance, and ruggedized options for
industrial deployments.
e.MMC Memory
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5 Experts on Addressing the Hidden Challenges of Embedding Edge AI into End Products
