Introduction

Generative AI is advancing at an unprecedented pace, rivaling the evolution of mobile phones and the Internet. With AI models now expanding to billions, or even tens of billions, of parameters, the demand for computing power is soaring.

Mounting Data Challenges

Statistics indicate that the global volume of data generated stood at approximately 10 exabytes (EB) in 2015. By 2025, this is projected to soar to 175 zettabytes (ZB), and by 2035, it could reach an astonishing 2,432 ZB.

Dr. Zhou Zhenyu, Chairman and CEO of Actions Technology, noted: ‘Relying on the cloud to handle all this data is clearly unrealistic.’

Dr. Zhou emphasized the need for a balanced distribution of computational tasks between cloud servers and edge devices.

Understanding Hybrid AI Architecture

This collaborative architecture, known as Hybrid AI, integrates cloud and edge AI for a more efficient experience. The deployment of edge AI is essential for creating accessible AI in daily life.

Challenges Facing Edge AI

• Finding a balance between performance, power, and cost.
• Building a robust ecosystem akin to CPU and GPU developments.

Advantages of Edge AI Deployment

Edge AI integrates machine learning into IoT devices, reducing reliance on cloud power and providing low-latency experiences. The benefits include:

• Low power consumption.
• Enhanced data privacy.
• Greater personalization.

Future of Edge AI

According to ABI Research, the edge AI market is expected to expand rapidly, with projections of four billion edge AI devices by 2028. Actions Technology is spearheading advancements with its latest strategy, aiming to produce low-power audio edge AI applications.

Overcoming Architectural Bottlenecks

Current general-purpose CPUs face challenges due to the traditional Von Neumann architecture, leading to significant power and memory access issues. Dr. Zhou advocates for a Computing-in-Memory (CIM) architecture based on SRAM to enhance performance.

Innovations with MMSCIM

Actions Technology’s Mixed-Mode SRAM-based CIM (MMSCIM) technology promises better energy efficiency and computational capabilities, particularly for audio applications.

Conclusion: A New Era for Audio Technology

With AI evolving rapidly, the integration of audio technologies is becoming paramount. Actions Technology’s innovations in edge AI represent groundbreaking steps towards a more connected and efficient audio future.

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