Rapid development of AI at the edge necessitates appropriate processors and memory systems
In a groundbreaking development, AI silicon provider Hailo and memory technology leader Micron have joined forces to revolutionise edge AI applications. This collaboration aims to rethink how millions, or even billions, of endpoints can evolve beyond simple cloud connectivity for AI tasks, becoming truly AI-enabled edge systems.
Hailo's AI Processors and Micron's LPDDR Technology: A Balanced Solution
At the heart of this partnership is Hailo's Hailo-10H AI processor, capable of delivering up to 40 TOPS, making it ideal for running deep learning applications more efficiently and effectively than traditional solutions. The Hailo-15 VPU system-on-a-chip combines AI inferencing capabilities with advanced computer vision engines, generating premium image quality and advanced video analytics.
Micron's LPDDR technology, known for its high-speed, high-bandwidth data transfer with low power consumption, is the perfect complement to Hailo's AI processors. This technology offers significant performance gains over earlier generations, with LPDDR5X doubling the performance of LPDDR4X, making it ideal for edge AI applications.
Overcoming Edge AI Challenges
Managing AI at the edge introduces new challenges, including the need to consider memory performance while staying within strict limits on energy consumption and cost. However, the combination of Hailo's AI processors and Micron's LPDDR technology provides a balanced solution, staying within tight energy and cost budgets.
Optimising AI for the Edge
To further optimise AI for the edge, several strategies are being employed. These include model optimisation techniques such as quantization, pruning, knowledge distillation, fine-tuning, and compiling models to machine code. Additionally, efficient compute architectures are being developed, with AI accelerators like neural processing units (NPUs) being embedded directly within microcontrollers or SoCs.
These steps significantly decrease computational demands and energy consumption while maintaining necessary accuracy and responsiveness at the device level. The goal is to enable power-constrained edge devices to perform advanced AI tasks efficiently, making AI truly pervasive in IoT and video surveillance environments.
The Future of Edge AI
The future of edge AI lies in co-processors that integrate with edge platforms, enabling real-time deep learning inference tasks with low power consumption and high cost-efficiency. These processors support a wide range of neural networks, vision transformer models, and large language models (LLMs).
As AI foundation models grow larger, memory bandwidth and performance have not advanced at the same rate as compute power, creating a bottleneck. However, the Hailo-15 VPU can handle both AI-powered image enhancement and processing of multiple complex deep learning AI applications at full scale and with excellent efficiency.
The industry is shifting towards more efficient compute architectures and specialised AI models tailored for distributed, low-power applications. Hailo's processors are geared towards the new era of generative AI on the edge, enabling perception and video enhancement through a wide range of AI accelerators and vision processors.
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Technology plays a crucial role in this partnership between Hailo and Micron, as they work together to revolutionise edge AI applications. Hailo's AI processors, such as the Hailo-10H and Hailo-15 VPU, and Micron's LPDDR technology, known for its high-speed, high-bandwidth data transfer with low power consumption, aim to provide a balanced solution for managing AI at the edge, overcoming challenges like memory performance and energy consumption.
