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Maxim’s New Camera Cube Design Enables Artificial Intelligences at the Edge


The camera cube executes low latency AI vision and hearing inferences on a coin cell power budget with reduced cost and size


Maxim Integrated have released the MAXREFDES178# camera cube reference design, which demonstrates how Artificial intelligence (AI) applications previously limited to machines with large power and cost budgets can be embedded in space-constrained, battery-powered edge devices. The MAXREFDES178# enables ultra-low-power internet of things (IoT) devices to implement hearing and vision and highlights the MAX78000 low-power microcontroller with neural network accelerator for audio and video inferences. The reference design also contains the MAX32666 ultra-low power Bluetooth® microcontroller and two MAX9867 audio CODECs. The entire system is delivered in an ultra-compact cube to show how AI applications such as facial identification and keyword recognition can be embedded in low-power, cost-sensitive applications such as wearables and IoT devices.

Click for Larger Image - Maxim’s New Camera Cube Design Enables Artificial Intelligences at the Edge AI applications require intensive computations, usually performed in the cloud or in expensive, power-hungry processors that can only fit in applications with big power budgets such as self-driving cars. But the MAXREFDES178# camera cube demonstrates how AI can live on a low-power budget, enabling applications that are time- and safety-critical to operate on even the smallest of batteries. The MAX78000’s AI accelerator slashes the power of AI inferences up to 1,000x for vision and hearing applications, as compared to other embedded solutions. The AI inferences running on the MAXREFDES178# also show dramatic latency improvements, running more than 100x faster than on an embedded microcontroller.

“The next big opportunity in AI is providing machine learning insights at the edge,” said Alan Descoins, CTO at Tryolabs. “The MAXREFDES178# shows how Maxim Integrated’s AI solution is a breakthrough in power, latency and size that can unlock the possibilities for AI in battery-powered designs.”

The compact form factor of the camera cube at 1.6in x 1.7in x 1.5in (41mm x 44mm x 39mm) shows that AI can be implemented in wearables and other space-constrained IoT applications. The MAX78000 solution itself is up to 50 percent smaller than the next-smallest GPU-based processor and does not require other components like memories or complex power supplies to implement cost-effective AI inferences.

“Machine learning promises a lot: that machines can make sense of what they see and hear like humans, as well as make more autonomous decisions. Until the MAX78000, the embedded world was left behind because you couldn’t implement AI at the edge in a power, cost and size constrained manner,” said Kris Ardis, executive director of the Micros, Security and Software Business Unit at Maxim Integrated. “Now the MAXREFDES178# demonstrates how meaningful and powerful AI inferences can be run at the edge, on even the smallest and most energy-conscious devices.”

Features of the MAXREFDES178 Hand-Held Camera Cube Reference Design

  • Two MAX78000 ARM Cortex M4F Microcontrollers with CNN Accelerator
  • BLE5 Wireless Connectivity
  • Li-Ion Battery Powered
  • Color Image Sensor
  • Digital Microphone
  • Multiple audio codecs with stereo audio input and output
  • Color TFT Capacitive Touch LCD
  • Micro SD Connector
  • On-Board QSPI FLASH and QSPI SRAM

For more information on the MAXREFDES178 Hand-Held Camera Cube Reference Design, visit the Maxim Integrated Website at Maxim Integrated MAXREFDES178 product page


The company's Web site address is www.maximintegrated.com.
[Reprinted with kind permission from Maxim Integrated - Release Date 21st June, 2021]