AI is pervasive today, from consumer to enterprise applications. With the explosive growth of connected devices, combined with a demand for privacy/confidentiality, low latency and bandwidth constraints, AI models trained in the cloud increasingly need to be run at the edge.
MAIX is Sipeed’s purpose-built module designed to run AI at the edge, we called it AIoT. It delivers high performance in a small physical and power footprint, enabling the deployment of high-accuracy AI at the edge, and the competitive price make it possible embed to any IoT devices. As you see, Sipeed MAIX is quite like Google edge TPU, but it act as master controller, not an accelerator like edge TPU, so it is more low cost and low power than AP+edge TPU solution.
 
Specifications:
 
CPU:RISC-V Dual Core 64bit, 400Mh adjustable
Powerful dual-core 64-bit open architecture-based
processor with rich community resources
FPU Specifications IEEE754-2008 compliant high-performance pipelined FPU
Debugging Support High-speed UART and JTAG interface for debugging
Neural Network Processor (KPU)
• Supports the fixed-point model that the mainstream training framework trains according to specific restriction rules
• There is no direct limit on the number of network layers, and each layer of convolutional neural network parameters can be configured separately, includ- ing the number of input and output channels, and the input and output line width and column height
• Support for 1x1 and 3x3 convolution kernels
• Support for any form of activation function
• The maximum supported neural network parameter size for real-time work is 5MiB to 5.9MiB
• The maximum supported network parameter size when
working in non-real time is (flash size - software size)
Audio Processor (APU)
• Up to 8 channels of audio input data, ie 4 stereo channels
•  Simultaneous scanning pre-processing and beamforming for sound sources in up to 16 directions
• Supports one active voice stream output
• 16-bit wide internal audio signal processing
• Support for 12-bit, 16-bit, 24-bit, and 32-bit input data widths • Multi-channel direct raw signal output
• Up to 192kHz sample rate
• Built-in FFT unit supports 512-point FFT of audio data
•Uses system DMAC to store output data in system memory
Static Random-Access Memory (SRAM)
The SRAM is split into two parts, 6MiB of on-chip
general-purpose SRAM memory and 2MiB of on-chip AI SRAM memory, for a total of 8MiB
Field Programmable IO Array (FPIOA/IOMUX)
FPIOA allows users to map 255 internal functions to 48
free IOs on the chip
Digital Video Port (DVP) Maximum frame size 640x480
FFT Accelerator
The FFT accelerator is a hardware implementation of the
Fast Fourier Transform (FFT)

Software Specifications:

FreeRtos & Standard SDK Support FreeRtos and Standrad development kit
MicroPython Support Support MicroPython on M1
Machine vision Machine vision based on convolutional neural network
Machine hearing High performance microphone array processor

Electrical Features:

  • For Sipeed MAIX-I module Without WiFi
Supply voltage of external power supply 5.0V ±0.2V
Supply current of external power supply >300mA
Temperature rise <30K
Range of working temperature -30℃ ~ 85℃
 
  • For Sipeed MAIX-I module With WiFi
Supply voltage of external power supply 4.2V ~ 5.2V
Supply current of external power supply >600mA
Machine vision <30K
Machine hearing -30℃ ~ 85℃
 
RF Features:
  • With WiFi
    • MCU : ESP8285 Tensilica L106 32-bit MCU
    • Wireless Standard 802.11 b/g/n
    • Frequency Range 2400Mhz - 2483.5Mhz
    • TX Power(Conduction test) 802.11.b : +15dBm
    • 802.11.g : +10dBm(54Mbps)
    • 802.11.n : +10dBm (65Mbps)
    • Antenna Connector IPEX 3.0x3.0mm
    • Wi-Fi mode Station/SoftAP/SoftAP+Station
MAix's Advantage and Usage Scenarios:
  • MAIX is not only hardware, but also provide an end-to-end, hardware + software infrastructure for facilitating the deployment of customers' AI-based solutions.
  • Thanks to its performance, small footprint, low power, and low cost, MAIX enables the broad deployment of high-quality AI at the edge.
  • MAIX isn't just a hardware solution, it combines custom hardware, open software, and state-of-the-art AI algorithms to provide high-quality, easy to deploy AI solutions for the edge.
  • MAIX can be used for a growing number of industrial use-cases such as predictive maintenance, anomaly detection, machine vision, robotics, voice recognition, and many more. It can be used in manufacturing, on-premise, healthcare, retail, smart spaces, transportation, etc.
Technical Details:
 
Dimensions 25mm x25mm x1mm
Weight G.W 8g
Battery Exclude

Package Includes:

  • 1 x Sipeed MAIX-I module

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Sipeed MAIX-I module

  • Brand: Seeed Studio
  • Product Code:Seeed-Sipeed-MAX-I
  • Reward Points:10
  • Availability:Out Of Stock
  • रo 1,210.68

  • Ex Tax:रo 1,026.00
  • Price in reward points:1026

  • 100 or more रo 1,163.48

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Tags: Sipeed, MAIX, AI, edge

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