tinyML Hackathon Challenge 2023 - Brainchip Akida PCIe Board
Akida PCIe Board INTRODUCTION
The Akida Board Evaluation Kit is a one-lane PCIe board, for Akida technology assessment. Itincludes the AKD1000 Akida processor from Brainchip. The PCIe board can be integrated into a Linux computer. An x86-64 PC architecture, such as any intel, i5, i7, i9 based computer.Or an aarch64 machine architecture such as a Raspberry Pi 4 (IO mother board + CSdaughter board).OSLinux Ubuntu 16.04, 18.04 and 20.04SlotsA one-lane PCIe slot available
Akida Board Evaluation Kit content and description:
• Akida PCI Express Reference Board
• Bracket and screw
Raspberry Pi
The Raspberry Pi is an aarch64 machine architecture such as a Raspberry Pi 4 (IO mother board + CS daughter board).
Видео tinyML Hackathon Challenge 2023 - Brainchip Akida PCIe Board канала The tinyML Foundation
The Akida Board Evaluation Kit is a one-lane PCIe board, for Akida technology assessment. Itincludes the AKD1000 Akida processor from Brainchip. The PCIe board can be integrated into a Linux computer. An x86-64 PC architecture, such as any intel, i5, i7, i9 based computer.Or an aarch64 machine architecture such as a Raspberry Pi 4 (IO mother board + CSdaughter board).OSLinux Ubuntu 16.04, 18.04 and 20.04SlotsA one-lane PCIe slot available
Akida Board Evaluation Kit content and description:
• Akida PCI Express Reference Board
• Bracket and screw
Raspberry Pi
The Raspberry Pi is an aarch64 machine architecture such as a Raspberry Pi 4 (IO mother board + CS daughter board).
Видео tinyML Hackathon Challenge 2023 - Brainchip Akida PCIe Board канала The tinyML Foundation
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
![tinyML Talks Taiwan in Mandarin and English: Discovering tinyML](https://i.ytimg.com/vi/hPtRLygc4LE/default.jpg)
![tinyML Summit 2022: Sensing Applications as a Driver for TinyML Solutions](https://i.ytimg.com/vi/pUAAGVVYgLQ/default.jpg)
![tinyML Neuromorphic Engineering Forum - Sensors Session](https://i.ytimg.com/vi/Mt9X0ALdCpI/default.jpg)
![tinyML Vision Challenge - Himax & Edge Impulse](https://i.ytimg.com/vi/6tmCEzNSIas/default.jpg)
![tinyML Talks Chao Xu: Enabling Neural network at the low power edge: A neural network compiler...](https://i.ytimg.com/vi/Rs1yeTSuZLA/default.jpg)
![SensMACH 2020 Daniel Situnayake: Embedded machine learning in the real world](https://i.ytimg.com/vi/a67hWPT1NLE/default.jpg)
![tinyML Talks: Empowering the Edge: Practical Applications of Embedded Machine Learning on MCUs](https://i.ytimg.com/vi/tkqNS611cRc/default.jpg)
![tinyML Talks: Efficient AI for Wildlife Conservation](https://i.ytimg.com/vi/FfvcZEMn2l0/default.jpg)
![tinyML Research Symposium 2022: Towards Agile Design of Neural Processing Units with Chisel](https://i.ytimg.com/vi/xlP1xdKRrqc/default.jpg)
![tinyML Talks Phoenix: Novel Device and Materials in Emerging Memory for Neuromorphic Computing](https://i.ytimg.com/vi/_apkQF1ZL6A/default.jpg)
![tinyML Talks - Phoenix meetup: Analog TinyML for health management using intelligent wearables](https://i.ytimg.com/vi/bCzg8y6aRi8/default.jpg)
![tinyML Talks India: Single Lead ECG Classification On Wearable and Implantable Devices](https://i.ytimg.com/vi/uHywaYleCtA/default.jpg)
![tinyML Summit 2023:Personal Computing devices use-case and applications enabled by Smart Sensors](https://i.ytimg.com/vi/9hvz6ZB5G8A/default.jpg)
![tinyML Talks: From the lab to the edge: Post-Training Compression](https://i.ytimg.com/vi/Ada9Tq8JAX8/default.jpg)
![tinyML Talks: State of Hardware & Software Ecosystem for Low-Power ML Applications on RISC-V](https://i.ytimg.com/vi/Rcbrc2rnXlk/default.jpg)
![tinyML Talks: Meetup Italy with small-medium industries](https://i.ytimg.com/vi/sAmRSm-tdd4/default.jpg)
![tinyML Hackathon Challenge 2023 - Infineon XENSIV 60GHz Radar Sensor and devkit explanation](https://i.ytimg.com/vi/yL6f61MKzFo/default.jpg)
![tinyML Auto ML Tutorial with Qeexo](https://i.ytimg.com/vi/qo0JTM6gaIE/default.jpg)
![tinyML On Device Learning Forum - Warren Gross: On-Device Learning For Natural Language Processing..](https://i.ytimg.com/vi/ERLFRluwRjA/default.jpg)
![EMEA 2021 tiny Talks: Building Heterogeneous TinyML Pipelines](https://i.ytimg.com/vi/p-Rtnvj4L4I/default.jpg)
![tinyML EMEA 2022- Eran Treister: Wavelet Feature Maps Compression for Image-to-Image CNNs](https://i.ytimg.com/vi/fPmvwecx7TY/default.jpg)