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Regarding AI, what is fascinating is the fact that open source software packages are at the forefront. Google has produced and maintained TensorFlow and ensured that it runs effectively around Raspberry Pi hardware. In terms of AI and device vision, this is indeed an interesting time. In fact, it is indeed an open resource, which shows that more people can participate and lead their efforts and ideas.

Given the basics, why should you use Raspberry Pi?

Raspberry Pi 4 came out last year, and during the initial period, Raspberry Pi was able to run deep learning neural networks at reasonable speeds (for example, 4 or 5 Hz). It's not super fast, but many applications can use this feature. Our bird feeder application is a good example.

The Raspberry Pi Foundation will continue to improve effectiveness, and long-term versions of Vizy will also increase. Raspberry Pi can also be everywhere, everyone is using it, and the amount of information and support is huge. It is different from other platforms that have not been identified as such and also have on-site assistance. Therefore, we believe that the Vizy system is generally a convincing platform that allows AI and machine vision to move forward

Which machine learning software package can be used for this program?

I can't believe any machine learning software program that cannot be used with Raspberry Pi. Smaller size packages supported by TensorFlow, PyTorch, Keras, OpenCV and Python. This is a large room, not restricted by assistance, so this is another reason why Raspberry Pi is convincing.

To use Vizy, we need to take up most of the components of the Raspberry Pi and add better energy components, improved I/O, a sturdy enclosure, and easy-to-use and more integrated computer software. We are happy to find out what individuals think about this!