Robots and Physical Computing

This is the first of a planned occasional series of posts on playing with some of the current AI specific add-on processors for Intenet of Things (IoT). In the series, it is planned that some experiments with the Google Coral adapter and the Development Board; as well the NVIDIA Jetson Nano will be shown. Why bother? Basic reason is I love playing with AI and hardware - so it is kind of fun. Another reason is AI, IoT and e dge computing, are important and growing technologies, and I want to start getting my head around them a bit. In this post, I look at starting to use Coral Accelerator with a Raspberry Pi. The Coral environment is related to Google's earlier AIY Edge Tensor Processing Unit (TPU) range  https://aiyprojects.withgoogle.com/edge-tpu/  and designed to work with TensorFlow Lite . Good place to start is Google's Get started with the USB Accelerator  pretty much all you need to do to get going is in it, it also mentions Raspberry Pi. It makes a good ...

This is second in a two-post series on building a neural network using microbits with micropython. In the first post python was used to produce a neural network without the microbits. In this post the network is as shown in figure 1 is developed. The figure below shows the arrangement of the connections to be built; pin 2 is the output of each neuron. The two micro:bits/neurons on the left of the picture taking in the two same inputs ; the output from these neurons are the two inputs to the output neuron on the right. figure 1 The micro:bit objects used in Figure 1 were produced using the micro:bit Fritzing diagram available at  https://github.com/microbit-foundation/dev-docs/issues/36  thanks to David Whale ( @whalleygeek  ) for this. The Inputs neurons Neuron 1: from microbit import * W=[-1,-1,1] while True:     x1=pin0.read_digital()     x2=pin1.read_digital()     net = W[0]+W[1]*x1+W[2]*x2 ...

These two posts are really extensions of a set of post in response to a question from Carl Simmons ( @Activ8Thinking ) concerning building a micro:bit simple neuron. In those, the Microsoft MakeCode was used. In this two-post series is going to go through building neurones and neural networks in Python and by the end of the second post a python-based microbit neural network Post 1 (this one) A  single neuron and a simple neuron network will be produced in Python are produced. Post 2 looks at producing a network of neurons, ie. neural network using the idea from post 1 but using a three microbits.; looking to solve the problem that a single neuron can't solve, making an Exclusive OR gate (XOR) 1. Overview and non-microbit neuron 1.1 Overview:  The characteristics of the system will be: Inputs are going to be binary Weighted sum is bias+W1*input1+w2*input2 If weighted sum>=0 then the output is True (T on the LEDs) or '1' If weigh...

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