On 30 July 2021, the Federal Court of Australia decided that AI systems can be inventors. In a word-first determination of Thaler v Commissioner of Patents, the Honourable Justice Beach found that AI systems can be the inventors on a patent application under Australian patent law.

[image: iStockphoto]

How does one determine whether an action is good or bad? Most people use some form of moral framework to rationalise the ‘goodness’ of their decisions.

[image: Atlassian]

In today’s blog post — We are excited to introduce our latest initiative — a DeepNeuron Law and Ethics (LAE) Committee.

Six Monash University students have taken 2nd prize in the SuperComputing 2021 Indy Student Cluster Competition (IndySCC).

Hello and welcome to the Monash DeepNeuron project walkthrough! If you haven’t already checked out our previous blogs on Introduction to Deep Learning, I highly recommend you check those out and get familiar with the concepts before proceeding.

In workshop 2 of this series, we introduced PyTorch, and showed you how to create datasets, data loaders, and bind it all together into a training and validation loop. In that article we were using pre-trained models which we fine-tuned with our own dataset to try and get better results.

In workshop 2 of this series, we introduced PyTorch, and showed you how to create datasets, data loaders, and bind it all together into a training and validation loop. Now, we want to extend the power of our models by introducing CNNs to recognise patterns in visual data.

How can we bring AI to life? Creating neural networks using PyTorch!

Through time there have been a variety of deep-learning frameworks: Theano, Torch, MXNet… the list goes on, but from all of them arose the big-two giants — TensorFlow and PyTorch.

Perceptrons, Datasets, and Neural Nets, if you think you’ve stumbled across a biology article you have been mistaken. We’re going to run through the fundamental principles of deep learning at a very high level to give you a smooth introduction to the field, without the mathematical baggage that comes with it.

In a Student Cluster Competition, students are required to work with hardware and assemble a computing cluster that is capable of running a range of High-Performance Computing applications. These include but are not limited to benchmarks as well as various scientific programs in the domains such as Artificial Intelligence, Quantum computing, and Astronomy.