I’m Joel Pitt from New Zealand.
I’ve been fascinated by learning algorithms, complex systems, and emergent behaviour since I was teenager. Whether that’s evolvable 3d physics simulations (back in early 2000), to learning molecular biology and building genomics and bioinformatic tools for colleagues at university, to country-wide GIS simulations to predict the spread of invasive biological species as part of my PhD.
More recently I’ve been fascinated by using recent advances in deep learning for artistic purposes and learning how neural networks can push the envelope in the field of computer vision.
The speed at which machine learning and AI is progressing is breath-taking compared to two decades ago, and it’s an exciting time to be alive!
I think it’s great that SNet is taking on the ambitious project of ensuring these advances are available to all and that it’s open-source development meshes well with the ethos of the machine learning community’s desire for an open research environment.
My role at SingularityNet is to assist whereever I can be most helpful. Currently I’m focussed on integrating existing machine learning models and algorithms as SNet services, to help seed the network with things people will hopefully find useful. If you have particular machine learning models you’d like to see available on SNet, feel free to reach out. I’m happy to either point you in the right direction or put it on my todo list