Highly Recommended Viewing: A Rapid Overview of Machine Learning, Deep Water meta-Framework and 16 GPU EC2 Instances

The first talk hits the mark on providing a rapid-fire quick history and update on machine learning and also provides an introduction to Amazon’s 16 GPU Amazon EC2 instance to train or act as the hardware foundation for the new world of machine language frameworks.

From the Deep Water website – “Using complex multi-layer artificial neural networks, Deep Learning helps us derive insights from large unstructured data such as images, videos, sound and text or structured data from transactional databases such as financial data or time series. It enables innovations in domains as varied as medicine, social media, customer service, targeted marketing, automotive safety, security or fraud detection.”

In the next video, Amazon offers up a 8 and 16 GPU EC2 instance.  A P3 instance can offer 1 PetaFLOP in a single instance.

A side note: We can differ on the optimism expressed but we are looking at the building of a new machine learning technology which will have a deeply profound ability to change society in radical ways. This is no longer speculation. An equivalent of a “Cambrian explosion” is on its way and will hit human societies in relatively short order.  For example, what happens when you don’t need drivers, cashiers, analysts, and a wide range of other jobs because machine-learning agents do the work? When technology will not generate new jobs for humans but rather for AI?  What effect will this have on human societies in general to see such wide-spread job losses. Will governments act on behalf of their citizens or on behalf of other interests.  It is an interesting question worth pondering now (as opposed to when we are faced with the problem).  Two authors Robert McChesney (professor at the University of Illinois at Urbana–Champaign) and John Nichols (journalist) offered a view of this future in 2016 in the book “People Get Ready – The fight against a jobless economy and a citizenless democracy “.