Summary:  What comes next after Deep Learning?  How do we get to Artificial General Intelligence?  Adversarial Machine Learning is an emerging space that points to that direction and shows that AGI is closer than we think.

Deep Learning, Convolutional Neural Nets (CNNs) have given us dramatic improvements in image, speech, and text recognition over the last two years.  They suffer from the flaw however that…

Summary:  Are there large, sustainable career opportunities in AI and if so where?  Do they lie in the current technologies of Deep Learning and Reinforcement Learning or should you focus your career on the next wave of AI?

If you’re a data scientist thinking about expanding your career options into AI you’ve got a forest and…

Summary:  At the core of modern AI, particularly robotics, and sequential tasks is Reinforcement Learning.  Although RL has been around for many years it has become the third leg of the Machine Learning stool and increasingly important for Data Scientist to know when and how to implement.

If you poled a group of data scientist just a few years back about how many machine learning problem types there are you would almost certainly have gotten a…

Summary:  What are the earliest seeds of artificial intelligence?  To whom do we owe thanks for starting us down this path?  Many modern researchers to be sure, but the earliest is Leonardo Torres of Spain, in about 1914.

As data scientists it’s very cool to be at the forefront in this age of techno-optimism.  Since the awakening of the digital age calculated by economic researchers to have begun about 1994, a wave of increased productivity has…