Synopsis: The new cognitive capabilities in our machines were the result of a shift in the way we
think about problem solving. The shift is the most significant change in AI, ever, if not in
science as a whole. Machine Learning based systems are now successfully attacking
both simple and complex problems using these novel Methods.
We are experiencing a revolution at the level of Epistemology which will affect much more
than just the field of Machine Learning. We want to add more of these new Methods to
our standard problem solving toolkit, but we need to understand the tradeoffs.
Bio: Monica Anderson, MSCS, is an independent AI and ML researcher and founder of Syntience Inc.
Her work has focused on the Epistemology of AI but all her theory is based on her experiences of design and implementation of (Human Language) Understanding Machines based on Deep Discrete Neuron Networks since Jan 1, 2001.
She can adopt a Holistic or Reductionist stance as needed, and wants to teach others how to switch. Her current projects include creating a social medium where chat messages are routed by an Understanding Machine. She has been awarded a handful of patents in this field.
She is an ex-Googler, has facilitated 100+ Bay Area AI meetup sessions over 5 years, and plays keyboards and Bridge.