John Chamberlain, Software Developer and Author
 Developer Dairy – You Heard It Here First – Saturday, February 9, 2019
AlphaStar Chases the Singularity
Something extremely important has just happened in the field of AI which has significant implications for mankind. After about 2 years of effort, DeepMind has figured out how to succeed at StarCraft. On December 10, 2018, their Starcraft AI called "AlphaStar" beat a strong amateur for the first time and two weeks ago it beat a second-tier professional player 10-1 in a live event. AlphaStar uses a new method of neural network training that promises to give computers the ability to create genuine strategies for the first time--the last remaining serious obstacle to achieving artificial intelligence. ....
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Sliva, Amy, Scott Neal Reilly, Randy Casstevens, and John Chamberlain. "Tools for validating causal and predictive claims in social science models." Procedia Manufacturing 3 (2015): 3925-3932.
Abstract: We describe a suite of causal/predictive analysis techniques adapted from a variety of social, natural, and computational science applications, specifically chosen for their unique applicability to the problems of analyzing temporally offset causes and effects. In particular, we describe four methods for analyzing predictive/causal claims: (1) Granger causality is a well-established method from econometrics that can identify relationships between temporally offset causes and effects when the offsets are fixed; (2) forward-only dynamic time-warping (DTW) addresses uneven temporal offsets; (3) convergent cross mapping (CCM) can be used to analyze bi-directional causality produced by the feedback relationships present in many social systems; (4) finally, we describe a novel feature-based qualitative pattern-recognition approach to identify and explain qualitative causal/predictive relationships that don't fit more traditional correlation-based analysis techniques.
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Northeastern ACM Speaker Series

Date: 28 April 2003
Topic: The Importance of Robotics Development to Our Future

Abstract: It is no secret that future productivity depends on automation. What is less recognized is the importance of physical automation--robotics--to our future. As programmers we focus on informational automation and tend to see robotics as a sideline, one of many specialities, and one that is even a little distant because it appears hardware dependent. This may be an error in perception. Robotics is increasingly at the focal point of human development and software development is the single most important component of robotics. This talk will detail the pivotal role robotics has in our future and why it is crucial for computer scientists to take the lead in physical automation as well as informational automation.
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Developer Diary · about · · bio · Revised 9 February 2019 · Pure Content