I recently ran across a thought-provoking post on the USC Anneberg Innovation Lab blog – “Why Do We Need Data Science when We’ve Had Statistics for Centuries.” With all the debate of late surrounding the relatively new “data science” term, I’ve been thinking a lot about this question, so I thought I’d analyze this notion […]
An eye-catching piece appearing in today’s edition of The Independent featured the thoughts of luminaries from the scientific world – renowned physicist Stephen Hawking, U.C. Berkeley computer-science professor Stuart Russell, and MIT physics professors Max Tegmark and Frank Wilczek – about the potential perils of artificial intelligence.
Unsupervised machine learning techniques have proven useful in identifying fake research papers submitted to the arXiv preprint server. Approximately 500 preprints are receiving daily by the automated repository arXiv, but are not pre-screened by humans. As a result, many nonsense papers generated by software such as SCIgen and Mathgen have been found in the most popular repository used by scientists to share research results.
If you’ve ever spent valuable billable hours time thinking about an algorithm to seek out the optimal cheeseburger, and calculate metrics like the maximal meat-to-bun ratio, then this presentation by noted data scientist Hilary Mason at the Ignite NYC event last year is for you. Hilary, a self-admitted cheeseburger lover, found some data sets in […]
At year end 2013, a probing article appeared in CMS Wire, “The End of Data Scientists and Other Predictions.” I remember reading it at the time and thinking to myself, “Oh well, I better fire up a screenplay template in Word like everyone else here in LA and start typing because I’ll be out of work soon.”