Past is prologue1. In one interpretation it is that the past has predetermined the sequence which is about to unfold–and so I believe that how we have gotten to where we are in Artificial Intelligence will determine the directions we take next–so it is worth studying that past.
Read the full article here: http://rodneybrooks.com/forai-the-origins-of-artificial-intelligence/
A few years ago, Paul Allen, the co-founder of Microsoft, published the results of something called the Great Elephant Census, which counted all the savanna elephants in Africa.
Read the full article here: https://www.npr.org/2019/10/25/760487476/elephants-under-attack-have-an-unlikely-ally-artificial-intelligence
Organizations that hope to make AI a differentiator need to draw from alternative data sets — ones they may have to create themselves. Machine learning — or artificial intelligence, if you prefer — is already becoming a commodity.
Read the full article here: https://sloanreview.mit.edu/article/the-machine-learning-race-is-really-a-data-race/
Little-known companies are amassing your data — like food orders and Airbnb messages — and selling the analysis to clients. Here’s how to get a copy of what they have on you.
Read the full article here: https://www.nytimes.com/2019/11/04/business/secret-consumer-score-access.html
The boxes for prescription drugs typically include an insert of tissue-thin paper folded as tight as origami.
Read the full article here: https://medium.com/berkman-klein-center/from-technical-debt-to-intellectual-debt-in-ai-e05ac56a502c
Bill Benter did the impossible: He wrote an algorithm that couldn’t lose at the track. Close to a billion dollars later, he tells his story for the first time. Happy Valley Racecourse in Hong Kong. Photographer: Xyza Bacani for Bloomberg Businessweek.
Read the full article here: https://getpocket.com/explore/item/the-gambler-who-cracked-the-horse-racing-code