Online shopping accounts for only 8.4 percent of all retail sales in the United States, but it has had an outsize effect on the retail workforce. The hundreds of thousands of jobs created by new online firms have not absorbed the job losses at traditional retailers. At the same time, the new jobs are concentrated in a handful of large cities and tech hubs.
Online retailers can sell more products with fewer workers than traditional stores. Nearly three-quarters of e-commerce firms have four or fewer employees. Even though online companies pay higher average wages to their workers, they have a bigger impact on retail sales than on retail employment. Click here to read the full article.
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This year, IBM will introduce Cognitive Highlights, a cutting edge project that will use artificial intelligence to give fans front-row seats to all the biggest moments from the tournament.
The system works by combining information recorded by an on-court statistician with data from an array of different sensors. Everything from the number of aces accomplished by a particular player to the speed of individual serves is taken into account. Cognitive Highlights pairs this data with an analysis of how the crowd responded to particularly exciting moments. The system was trained to recognize cheering from the crowd and how players reacted, using audio and video footage gathered at previous iterations of the Championships. Click here to read the full article. The system, called DeepText, is based on recent advances in artificial intelligence and a concept called word embeddings, which means it is designed to mimic the way language works in our brains. When the system encounters a new word, it does what we do and tries to deduce meaning from all the other words around it.
White, for instance, means something completely different when it’s near the words snow, Sox, House, or power. DeepText is designed to operate the way a human thinks, and to improve over time, like a human too. The machines give each comment a score between 0 and 1, which is a measure of Instagram’s confidence that the comment is offensive or inappropriate. Above a certain threshold, the comment gets zapped. As with spam, the comments are rated based both on a semantic analysis of the text and factors such as the relationship between the commenter and the poster, as well as the commenter’s history. Something typed by someone you’ve never met is more likely to be graded poorly than something typed by a friend. Click here to read the full article. |
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