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    The Degree of Impact Deep Learning Can Make On The Transportation Sector

    By Apac CIO Outlook | Monday, December 03, 2018
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    Trending technologies such as artificial intelligence, machine learning, and deep learning have been permeating into almost every sphere of life today. The impact of deep learning on the transportation sector during recent times is an interesting development, which definitely deserves a mention. Industry veterans opine that better utilization of deep learning can solve several challenges plaguing the sector for many decades. Several online resources have recently stated that deep learning has been disrupting the transportation sector. Industry veterans have estimated that by 2025, the deep learning market would reach a staggeringly high figure, a little more than around $10 Billion. Deep learning has been incredibly useful in the prediction of traffic flow, which is easily one of the greatest challenges plaguing the transportation sector for decades. Adoption of deep learning in traffic management across several towns has already helped in overcoming the challenges of traditional traffic decongestion approaches.

    Deep learning is highly useful in data analysis and unearthing insights with the ability to empower the transportation sector.  The cutting-edge discipline has ushered several changes in the transportation sector during recent times. The best example probably is the increase in popularity of smart self-driving cars which have the ability to maneuver through hurdles and require little to no intervention of a human. It is believed that the increase in adoption of such self-driving cars will reduce the probabilities of accidents in the days to come.

    A popular instance of a self-driving vehicle is Olli, an automobile that has grabbed the world's attention for its capabilities. Designed by a reputed motor manufacturer, this vehicle is equipped with several capabilities. Interestingly, the vehicle also suggests places of interest during a journey and it is widely believed that Olli would be one of the most desirable automobiles of the near future.

    These examples clearly illustrate the potential of deep learning and have proved that the discipline will greatly empower the transportation sector. Intelligent adoption of deep learning can work wonders for any organization.

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