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Artificial Intelligence: Healthcare Discussion at AI Conclave 2020 DRG Blog DRG

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On January 24th, DRG's Garima Kaul, Sr. Director Biopharma Insights, was one of four invited panelists who spoke on the application of artificial intelligence at AI Conclave 2020. The conference was organized by BML Munjal University at the India Habitat Centre, New Delhi, India and included representatives from industries such as banking, finance, and consulting. Below, Garima recaps the discussion that took place on the application of AI in the healthcare industry. A person may order an item through an e-commerce website and be guided to other frequently bought items and then subsequently log-on to a social media account and see similar recommendations in their feed. What may seem like an invisible hand in the background moving items into view, is AI running pattern-based algorithms, curating data and information based on consumer preferences.


How will Artificial Intelligence and Internet of Things change the world.

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Are you finding it difficult to understand trends in Artificial Intelligence (AI) and the Internet of Things (IoT)? Join AI&IoT Summit - 6-7 June 2018, New Delhi http://ai-iotsummit.com/?utm_source y... Know more at- https://geospatialworldforum.org/ai-a... #gis #AI #IoT Video Courtesy- 1. TIA NOW 2. LinkedIn Learning Solutions 3. AT&T Business 4. Qualcomm 5. Prime Minister's Office of Japan 6.


Machines are 25% more efficient than humans in hiring right talent: TeamLease

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New Delhi: Hiring based on machine learning is 20-25% more efficient than manual hiring, a survey by recruitment and staffing company TeamLease showed. The report'The New Landscape of Hiring', shared exclusively with Mint, says the time, cost and attrition rates in machine-based hiring are lower than in manual hiring. Machine learning-based hiring is a process in which recruiters can use algorithms powered by machine learning to hire candidates. "With machine hiring, one could estimate attrition (early/premature as well as long-term) likelihoods and therefore choose candidate types that are associated with lower likelihoods. This is a rare (or not a) possibility in case of manual hiring unless data is manually captured and analysed," said Rituparna Chakraborty, co-founder and executive vice-president, TeamLease.