Episode 16: Using Natural Language Generation to Give Your Data a Voice

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This is a podcast episode titled, Episode 16: Using Natural Language Generation to Give Your Data a Voice. The summary for this episode is: Natural language generation (NLG) is a technology that allows companies to take vast quantities of data and turn them into compelling narratives that communicate the valuable insights they contain. In this episode, Jon Prial talks to Stuart Frankel, the CEO and Co-Founder of Narrative Science. Find out about the amazing advances in NLG technology and how this particular type of artificial intelligence is changing the way that many companies do business. You'll hear about: -Narrative Science and how it helps data rich companies become more efficient(1:03) -The difference between natural language processing and natural language generation (3:12) -Why NLG projects have to start with communication goals, not data (5:29) -The limits of data visualization (8:01) -Turning various types of data into narratives (9:59) -Why Narrative Science initially didn’t call itself an AI company (16:15) -Leveraging other AI engines versus doing everything yourself (18:11) -Measuring success and getting better with AI solutions (20:08) -Approaching the many aspects of AI to create a successful strategy (21:29) -The maturity of the NLG industry (23:06) -Where CEOs should start with AI (24:15)

DESCRIPTION

Natural language generation (NLG) is a technology that allows companies to take vast quantities of data and turn them into compelling narratives that communicate the valuable insights they contain. In this episode, Jon Prial talks to Stuart Frankel, the CEO and Co-Founder of Narrative Science. Find out about the amazing advances in NLG technology and how this particular type of artificial intelligence is changing the way that many companies do business. You'll hear about: -Narrative Science and how it helps data rich companies become more efficient(1:03) -The difference between natural language processing and natural language generation (3:12) -Why NLG projects have to start with communication goals, not data (5:29) -The limits of data visualization (8:01) -Turning various types of data into narratives (9:59) -Why Narrative Science initially didn’t call itself an AI company (16:15) -Leveraging other AI engines versus doing everything yourself (18:11) -Measuring success and getting better with AI solutions (20:08) -Approaching the many aspects of AI to create a successful strategy (21:29) -The maturity of the NLG industry (23:06) -Where CEOs should start with AI (24:15)