Episode 13: Tapping into the Power of Natural Language Processing with Jason Brenier

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This is a podcast episode titled, Episode 13: Tapping into the Power of Natural Language Processing with Jason Brenier. The summary for this episode is: Natural language processing (NLP) is a growing application of artificial intelligence. It can bring tremendous value to your client interactions and take your company down entirely new paths of process automation. In this episode, Jon Prial talks to Jason Brenier, CTO of Idibon, a San Francisco based company that provides cloud-based natural language processing services. Find out how your business can benefit from this amazing technology. You’ll hear about: -What Idibon does and how (1:03) -Idibon’s biggest challenge taking machine learning from research to applications (2:31) -What NLP is and the four things you can do with it (5:58) -Using NLP as the building blocks for more sophisticated systems (8:02) -What CEOs need to do leverage NLP within their existing infrastructure (9:50) -The type of skills that companies should be hiring for to succeed in the space (12:30) -Data needs for doing NLP (14:06)

DESCRIPTION

Natural language processing (NLP) is a growing application of artificial intelligence. It can bring tremendous value to your client interactions and take your company down entirely new paths of process automation. In this episode, Jon Prial talks to Jason Brenier, CTO of Idibon, a San Francisco based company that provides cloud-based natural language processing services. Find out how your business can benefit from this amazing technology. You’ll hear about: -What Idibon does and how (1:03) -Idibon’s biggest challenge taking machine learning from research to applications (2:31) -What NLP is and the four things you can do with it (5:58) -Using NLP as the building blocks for more sophisticated systems (8:02) -What CEOs need to do leverage NLP within their existing infrastructure (9:50) -The type of skills that companies should be hiring for to succeed in the space (12:30) -Data needs for doing NLP (14:06)