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Real-time conversational insights from phone call data

Invoca's Signal AI uses NLP model architectures to process phone call data and extract conversational insights, as discussed by ML engineer Mike McCourt.

Feb 17 · · primary fetch1 sourceupdated Feb 17 ·

Daniel and Chris hang out with Mike McCourt from Invoca to learn about the natural language processing model architectures underlying Signal AI. Mike shares how they process conversational data, the challenges they have to overcome, and the types of insights that can be harvested. Sponsors: Linode – Our cloud of choice and the home of Changelog.com. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code changelog2019 OR changelog2020. To learn more and get started head to linode.com/changelog. Brain Science – For the curious! Brain Science is our new podcast exploring the inner-workings of the human brain to understand behavior change, habit formation, mental health, and being human.

It’s Brain Science applied — not just how does the brain work, but how do we apply what we know about the brain to transform our lives. Featuring: Mike McCourt – GitHub, LinkedIn Chris Benson – Website, GitHub, LinkedIn, X Daniel Whitenack – Website, GitHub, X Show Notes: Mike McCourt | Invoca Employee Spotlight Invoca Signal AI Zipf’s law Meet the Data Scientists Behind Invoca’s Conversational Analytics Algorithms -Invoca raises $56 million to apply AI…

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  1. share.transistor.fmReal-time conversational insights from phone call dataprimary