Divining For News – Veryan Goodship, Co-founder and CEO, Truba (truba.news) – How Artificial Intelligence Can Help To Tailor News, And Separate The Wheat From The Chaff

Veryan Goodship, Co-founder and CEO of Truba (truba.news), provides a detailed discussion on his company's technology-based news delivery, and how it was born of specific needs that occurred within the Canadian Financial Industry.

The Canadian economics graduate discusses his startup's mission to rethink the ways in which users receive news in our 24-hour, complex, streaming and constant news-heavy world. The news tech CEO outlines how current problems with the dissemination of news has created a situation where many people are actually less informed than perhaps pre-tech times.

Goodship explains how his company, Truba, works to deliver news via various methods that tailor a reader's news to their interests, in formats that they are comfortable with and may find more convenient. One such method is via Truba's "Daily Snap" product, which provides readers top-trending news that would be available through social media but through a newsletter format that allows the user to avoid social media altogether. Additionally, Truba provides personalized news feeds that are comprised from a particular user's click data input.

Essentially whatever the analytics have demonstrated the user is interested in due to their clicks and links followed, etc., would become the foundation for a tailored news platform. One of the benefits of this offering is that it can provide the interested reader with personalized news without the fear of being targeted or marketed to, or the fear of having their data being sold to third parties.

Goodship discusses the process that Truba uses to personalize a reader's news platform, including inputting of initial user information and the training of algorithms through user input. And he'll provide insight into how the AI algorithms use linear regression to decipher which features are most important.

The news tech CEO gives an overview of the many and various input that are used to customize news feeds, from term frequencies (such as how often terms show up in text), to term comparison, to title sizes and more. And he'll give us some notes on how machine vision (recognition of pictures and video) and audio analyzation (wave length and speed) play a part in the process of news selection algorithms.