Artificial Intelligence in Industry with Dan Faggella

Episode summary: This week on AI in Industry, we speak to Rana el Kaliouby, Co-founder and CEO of Affectiva about how machine vision can be applied to detecting human emotion - and the business value of emotionally aware machines.

Enterprises leveraging cameras today to gain an understanding of customer engagement and emotions will find Rana’s thoughts quite engaging, particularly her predictions about the future of marketing and automotive.

We’ve had guests on our podcast say that the cameras of the future will most likely be set up for their outputs to be interpreted by AI, rather than by humans. Increasingly machine vision technology is being used in sectors like automotive, security, marketing, and heavy industry - machines making sense of data and relaying information to people. Emotional intelligence is an inevitable next step in our symbiotic relationship with machines, an in this interview we explore the trend in depth.

Interested readers can listen to the full interview with Rana here: https://www.techemergence.com/can-businesses-use-emotional-intelligence

 

Direct download: AI_in_Industry-Rana_el_Kaliouby-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 12:00pm PDT

A myriad of customer service channels exist today, such as social media, email, chat services, call centers, and voice mail. There are so many ways that a customer can interact with a business and it is important to take them all into account.

Customers or prospects who interact via chat may represent just one segment of the audience, while the people that engage via the call center represent another segment of the audience. The same might be said of social media channels like Twitter and Facebook.

Each channel may offer a unique perspective from customers – and may provide unique value for business leaders eager to improve their customer experience. Understanding and addressing all channels of unstructured text feedback is a major focus for natural language processing applications in business – and it’s a major focus for Luminoso.

Luminoso founder Catherine Havasi received her Master’s degree in natural language processing from MIT in 2004, and went on to graduate with a PhD in computer science from Brandeis before returning to MIT as a Research Scientist and Research Affiliate. She founded Luminoso in 2011.

In this article, we ask Catherine about the use cases of NLP for understanding customer voice – and the circumstances where this technology can be most valuable for companies.

Read the full article:

techemergence.com/improving-customer-experience-with-ai-gaining-quantifiable-insight-at-scale

Direct download: AI_in_Industry-Catherine_Havasi-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 7:55pm PDT

Episode summary: In this episode of AI in Industry, we speak with Khalifeh Al Jadda, Lead Data Scientist at CareerBuilder, about the applications of machine learning in improving a user’s search experience.

Khalifeh also talks about what the future of search might look like and how AI will continue to make the search experience more intuitive (for search engines, platforms, eCommerce stores, and more).

Business leaders listening in will get a sneak peak into the future of online search - and an understanding of how and where improvements in search features could impact their business.

Interested readers can listen to the full interview with Khalifeh here:

https://www.techemergence.com/better-than-elasticsearch-machine-learning-search/

Direct download: AI_in_Industry-Khalifeh_Al_Jadda-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 1:48am PDT

Episode summary: In this episode of AI in Industry, we speak with Andy Terrel, the Chief Data Scientist at REX - Real Estate Exchange Inc., about how AI is being used in the real estate sector today.

Looking ahead ten years into the future, Andy paints a picture of the areas where he believes AI will change the real estate business. Andy explores how marketing in real estate might change in the future with chatbots and conversational interfaces in real estate which are high value per ticket interactions - a process that will likely vary greatly from the chatbot applications we see for smaller B2C purchases (in the fashion sector, eCommerce, etc).

Interested readers can listen to the full interview with Andy here:

https://www.techemergence.com/ai-use-cases-future-real-estate/

Direct download: AI_in_Industry-Andy_Terrel-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 5:14am PDT

Episode summary: Here on the AI in Industry podcast, we’ve heard AI experts explain how high-performance computing (HPC) has enabled everything from machine vision to fraud detection. In this week’s episode, we speak with Paul Martino, Managing Partner at Bullpen Capital, about which industries and AI applications will require high-performance computing most.

Paul also adds some useful tips for business leaders on how to prepare for the coming AI-related developments in hardware and software.

Interested readers can listen to our full interview with Paul here: https://www.techemergence.com/?p=12779&preview=true

 

 

Direct download: AI_in_Industry-Paul_Martino-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 7:40am PDT

Episode summary: In this episode of AI in Industry, we speak with Dr. Sanmay Das from the Washington University in St. Louis about risk prediction and management in industries like banking, insurance and finance.

Sanmay explores how are banks and other financial institutions are improving risk and fraud prevention measures with machine learning. In addition, he explores the ramifications of improved fraud detection in the coming 5 years ahead.

Interested readers can listen to the full interview with Sanmay here: https://www.techemergence.com/machine-learning-for-credit-risk/

Direct download: AI_in_Industry-Sanmay_Das-Mixdown.mp3
Category:Artificial Intelligence -- posted at: 2:30am PDT

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