Teaching Machines to Recognize Human Emotions with Entropik Tech and Intel – Intel on AI – Episode 49

Image for FaceBook

Share this post:
Facebook | Twitter | Google+ | LinkedIn | Pinterest | Reddit | Email
This post can be linked to directly with the following short URL:

The audio player code can be copied in different sizes:
144p, 240p, 360p, 480p, 540p, Other

The audio player code can be used without the image as follows:

This audio file can be linked to by copying the following URL:

Right/Ctrl-click to download the audio file.
Connected Social Media - iTunes | Spotify | Google | Stitcher | TuneIn | Twitter | RSS Feed | Email
Intel - iTunes | Spotify | RSS Feed | Email
Intel on AI - iTunes | Spotify | RSS Feed | Email

In this Intel on AI podcast episode: Knowing how a product or service makes a customer feel enables companies to make successful products that their customers enjoy. Yet measuring this traditionally takes a lot of time and effort through impact studies and advertising testing. Millions are spent on creating promotional materials that have little to no analytics behind them. The ability to analyze and measure a customer’s emotional reaction in real-time would be an incredibly valuable tool for many companies. Sumit Chauhan, a Data Scientist from Entropik Tech, joins the Intel on AI podcast to talk about how Entropik focuses on emotion AI to create technologies to detect human emotions through the monitoring of brainwaves, facial expressions, and eye tracking. He illustrates how Entropik’s Affect Lab, the Emotion AI platform is an emotionally intelligent consumer research platform that offers brands a chance to preview the performance of their creatives before launch and integrate the results to produce consumer-centric offerings that generate better ROIs. Sumit discusses how Entropik was able to work with Intel to better optimize their workloads to take advantage of the efficient multi-core processing of Intel Xeon Scalable processors, along with Dlib source build and Intel Distribution of Python to achieve significant improvement in Inference performance for their solution.

To learn more, visit:

Visit Intel AI Builders at:

Tags: , , , , , , , , , , ,
Posted in: Artificial Intelligence, Audio Podcast, Intel, Intel on AI