AI is revolutionizing neuromarketing

AI is revolutionizing neuromarketing on @venturebeat  #INBOUND17 #ai #ml

  • In recent years, AI has offered a huge boost to neuromarketing — the science of reading consumers’ minds to gauge their reactions to marketing stimuli.
  • When combined with AI-based facial recognition, biometric insights can offer even more accurate data about consumers’ responses to marketing messaging.
  • IBM’s Watson — the company’s computer system that answers questions delivered in natural language — doesn’t use biometric data to gauge the excitement at an event.
  • What makes these methods more than merely interesting is the fact that they provide the means to obtain data about consumers’ emotional reactions in real time and adjust marketing messages accordingly.
  • Once AI is fully adopted in neuromarketing processes, marketers will have the ability to call on consumers to crowdsource their marketing campaigns without the fear of collecting unreliable data.

An unfortunate fact about humanity is that people lie. While this is a chronic issue for human relations, it’s one that may be less of an issue for marketers of the future, thanks to non-human intervention.
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Applying Deep Learning at Cloud Scale, with Microsoft R Server & Azure Data Lake

Applying Deep Learning at Cloud Scale, w/ Microsoft R Server & Azure Data Lake

  • Figure 4: Generating training data in parallel using Microsoft R Server.
  • We present the final tagged test image in Figure 8 where cars and boats are labeled with red and green bounding boxes respectively; you can also download the image .
  • Each worker node returns a labelled list of moving window tile coordinates, which is then used to label the final test image in MRS running on HDInsight Spark edge node.
  • We compress 2.3 million training images from 8.9GB of raw PNG images to 5.1GB with im2rec binary in 10 minutes for optimal training performance.
  • MXNet DNN model training using NVIDIA Tesla K80 GPU using Microsoft R Server (MRS).

This post is by Max Kaznady, Data Scientist, Miguel Fierro, Data Scientist, Richin Jain, Solution Architect, T. J. Hazen, Principal Data Scientist Manager, and Tao Wu, Principal Data Scientist Manager, all at Microsoft.

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Neural Networks for Artists

Visuals provide an engaging entry point to the world of deep machine learning

  • ” Imagine your vacation photos rendered in the style of Pablo Picasso, or Leonardo da Vinci’s Mona Lisa painted in the style of Vincent Van Gogh’s Starry Night.
  • For more examples of both static and video style transfer, as well as a near real-time style transfer “mirror,” (!) see Kogan’s website .
  • For a few visual explanations of how deep learning works, check out ” Unveiling the Hidden Layers of Deep Learning. “
  • The first renders the video in the style of Van Gogh’s Starry Night.
  • Style is such an abstract concept to us, which is what makes algorithms inferring it so interesting, even when it’s not aesthetically pleasing.

Read the full article, click here.


@sciam: “Visuals provide an engaging entry point to the world of deep machine learning”


From hallucinogenic-like DeepDream composites to mesmerizing style-transfer videos, visuals provide an engaging entry point to the world of machine learning


Neural Networks for Artists