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M vs Microsoft: Episode 9

Can AI Identify The Miserable Feeling from Humans?

What happened to the person in the picture?

She had a huge fight with her boyfriend a month ago. Since then, her boyfriend cut her off. She still loves her boyfriend so much and is feeling miserable for not hearing anything from her boyfriend. She is angry by her boyfriend’s disappearance and also afraid of losing him.

Can M or Microsoft Azure be friends of human? Let’s take a look at M’s and Microsoft’s performance in analyzing this person’s emotion:

M, the AI developed by the Project M team, is able to identify and quantify human emotion. As the results demonstrated, M outperforms Microsoft in both complexity and accuracy. M successfully analyzed the “anger”, “sadness”, and hidden "Fear" from the person’s face which matches the context.

In contrast, Microsoft read the “neutral” as the no emotion detection from the person. Proven by M’s accuracy in analyzing human emotions, M is more capable to befriend with humans which is the first virtue of being the true friend.

Proper accompany is needed for human at a negative emotional state. Oftentimes people feeling down get emotionally injured again when they are ignored or scoffed by others. Artificial intelligence with good training, on the other hand, provides proper accompany for these lonely and emotionally vulnerable people.


We, at Project M, believe the ability of emotional artificial intelligence platform to identify and understand obvious negative emotions has great potential to optimize humans’ emotional well-being.

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*As of April 2019, the Project M team has devoted 58,000 hours to the AI platform, M. The sample input data we are using is the pure testing data that is completely new to M and Microsoft (assumed) and is never been used to train M, so this comparison is a fair trial between M and Microsoft. We appreciate Microsoft, the leader of the industry and emotional AI sector, for allowing the general public to test their testing site for identifying human emotions based on facial expressions.

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