Got sarcasm?

I'm being sarcastic." We've all had at least one exchange in which we either had to explain or had someone else explain that what was said was not intended to be taken straight. Generally, you need to know something about both the context and the speaker to grasp when to take a statement at face value or interpret it as sarcastic.

That's why it's particularly challenging to get handle on intent when attempting sentiment analytics on social media. For artificial intelligence to truly understand what humans mean, it needs emotional intelligence, as well. Iyad Rahwan, an associate professor the MIT Media lab and one of his students, who developed the algorithm with one of, Bjarke Felbo worked on just that.

The results are what they call Deep Moji. Described as "artificial emotional intelligence," Deep Moji was trained on millions of emojis "to understand emotions and sarcasm." Rahwan explained to MIT's Technology Review that in the context of online communication emojis take on the function of body language or tone in offering nonverbal cues for meaning.

Read more in Emojis Train AI to Recognize Sarcasm

Getting insight on all the channels with AI

Marketers have access to more data on their customers than ever before. The challenge is getting rapid insights from all the channels used, in time to act effectively. One solution is an  AI-powered customer retargeting platform for omni-channel marketing operations. Abhi Yadav, ZyloTech's  co-founder and CEO, spoke to me about the function of AI in omni-channel marketing.

ZyloTech, formerly DataXylo, launched in 2014 as an MIT spin off. Its advisory teams includes PhDs in AI, data scientists, and other marketing experts from the university. The platform uses machine learning to analyze all customer data continuously, and in near real time, for actionable insights on omnichannel marketing.

In the current environment, marketers really have “no way of knowing whether the individual” targeted by the ad “is a new, lost, inactive, loyal or brand-conscious customer,”  says Yadav.

Read more in An AI Approach to Omnichannel

Got rhythm? This algorithm does.

from https://commons.wikimedia.org/wiki/File:Rap-logo-persian-wiki.png

Most of us have heard of DeepBlue, the computer that harnessed artificial intelligence to beat a chess champion back in 1997. Now there’s DeepBeat, a machine learning algorithm that raps.

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An Algorithm Gets Rhythm

The science of empathy

"You never really understand a person until you consider things from his point of view, until you climb in his skin and walk around in it," declares Atticus Finch in Harper Lee's To Kill a Mockingbird. Gaining that kind of empathic insight is helpful not only for fostering humanity, but for improving business results....

Ultimately, there is no magical question that will elicit what the C-suite and IT leaders need to know about their customers. In fact, some customers may not even be able to articulate exactly what caused them to feel less than satisfied. The solution to that problem is not magic, but science.


Even when people can't find words for what they are feeling, sensors can pick up on the signs of stress that, when combined with contextual data, can reveal the emotional triggers that define a customer's experience. That's where design consultant Elliot Hedman comes in. Experience designer at mPath, Hedman has developed a methodology that combines stress-testing sensors with traditional observational techniques.

Graph from mPath

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Can Data Teach Us Empathy?

Planning a supply chain for space

photo from https://upload.wikimedia.org/wikipedia/commons/c/c7/Carina_Nebula_composite_of_visible_and_infrared_light_(captured_by_the_Hubble_Space_Telescope).jpg

The replicator that can produce food, clothes, and other necessities on demand is familiar to all devotees of Star Trek. That device was actually essential for the Enterprise's extended mission, to keep the ship properly equipped without having to pack along whatever the crew might need at some point light years away from a home planet. Though such replicators are still in the realm of science fiction, we are getting closer to the point of extended space trips.

Going back to the moon and maybe even Mars
NASA just finalized a $2.8 billion contract with Boeing Co. to produce the Space Launch System (SLS). SLS is a rocket powerful enough to carry astronauts where no human has gone before. That includes exploration of asteroids, the moon, and, ultimately, Mars. The first test flight is planned for 2017, and the first manned flight for 2021.

While Boeing is working on NASA's rockets, MIT is working on supply chain management that solves the logistical challenges inherent in extended space travel. 

Read more in 

Space & the Supply Chain

Your email organized

Imagine coming into your office and finding all your files rearranged for better organization. You get a note saying: “You’ll now find your important files here, your social media files here, and your promotions over there.”

That’s just about what Gmail did with inboxes a few weeks back. While I don’t really mind having my email organized according to the Gmail system, Google's ability to make the change really drove home the point to me that email metadata is open for use.
Read more in Learning About You From Your Email Metadata.

Pictured here is an example of the raw metadata sent to me by the Immersion team at MIT.

3D printing really takes off with the help of big data

The only thing holding GE back from fully integrating 3D printing was insufficient data to assure uniform results. "A part is made out of thousands of layers, and each layer is a potential failure mode," Prabhjot Singh, head of the GE lab working on such processes, told MIT Technology Review. "We still don't understand why a part comes out slightly differently on one machine than it does on another, or even on the same machine on a different day."Now GE has come up with a big data solution to that problem.

Read more in 

Big Data Helps 3D Printing Take Off