Mei to Use AI to Improve Relationships

The application will help people fill in the gaps in communication
07 August 2018   403

Es Lee, a graduate of the computer science department at Harvard University, founded the Mei start-up. The application will help people fill in the gaps in communication, giving advice on how to respond in various situations. This is reported by Venture Beat.

Mei processes messages using algorithms that take into account the response time, laconicity, word selection and other factors. Based on these data, the application builds a psychological portrait of the interlocutor. Lee argues that algorithms can determine the age of the interlocutor only on the emoticons used. If you add text to it, the application will understand what kind of relationship between people and determine their strength. 

One of the difficulties of maintaining relationships through text is that it’s [possible] to come across as crass or rude — even when that was never the intention. Emotion is lost in text messages. It’s a different form of body language that people aren’t quite attuned to detecting yet.

Es Lee

Creator, Mei

In practice, AI calculates the percentage of compatibility, taking into account 5 personality factors: openness, goodwill, conscientiousness, emotionality and extraversion. At the same time, he additionally breaks each of them into sub-points (original, stubborn, polite, etc.), and also identifies features that most closely match the two interlocutors (for example, pride and seriousness).

Mei Screen
Mei Screen

Mei has been trained on millions of messages from more than 100,000 application users, data from two universities and team development team correspondence. The messenger uses double encryption of messages, and they can be deleted at any time, regardless of whether they were read or not. There are instant messages that are deleted as soon as they are sent or read. According to the developers, the application is developed thanks to the data received from users.

AI to be Used to Create 3D Motion Sculptures

The system developed by the MIT and Berkeley scientists is called MoSculp and is based on artificial inteligence
21 September 2018   119

MoSculp, the joint work of MIT scientists and the University of California at Berkeley, is built on the basis of a neural network. The development analyzes the video recording of a moving person and generates what the creators called "interactive visualization of form and time." According to the lead specialist of the project Xiuming Zhang, software will be useful for athletes for detailed analysis of movements.

At the first stage, the system scans the video frame-by-frame and determines the position of key points of the object's body, such as elbows, knees, ankles. For this, scientists decided to resort to the OpenPose library, developed by the Carnegie Mellon University. Based on the received data, the neural network compiles a 3D model of the person in each frame, and calculates the trajectory of the motion, obtaining a "motion sculpture".

At this stage, the image, according to the developers, suffers from a lack of textures and details, so the application integrates the "sculpture" in the original video. To avoid overlapping, MoSculp calculates a depth map for the original object and the 3D model.

MoSculp 3D Model
MoSculp 3D Model

The operator can adjust the image during the processing, select the "sculpture" material, color, lighting, and also what parts of the body will be tracked. The system is able to print the result using a 3D printer.

The team of researchers announced plans to further develop the MoSculp technology. Developers want to achieve from the processing system more than one object on the video, which is currently impossible. The creators of the technology believe that the program will be used to study group dynamics, social disorders and interpersonal interactions.

The principle of creating a 3D model based on human movements has been used before. For example, in August 2018, scientists at the same University of California at Berkeley demonstrated an algorithm that transfers the movements of one person to another.