DeepMind to Test AI's IQ

Most models answered questions with an accuracy of 75%
12 July 2018   368

DeepMind, a subsidiary of Google, talked about the experiment with testing artificial intelligence models on generalization skills and abstract thinking. Specialists have developed a generator that formulates questions based on the notion of progression, color properties, shapes or sizes and their interrelationships. Similar tasks are encountered in IQ tests for people.

Most models answered questions with an accuracy of 75%. At the same time, researchers found a strict correlation between the effectiveness of tasks and the ability to identify the underlying abstractions. They managed to increase efficiency by training algorithms to explain their answers, to show what interrelations and properties should be considered in one or another issue.

However, in some models it is difficult to "transfer" the studied relationships to new properties, for example, if it trained to identify logical sequences relative to the color of objects, and in the task it is required to establish the dependence on their form.

The team found out that if the neural network correctly extrapolated its knowledge of the relationship to a new combination of values, then the accuracy of the tasks was increased to 87%. In the case of incorrect extrapolation, it fell to 32%.

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   134

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.