AI System to Create Drugs From Scratch

ReLeaSE (Reinforcement Learning for Structural Evolution) system can speed up the emergence of new medicines
03 August 2018   622

Scientists of the pharmaceutical school Chapel Hill Eshelman based at the University of North Carolina have developed a system called ReLeaSE, which can create molecules of drugs "from scratch". This can speed up the emergence of new medicines.

ReLeaSE (Reinforcement Learning for Structural Evolution) is a computer program consisting of two neural networks, which can be conditionally called a "student" and a "teacher". The algorithm works as follows:

  1. "Teacher" knows the properties and characteristics of the interaction of more than 1.7 million biologically active molecules and shares this information with the "student".
  2. "Student" in the process of mastering knowledge offers new molecules that can be used to create medicines.
  3. "Teacher" approves an effective molecule, laying down information about it in the memory of the "student", preventing similar mistakes in the future.

If we compare this process to learning a language, then after the student learns the molecular alphabet and the rules of the language, they can create new 'words,' or molecules. If the new molecule is realistic and has the desired effect, the teacher approves. If not, the teacher disapproves, forcing the student to avoid bad molecules and create good ones.
 

Alexander Tropsha

Creator, ReLeaSE

The team of scientists has already been able to generate molecules with the desired properties (desired bioactivity, safety profiles) and individual physical characteristics (melting point, water solubility, enzyme effect) using ReLeaSE.

Neural Network Now Can Animate People on Photos

Algorithm can even make people on the photos to 'go out' picture's borders
12 December 2018   110

Researchers at the University of Washington, together with the developers of Facebook, have created an algorithm that “revives” people in the photographs. In a single snapshot, it generates a three-dimensional moving model of a figure that can sit, jump, run, and even "go" beyond the limits of the image. The algorithm also works for drawings and anime characters.

To create such a technology, researchers used the experience of colleagues.

  • Mask R-CNN recognizes a human figure in the image and makes it stand out from the background.
  • Another algorithm imposes a simplified skeleton markup on the shape, defining how it will move.
  • The third algorithm "fills" the background space, previously hidden by the figure.

Further, the own algorithm of researchers on the basis of a marked two-dimensional figure creates a three-dimensional model and generates a texture level from the original image.

The developers added a user interface that allows you to change the shape of the figure in order to edit the photo itself or determine where the animation will begin. In addition, you can “revive” a drawing or photo in augmented reality and see a three-dimensional figure in VR or AR glasses.