MIT to Create Plant Cyborg

Elowan the robot with the plant drives to the light source necessary for photosynthesis
06 December 2018   745

Specialists at the Massachusetts Institute of Technology (MIT) have developed the Elowan robot, which is in a kind of symbiosis with the plant. A living organism uses electrical signals to control the movement of the robot.

So far, the system only responds to some changes, such as lighting a plant or a lack of water. Silver electrods are used to transmit signals, which are implanted in the leaves, roots and stem of the plant. The direction of movement of the robot depends on the strength of the impulse. For example, in one of the experiments, the robot on which the pot with the plant stood, itself drove up to the light source necessary for photosynthesis.

The algorithm looks like this: the plant needs light, this causes certain biochemical changes that generate an electrical impulse. The robot captures it, decrypts and executes the desired command.

In the future, such systems may be useful for automatic farms, where robots themselves will take care of plants, responding to their needs for light, water or nutrients. Such technologies will be used in agriculture on Earth, as well as in distant space expeditions, where it will be necessary to grow plants on board a ship.

Neural Network to Create Landscapes from Sketches

Nvidia created GauGAN model that uses generative-competitive neural networks to process segmented images and create beautiful landscapes from peoples' sketches
20 March 2019   372

At the GTC 2019 conference, NVIDIA presented a demo version of the GauGAN neural network, which can turn sketchy drawings into photorealistic images.

The GauGAN model, named after the famous artist Paul Gauguin, uses generative-competitive neural networks to process segmented images. The generator creates an image and transfers it to the discriminator trained in real photographs. He in turn pixel-by-pixel tells the generator what to fix and where.

Simply put, the principle of the neural network is similar to the coloring of the coloring, but instead of children's drawings, it produces beautiful landscapes. Its creators emphasize that it does not just glue pieces of images, but generates unique ones, like a real artist.

Among other things, the neural network is able to imitate the styles of various artists and change the times of the day and year in the image. It also generates realistic reflections on water surfaces, such as ponds and rivers.

So far, GauGAN is configured to work with landscapes, but the neural network architecture allows us to train it to create urban images as well. The source text of the report in PDF is available here.

GauGAN can be useful to both architects and city planners, and landscape designers with game developers. An AI that understands what the real world looks like will simplify the implementation of their ideas and help you quickly change them. Soon the neural network will be available on the AI ​​Playground.