Tesla to Open Security Software Source Code

Elon Musk believes that this is extremely important to a safe self-driving future for all
14 August 2018   717

Tesla intends to open the source code of the security system of its cars for third-party manufacturers. This was announced by Elon Musk after the DEF CON conference in Las Vegas. He also thanked the participants for improving the protection of the Tesla and SpaceX software.

With the opening of the source code, the technology of protection of electric cars Tesla will be free to use any auto concern. Security software should protect cars from intruders who are able to hack electric cars and gain access to remote control.

Great Q & A at defcon last night. Thanks for helping make Tesla & SpaceX more secure! Planning to open-source Tesla vehicle security software for free use by other car makers. Extremely important to a safe self-driving future for all.

Elon Musk

Founder, Tesla, SpaceX, Hyperloop, Boring Company

With the use of technology by competing companies, Tesla development companies can become a standard for car safety. Assistance to third-party firms in strengthening the protection of electric cars from burglary can positively affect the reputation of the company.

In May 2017, Ilon Mask announced the lack of reliability of automatic driving systems. However, according to his forecasts, in 2019 cars can already ride without the help of the driver.

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   138

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.