“With the help of advanced sensors, AI, and communication technologies, it will be possible to replicate physical entities, including people, devices, objects, systems, and even places, in a virtual world,” the white paper states.

Sharing the full story, not just the headlines.

Machine-learning methods can predict the long-term stability of planetary configurations 100,000 times faster than previous approaches.

A new gadget called the OpenCV AI Kit, or OAK, looks to replicate the success of Raspberry Pi and other minimal computing solutions, but for the growing fields of computer vision and 3D perception. Its new multi-camera PCBs pack a lot of capability into a small, open-source unit and are now seeking funding on Kickstarter.

The OAK devices use their cameras and onboard AI chip to perform a number of computer vision tasks, like identifying objects, counting people, finding distances to and between things in frame and more. This info is sent out in polished, ready-to-use form.

Having a reliable, low-cost, low-power-draw computer vision unit like this is a great boon for anyone looking to build a smart device or robot that might have otherwise required several and discrete cameras and other chips (not to mention quite a bit of fiddling with software).

Recently, Tesla filed a patent called ‘Systems and methods for adapting a neural network on a hardware platform.’ In the patent, they described the systems and methods to select a neural network model configuration that satisfies all constraints.

According to the patent, the constraints mainly include an embodiment that computes a list of valid configurations and a constraint satisfaction solver to classify valid configurations for the particular platform, where the neural network model will run efficiently.

The Reason Behind the Patent.