This is bonkers:

New AI breakthroughs in NVIDIA Maxine, cloud-native video streaming AI SDK, slash bandwidth use while make it possible to re-animate faces, correct gaze and animate characters for immersive and engaging meetings.

Instead of transferring your face at N frames per second, they transfer it once at the beginning of the call and then update key positions over time. The results are super impressive (and just a bit creepy?).

Google, Intel, and others have recently been targeting AI at the edge with things like Coral and the Neural Compute Stick, but NVIDIA is taking things a step farther. They just announced the Jetson Nano, which is a $99 computer with 472 GFLOPS of compute performance, an integrated NVIDIA GPU, and a Raspberry Pi form factor. According to NVIDIA:

The compute performance, compact footprint, and flexibility of Jetson Nano brings endless possibilities to developers for creating AI-powered devices and embedded systems.

And it’s not only for inference (which is the main target of things like Intel’s NCS). The Jetson Nano can also handle AI model training:

since Jetson Nano can run the full training frameworks like TensorFlow, PyTorch, and Caffe, it’s also able to re-train with transfer learning for those who may not have access to another dedicated training machine and are willing to wait longer for results.

Check it out! You can pre-order now.

PhysX is NVIDIA’s hardware-accelerated physics simulation engine that’s now released as open source to move it beyond its most common use case in the gaming world, to give access to the embedded and scientific fields — think AI, robotics, computer vision, and self-driving cars.

PhysX SDK has gone open source, starting today with version 3.4! It is available under the simple 3-Clause BSD license. With access to the source code, developers can debug, customize and extend the PhysX SDK as they see fit.