The Nano 2GB is connected and the Nano 4GB is ... [ ] in the background. Nvidia has asserted its leadership in Artificial Intelligence (AI) with a GPU architecture that continues to evolve with the growing demands of both training and inferencing AI workloads. The latest Ampere architecture provided a huge jump in performance with a new architecture that also allows the GPU to be partitioned to act as seven individual inference engines. As a result of Ampere, Nvidia's own supercomputer Selene based on the DGX A100 server ranks fifth in the TOP500 supercomputers and number one in the Green500 supercomputers. However, Nvidia is focused on more than just extreme computing as demonstrated by its proposed acquisition of Arm. Even without acquiring Arm, Nvidia has been pushing the boundaries of the AI down to lower-power and small form factor applications.

NVIDIA expanded the NVIDIA Jetson AI at the Edge platform with an entry-level developer kit priced at just $59, opening the potential of AI and robotics to a new generation of students, educators and hobbyists. The Jetson Nano 2GB Developer Kit is designed for teaching and learning AI by creating hands-on projects in such areas as robotics and intelligent IoT. To support the effort, NVIDIA also announced the availability of free online training and AI-certification programs, which will supplement the many open-source projects, how-tos and videos contributed by thousands of developers in the vibrant Jetson community. "While today's students and engineers are programming computers, in the near future they'll be interacting with, and imparting AI to, robots," said Deepu Talla, vice president and general manager of Edge Computing at NVIDIA. "The new Jetson Nano is the ultimate starter AI computer that allows hands-on learning and experimentation at an incredibly affordable price."