In AI/ML, data and computing power are resources that go hand-in-hand. So, as our datasets and databases have grown over the years, so too has the demand for computing power. While it is possible to make use of cloud computing services such as those offered by Microsoft, IBM, Google etc. such an approach can be costly and at times cumbersome. In the last year Nvidia has introduced its Xavier computer as a powerful and efficient solution for developers seeking to prototype their ideas.
The Xavier is an AI computer that delivers the performance of a high-end GPU workstation in an embedded module that operates at 30W or less. Containing a 512-core Volta GPU, 8-core 64-bit CPU, and a 16GB Memory, it’s hard to believe that all of that power can fit in the palm of your hand!
So, you can expect that this is an exciting new piece of technology for all the AI Scientists, ML Engineers, and Data Analysts around the world that are bonded together by our shared need computing power and have ever felt limited by the amount of computing power available to them.
This post will hopefully help anyone who has obtained a Xavier and would like some guidance on how set it up, install a few packages, and configure device behaviour.
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