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Startup's Sorting Machines Use AI to Protect Healthy Fish Eggs


Fisheries collect millions upon millions of fish eggs, protecting them from predators to increase fish yield and support the propagation of endangered species -- but an issue with gathering so many eggs at once is that those infected with parasites can put healthy ones at risk. Jensorter, an Oregon-based startup, has created AI-powered fish egg sorters that can rapidly identify healthy versus unhealthy eggs. The machines, built on the NVIDIA Jetson Nano module, can also detect egg characteristics such as size and fertility status. The devices then automatically sort the eggs based on these characteristics, allowing Jensorter's customers in Alaska, the Pacific Northwest and Russia to quickly separate viable eggs from unhealthy ones -- and protect them accordingly. Jensorter is a member of NVIDIA Inception, a program that nurtures cutting-edge startups revolutionizing industries with advancements in AI, data science, high performance computing and more.

AWS beats Google and Microsoft to launching instances with Nvidia Volta GPUs


Amazon Web Services is the first cloud to launch new compute instances that allow developers to build applications that tap into Nvidia's new generation of Volta GPUs, which are designed to provide high-performance acceleration for applications like AI computation. Companies all over are turning to machine learning to help propel their businesses, but building new models often requires a great deal of computation. The Volta is supposed to be a good deal faster at that than past generations of Nvidia's silicon, and making it available through Amazon's cloud means that companies will be able to get started using them right away. Customers will be able to run instances with up to 8 V100 GPUs, which will be made available initially from AWS's Northern Virginia, Oregon, Ireland, and Tokyo datacenters. Nvidia launched a new GPU Cloud offering alongside AWS, which is designed to provide companies with the most optimized environment for running deep learning applications on top of the company's hardware in a public cloud.