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New Blender AMI with Mate Desktop, Turbo VNC Server, and VirtualGL

Last week we released several media related AMIs featuring a RESTful API interfaces. We received feedback, particularly on our Blender rendering AMI, that some of you would like to try and work directly with Blender via a remote session and a Desktop environment. Always listening to user feedback, this week we are releasing a Bitfusion Ubuntu 14 Blender AMI pre-installed with Nvidia Drivers, Cuda 7.5 Toolkit, Blender 2.77, and a complete Linux desktop environment including Mate Desktop, TurboVNC Server and VirtualGL for full 3D hardware acceleration of OpenGL applications when using remote display software.
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New Bitfusion Deep Learning and Media AMIs with REST APIs for Developers

Today we are introducing four new AMIs targeted at developers that want to offload compute intensive applications or tasks from their thin clients, laptops, or even mobile devices into the cloud where they can utilize vastly more powerful systems to get these tasks done orders of magnitude faster. The four new AMIs are as follows: Bitfusion Mobile Deep Learning Service, Bitfusion Mobile Image Manipulation Service, Bitfusion Mobile Rendering Service, and Bitfusion Mobile Video Processing Service. Each AMI comes with a simple REST API which can be used as is and for which we provide simple example scripts. Alternatively, you can build on top of our API and provide your own services or integrate these AMIs into your applications. Here are the details for each new AMI:
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New Bitfusion Nvidia Digits 3 and Cuda 7.5 AMIs

We've been been cooking up several more AMIs to get you started on AWS quickly. This time we are introducing the Nvidia Digits 3 AMI which is designed to to get you started quickly with Nvidia's deep learning package which includes their branched versions of Caffe and Torch, as well as a browser accessible interface for quick experimentation. The second AMI is built on top of Ubuntu 14, the Cuda 7.5 Toolkit, and the latest Nvidia drivers, and is targeted at Cuda developers and those intending to deploy GPU applications with ease.
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