Amazon introduced AWS Deep Learning Containers, a collection of Docker images preinstalled with preferred deep learning frameworks, with the aim of making it more seamless to get AI-enabled apps on Amazon Web Services. At AWS, general manager of deep learning Dr. Matt Wood noted that the company has “done all the hard work of building, compiling, and generating, configuring, optimizing all of these frameworks,” taking that burden off of app developers. The container images are all “preconfigured and validated by Amazon.” Continue reading AWS Tool Aims to Simplify the Creation of AI-Powered Apps

Intel revealed that it has made progress in an anonymized, encrypted method of model training. Industries such as healthcare that need a way to use AI tools on sensitive, personally identifiable information have been waiting for just such a capability. At the NeurIPS 2018 conference in Montreal, Intel showed off its open-sourced HE-Transformer that works as a backend to its nGraph neural network compiler, allowing AI models to work on encrypted data. HE-Transformer is also based on a Microsoft Research encryption library. Continue reading Intel Describes Tool to Train AI Models with Encrypted Data

On November 29 at the AWS re:Invent conference, Amazon Web Services introduced its AWS DeepLens, a video camera whose main purpose is to teach developers how to program AI functions. The camera comes loaded with different AI infrastructures and AWS infrastructure such as AWS Greengrass Core and a version of MXNet. Developers can also add their own frameworks like TensorFlow. The 4-megapixel camera can shoot 1080p HD video and offers a 2D microphone system for recording sound, in the form factor of an action camera on top of an external hard drive. Continue reading Amazon Debuts Intel-Powered DeepLens Camera to Teach AI