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Amazon’s latest announcements from AWS re:Invent 2017, Mozilla’s Speech Recognition Model, and IOTA’s Data Marketplace in today’s trending stories around artificial intelligence (AI) and data science news.

re:Invent 2017 in data science news

AWS IoT Analytics: Amazon announces dedicated analytics service for IoT data

To drive insights out of the huge data IoT generates, Amazon Web Services launched a dedicated IoT analytics service called AWS IoT Analytics. The IoT analytics tool lets users gather, store and then query the messages coming from the IoT sensors, while extracting specific sets of data on a regular basis. “With the AWS IoT Analytics service, you can process messages, gather and store large amounts of device data, as well as, query your data. Also, the new AWS IoT Analytics service feature integrates with Amazon Quicksight for visualization of your data and brings the power of machine learning through integration with Jupyter Notebooks,” the company said in its blog post.

SageMaker: AWS makes it easier to build and deploy machine learning models

AWS SageMaker is an end-to-end machine learning service making it easier for developers to build, train, and deploy machine learning models. With a goal to simplify machine learning and democratize deep learning models, SageMaker starts with an authoring component for data cleaning and processing, and offers scalable model hosting and training. Other than the built-in algorithms and one-click training, SageMaker has a new feature Hyper Parameter Optimization, using which developers can check a box at the beginning of tuning their model, and it will find the best parameters for their machine learning model.

AWS DeepLens: Amazon unveils deep learning powered wireless video camera for developers

Amazon has announced AWS DeepLens, a wireless AI camera that uses deep learning to run real-time computer vision models. DeepLens consists of an HD (1080p) video camera and an Intel Atom X5 processor that can process over 100 billion deep learning operations per second. The camera runs on Ubuntu 16.04 and is preloaded with the Greengrass Core. Amazon said it will pair DeepLens with SageMaker, another new platform being announced at re:Invent for developing and distributing machine learning algorithms. “Developers can extend these tutorials to create their own custom, deep learning-powered projects with AWS Lambda functions,” writes Amazon. “AWS DeepLens could be programmed to recognize the numbers on a license plate and trigger a home automation system to open a garage door, or AWS DeepLens could recognize when the dog is on the couch and send a text to its owner.” DeepLens is priced at $250 and includes wireless connectivity; it has a 2D microphone array and 8GB of onboard storage. It also features USB and microHDMI ports for connecting to a PC to export data.

Amazon Translate: A neural machine translation service more accurate and scalable

Amazon has announced a neural machine translation service named Amazon Translate, to deliver fast, high-quality, and affordable language translation. Amazon Translate will use machine learning and deep learning models to deliver more accurate and more natural sounding translation than traditional statistical and rule-based translation algorithms. Apart from accuracy, it is highly scalable, meaning it easily translates large volumes of text efficiently, localizing websites and applications for international users. To preview Amazon Translate, click here.

Aurora Serverless: AWS announces a serverless database service where users only pay for the processing when the database is actually doing work

Amazon’s AWS cloud computing division has announced a new database service making it easier and cheaper to quickly launch relational databases that don’t need to process data continuously. Aurora Serverless users only pay for the processing when the database is actually doing work. Customers no longer have to provision or manage database capacity, and the database automatically starts, scales, and shuts down based on application workload. Customers simply create an endpoint through the AWS Management Console, specify the minimum and maximum capacity needs of their application, and Amazon Aurora handles the rest.

Mozilla in data science news

Mozilla releases open source Speech Recognition Model and voice dataset

Mozilla has announced the initial release of its open source speech recognition model. The system is based on research from Baidu’s Deep Speech project, and was trained using a data set of almost 400,000 voice recordings from over 20,000 people. Mozilla said its system offers a word error rate of about 6.5 percent, not quite as good as human beings at recognizing speech, but still pretty close. The company is also releasing the world’s second largest publicly available voice dataset, which was contributed to by nearly 20,000 people globally.

No blockchain, but Tangle..

Cryptocurrency IOTA announces Data Marketplace for Internet of Things, uses new technique Tangle to distribute and decentralize its ledger

Upcoming cryptocurrency startup IOTA has launched a new micropayment-based Data Marketplace that’s powered by distributed ledger technology. The publicly data marketplace is specially designed for the Internet of Things. The initiative has gathered participation from more than 20 global organizations, including Deutsche Telekom, Bosch, Microsoft, PricewaterhouseCoopers, Accenture and Fujitsu. Research groups from leading universities in the world are also working on it. The marketplace aims to give connected devices the ability to securely transfer, buy and sell datasets using a “tangle” based distributed ledger technology for storing transactions. In contrast, most other cryptocurrencies including Bitcoin and Ether use blockchain technology. The IOTA Foundation claims that it is this decentralized permissionless ledger, where the data will be hosted, that will eventually ensure that the data being sold on IOTA’s marketplace is tamper-proof. Co-founders Dominik Schiener and David Sønstebø believe Tangle offers free transactions and much better scaling opportunities.


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