This Week In Digital covers many interesting talking points. A million new jobs in India in Cloud computing, Amazon with a couple of new inventions, and can Big data predict future?
1 Million New Cloud Computing Jobs To Be Created By 2022 In India – Express Computer, November 26, 2018.
Great Learning, an ed-tech platform for executives, came out with a report which states that over a million cloud computing jobs will be created in India by 2022. That said, the industry suffers with acute shortage of talent with more than 1.7 million cloud jobs worldwide remaining vacant due to shortage of talent. According to IDC, there is only one qualified candidate for 100 job postings in cloud computing across the globe. The major reasons for this gap are lack of training, hands on experience in a cloud-based environment and industry recognized certification. This skill gap comes at a time when almost two-thirds of global enterprises are using cloud computing; and the investment being made in cloud infrastructure is 4.5 times the rate of traditional IT spending.
Amazon Web Services Announces AWS RoboMaker – BUSINESS WIRE, November 26, 2018.
Amazon Web Services, Inc. (AWS), an Amazon.com company (NASDAQ: AMZN), today announced the availability of AWS RoboMaker, a new service that makes it easy for developers to develop, test, and deploy robotics applications, as well as build intelligent robotics functions using cloud services. AWS RoboMaker extends the most widely used open source robotics software framework, Robot Operating System (ROS), with connectivity to AWS services including machine learning, monitoring, and analytics services to enable a robot to stream data, navigate, communicate, comprehend, and learn. AWS RoboMaker provides an AWS Cloud9-based robotics integrated development environment for application development, robotics simulation to accelerate application testing, and fleet management for remote application deployment, update, and management.
Amazon launches AWS Ground Station to help companies transmit satellite data – Khari Johnson, November 27, 2018.
Amazon announced the launch of AWS Ground Station in preview today to help businesses, researchers, governments, and space agencies upload and download data from satellites orbiting Earth. To power the service, ground stations and antennas with the power to send and receive data will be placed at or near AWS datacenters around the world, AWS CEO Andy Jassy said. A handful of ground station-as-a-service locations are available today, and 10 more are in the works for early 2019, he said.
HPE buys AI and big data start-up – Tom Wright , November 28, 2018.
Hewlett Packard Enterprise (HPE) has snapped up artificial intelligence (AI) and big data start-up BlueData for an undisclosed amount. Santa Clara-based BlueData was founded in 2012 and has raised $39m (€34.57m) in funding, according to Crunchbase. HPE said the deal will “significantly expand” its footprint in the AI and machine-learning space, and bolster its big data analytics capabilities. Milan Shetti, SVP of HPE’s storage and big data business, said: “BlueData has developed an innovative and effective solution to address the pain points all companies face when contemplating, implementing, and deploying AI/ML and big data analytics. HPE said the acquisition is in line with its “data-first strategy”, which will see BlueData’s tech combined its own software-defined infrastructure.
Xynteo 2018: Big data, big impacts, small “me”? – Fiona Taylor, November 30, 2018.
In today’s digital world, we have an incredible opportunity to finally solve some of the world’s most intractable problems, using connectivity to pool ideas and resources across time zones and geographies, and to fuel innovative ideas and solutions. And yet, even as connectivity bridges divides, it leaves one big issue in place: data. For the fact is, society’s digital adoption outpaces its understanding of who should own the data that digital creates, who should be able to use it, and to what end.
Google’s Inclusive Images Competition spurs development of less biased image classification AI – Kyle Wiggers, December 2, 2018.
Bias is a well-established problem in artificial intelligence (AI) and is typical of models trained on unrepresentative datasets. It’s a tougher challenge to solve than you might think, particularly in image classification tasks where racial, societal, and ethnic prejudices frequently rear their ugly heads. In a crowdsourced attempt to combat the problem, Google partnered with the NeurIPS competition track in September to launch the Inclusive Images Competition. This challenges teams to use Open Images a publicly available dataset of 900 labeled images sampled from North America and Europe to train an AI system evaluated on photos collected from regions around the world. It’s hosted on Kaggle, Google’s data science and machine learning community portal.
Alibaba’s speech recognition algorithm can isolate voices in noisy crowds – Kyle Wiggers, December 2, 2018.
Chinese conglomerate Alibaba is one of the world’s largest ecommerce companies, but it’s increasingly turning its attention to artificial intelligence (AI). We’re solving scenarios [with] unseen difficulties,” said Rong Jin, dean of the Alibaba Institute of Data Science. “AI together with innovation [is helping] to solve some interesting challenges.” One of those challenges is speech recognition in noisy environments, like a crowded subway system or congested convention center. Alibaba’s solution is part hardware, part software, a far-field microphone array and sophisticated deep learning algorithms that isolate voices in a crowd, drastically reducing error rate.
Using big data to predict the future – Tim Sandle, December 2, 2018.
Advances with machine learning and big data analytics are helping researchers, and ultimately companies, to make predictions about future trends by analysing patterns. A new application looks at medicine. Researchers from the University of Córdoba have been exploring how large volumes of data can be organized, analyzed and cross referenced to predict certain patterns. This forms part of the process commonly referred to as ‘big data analytics’. The focus of the review was on predicting the response to specific examples, such as medical treatments, operational improvements for smart buildings, and even the behavior of the Sun. Each prediction process is based on the input of key variables.