Goto

Collaborating Authors

Results


Sr. Data Engineer

#artificialintelligence

Role Description: The Rackspace FinOps group enables cloud users to align their cloud technology adoption with their business strategies. We advise many of the world's largest AWS, GCP, Azure, and other Cloud consumers on topics ranging from cloud architecture to organizational governance to cloud economics, driving efficient cloud adoption and usage for our clients. The FinOps Data Engineer role is an exciting opportunity to build solutions that will help us and our clients turn complex multi-cloud cost and performance datasets into actionable insights. This is an opportunity to make an impact on a fast-growing team. You'll be instrumental in creating new and better analytics and ML solutions, and generally innovate to drive new value for our clients.


Nvidia, VMware to Bring Virtual GPUs to VMware's AWS Cloud

#artificialintelligence

If you've ever found yourself wishing you could do all the things you've been able to do with a hypervisor and regular virtual machines but on a GPU cluster – in your own data center or in the cloud – Nvidia and VMware are now saying your wish is about to come true. Monday morning, in conjunction with the start of VMworld in San Francisco, the two companies announced that VMware Cloud on AWS, the VMware-operated cloud service running on bare-metal infrastructure in AWS data centers, will soon feature virtualized GPUs you'll be able to provision and manage using the same vSphere tools you use with regular VM infrastructure. You'll be able to share a single physical GPU among multiple VMs, but you'll also be able to aggregate the power of many GPUs to train a machine-learning model at massive scale, the companies said. Related: VMworld: Look at Acquisitions for Virtualization's Cloud Play The play here is to get VMware into the infrastructure mix for the emerging set of enterprise computing workloads that benefit from GPU acceleration, such as AI and machine learning, as well as more traditional Big Data analytics. Also on Monday, the company announced a broad strategy for tackling the hybrid cloud opportunity, which is essentially to provide a single set of tools for managing all enterprise infrastructure, on premises and/or in any public cloud, in a uniform way.


Machine Learning Intro at @CloudEXPO Silicon Valley @BigDataTrunk #AI #IoT #BigData #MachineLearning #DeepLearning

#artificialintelligence

In his session at 23rd International CloudEXPO, Raju Shreewastava, founder of Big Data Trunk, will provide a fun and simple way to introduce Machine Leaning to anyone and everyone. Together we will solve a machine learning problem and find an easy way to be able to do machine learning without even coding. He solved a machine learning problem and demonstrated an easy way to be able to do machine learning without even coding. Speaker Bio Raju Shreewastava is the founder of Big Data Trunk (www.BigDataTrunk.com), a Big Data Training and consulting firm with offices in the United States. He previously led the data warehouse/business intelligence and Big Data teams at Autodesk.


A Decade Later, Apache Spark Still Going Strong

#artificialintelligence

Don't look now but Apache Spark is about to turn 10 years old. The open source project began quietly at UC Berkeley in 2009 before emerging as an open source project in 2010. For the past five years, Spark has been on an absolute tear, becoming one of the most widely used technologies in big data and AI. Let's take a look at Spark's remarkable run up to this point, and see where it might be headed next. Apache Spark is best known as the in-memory replacement for MapReduce, the disk-based computational engine at the heart of early Hadoop clusters.


Machine Learning & Security @CloudEXPO @Symantec #ArtificialIntelligence #MachineLearning #DataScience #Cognitive

#artificialintelligence

Most of us already know that adopting new cloud applications can boost a business's productivity by enabling organizations to be more agile and ready to change course in our fast-moving and connected digital world. But the rapid adoption of cloud apps and services also brings with it profound security threats, including visibility and control challenges that aren't present in traditional on-premises environments. At the same time, the cloud - because of its interconnected, flexible and adaptable nature - can also provide new possibilities for addressing cloud security problems. By leveraging the power of the cloud with a data science and machine learning cloud-based solution, security and risk professionals can solve many of the traditional security challenges found in popular apps like Office 365, Google Drive, Salesforce and Box. In her session at 19th Cloud Expo, Deena Thomchick, Senior Director of Cloud Security at Symantec, detailed how cloud-based data science, machine learning, computational analysis and intelligent algorithms can work together to help to deliver truly intelligent and responsive security and compliance for the cloud.


IBM Takes Watson AI to AWS, Google, Azure - InformationWeek

#artificialintelligence

Cloud computing has made a lot of technology more accessible, and artificial intelligence and its underlying technologies are no exception. If you want more organizations to be able to use your technology, then make it possible for them to use it on one of the big public cloud providers -- Microsoft Azure, Google Cloud Platform, and Amazon Web Services (AWS). Indeed, many organizations are now using the AI services that are available and have been built on those public cloud platforms -- AWS Rekognition, for instance. In an effort to broaden the distribution of its flagship artificial intelligence technology, IBM this week announced that it is making IBM Watson portable across all these public cloud services. The company unveiled the strategy this week at the IBM Think 2019 event in San Francisco.


Machine Learning on 50 Million Smart Meters: Utility Powerhouse Extends C3 Platform Europe-wide

#artificialintelligence

In enterprise AI, C3 (formerly C3 IoT) is amassing an impressive and seemingly unmatched record, one that the company has extended with its latest win, the expansion of a five-year engagement with Enel, Europe's largest power utility, to encompass nearly 50 million smart meters in homes and businesses. This follows C3 contract wins last year with Royal Dutch Shell, the U.S. Air Force and 3M, along with partnerships with AWS, Google Cloud and Microsoft Azure. In the large utilities space, other customers include Con Edison, covering the New York metropolitan area, and Engie, one of the biggest utilities in France. The new contract (dollar amount not disclosed) expands on C3's existing, five-year engagement for Enel in Italy involving 32 million smart meters. C3 will provide the €74.6 billion utility with AI and smart grid analytics applications enabling Enel to deploy the Unified Virtual Data Lake, integrating data across its retail, distribution, trading, renewables and conventional generation businesses.


Machine Learning on Google Cloud with H2O

#artificialintelligence

Prior to working at H2O, he worked as a Quality Assurance Software Engineer, developing software automation testing. Nicholas holds a degree in Mechanical Engineering, and has experience working with customers across multiple industries, identifying common problems, and designing robust, automated solutions.


Big Data Federation to Exhibit at @CloudEXPO NY #BigData #AI #MachineLearning #ArtificialIntelligence

#artificialintelligence

DXWorldEXPO LLC announced today that Big Data Federation to Exhibit at the 22nd International CloudEXPO, colocated with DevOpsSUMMIT and DXWorldEXPO, November 12-13, 2018 in New York City. Big Data Federation, Inc. develops and applies artificial intelligence to predict financial and economic events that matter. Their products are deployed by some of the world's largest financial institutions. The company develops and applies innovative machine-learning technologies to big data to predict financial, economic, and world events. The team is a group of passionate technologists, mathematicians, data scientists and programmers in Silicon Valley with over 100 patents to their names.


BlueData Introduces New Innovations for AI and Machine Learning in Hybrid or Multi-Cloud Deployments BlueData

#artificialintelligence

BlueData, provider of the leading Big-Data-as-a-Service (BDaaS) software platform, today announced the new summer release for BlueData EPIC . This release builds upon BlueData's innovations in running large-scale distributed analytics and machine learning (ML) workloads on Docker containers, with new functionality to deliver even greater agility and cost savings for enterprise Big Data and AI initiatives. Last spring, BlueData introduced support for hybrid cloud environments – leveraging the inherent infrastructure portability and flexibility of Docker containers. This past fall, BlueData delivered a major new release that added deep learning (DL), GPU acceleration, and multi-cloud support to the container-based BlueData EPIC platform. And last month, BlueData announced a new turnkey solution to accelerate AI and ML / DL deployments in the enterprise.