{"id":2951,"date":"2020-09-28T21:56:42","date_gmt":"2020-09-28T21:56:42","guid":{"rendered":"https:\/\/techclot.com\/index.php\/2020\/09\/28\/microsoft-unveils-5g-telco-playbook-with-azure-for-operators\/"},"modified":"2020-09-28T21:56:42","modified_gmt":"2020-09-28T21:56:42","slug":"microsoft-unveils-5g-telco-playbook-with-azure-for-operators","status":"publish","type":"post","link":"https:\/\/techclot.com\/index.php\/2020\/09\/28\/microsoft-unveils-5g-telco-playbook-with-azure-for-operators\/","title":{"rendered":"Microsoft Unveils 5G\/Telco Playbook With ‘Azure For Operators’"},"content":{"rendered":"

Microsoft Unveils 5G\/Telco Playbook With ‘Azure For Operators’<\/a><\/p>\n

\n\t\t\t\t\t\t\t\t\t\t\t<\/p>\n<\/figure>\n

Microsoft Azure Monday laid out its playbook to partner with communications<\/i>
\n <\/i>service providers by providing a carrier-grade platform for edge and cloud computing to help network operators realize the full potential of 5G technology.<\/p>\n

The No. 2 cloud provider\u2019s new Azure for Operators telco strategy is fortified by its past and current telco-related work\u2014including its partnerships with operators such as AT&T<\/a> and T-Mobile, and its development of Azure Edge Zones\u2014and acquisitions of telco-geared software makers Affirmed Networks and Metaswitch earlier this year.<\/p>\n

\u201cToday starts a new chapter in our close collaboration with the telecommunications industry to unlock the power of 5G<\/a> and bring cloud and edge closer than ever,\u201d Jason Zander<\/a>, executive vice president of Microsoft Azure, said in a blog post Monday. \u201cWe\u2018re building a carrier-grade cloud and bringing more Microsoft technology to the operator\u2019s edge. This, in combination with our developer ecosystem, will help operators to future-proof their networks, drive down costs and create new services and business models.\u201d <\/p>\n

Using Microsoft Azure and its artificial intelligence (AI) and machine-learning capabilities, operators will be able to automate their operations and offer new services including ultrareliable, low-latency connectivity, mixed-reality communications services, network slicing and highly scalable Internet of Things (IoT) applications to help transform industries, Zander said.<\/p>\n

Last summer, Microsoft Azure and AT&T unveiled a multiyear strategic alliance to leverage AI and 5G using AT&T\u2019s network and the Azure cloud platform to market integrated solutions in areas including voice, collaboration, edge, IoT, public safety and cybersecurity. Microsoft is now AT&T\u2019s preferred cloud provider for non-network applications.<\/p>\n

\u201cSince that announcement, we\u2019ve made considerable progress on our journey to become a \u2018public cloud-first\u2019 company,\u201d Igal Elvaz, AT&T\u2019s senior vice president of wireless, said in a statement. <\/i>\u201cMicrosoft\u2019s recent and bold acquisitions in the wireless core space will further support our long-term strategy of using public cloud for network workloads.\u201d <\/p>\n

In addition to AT&T, inaugural partners for Azure for Operators include systems integrators Accenture and Tech Mahindra, and Ascos, Etisalat, Hewlett Packard Enterprise, Intel, Mavenir, Red Hat, Samsung, Telstra, Tillman Digital Cities, Verizon<\/a> and VMWare.<\/p>\n

\u201cWe want to bring, effectively, the cloud economical models to the operators and carriers,\u201d Yousef Khalidi<\/a>, corporate vice president of Azure Networking, told CRN. \u201cUntil not long ago, most of the public clouds\u2014I\u2018m referring to us and the two other big ones\u2014were mostly designed and catering for the enterprise space, and that was a 10- to 12-year journey to get us there. But if you look really at meeting the needs of the whole segment of the telecommunications sector, we did not really meet their core network needs. We definitely ran their enterprise back-office applications, line of business, CRM, etc., but not the core networks. So we realized there\u2019s an opportunity to help our customers better here.\u201d<\/p>\n

To do so, Microsoft needed to have the right technology set, the right people and the right mindset to understand what those customers need to better serve their own customers, Khalidi said. <\/p>\n

\u201cTheir needs are carrier-grade networks, software that can run mobile and wired and wireless networks,\u201d he said. \u201cAll of us are going through an inflection point with 5G. They also have a need to introduce compute in their workloads, which is something, frankly, we understand quite well.\u201d<\/p>\n

Click through to read more about the Operators for Azure strategy unveiled by Microsoft, which last week said it had joined the 5G Open Innovation Lab<\/a>\u2014a global ecosystem of developers, enterprises and government institutions\u2014as a founding partner to help startups with its engineering and technology resources.<\/p>\n<\/p>\n

Published at Mon, 28 Sep 2020 20:03:45 +0000<\/p>\n

DARPA sets sights on making AI self-aware of complex time dimensions<\/a><\/p>\n

The Defense Advanced Research Projects Agency (DARPA) is setting its sights on developing an AI system with a detailed self-understanding of the time dimensions of its learned knowledge.<\/p>\n

DARPA\u2019s Time-Aware Machine Intelligence (TAMI) research program and incubator<\/a> is looking to develop a new class of neural network architectures that incorporate an explicit time dimension as a fundamental building block for network knowledge representation,\u201d according to the TAMI program solicitation<\/a>.<\/p>\n

The overall goal is to create an AI system that will be able to \u201cthink in and about time\u201d when exercising its learned task knowledge in task performance.<\/p>\n

The Challenge<\/strong><\/h3>\n
\n

Current neural networks do not explicitly model the inherent time characteristics of their encoded knowledge.<\/p>\n

Consequently, state-of-the-art machine learning does not have the expressive capability to reason with encoded knowledge using time.<\/p>\n<\/blockquote>\n

The Proposed Solution<\/strong><\/h3>\n
\n

TAMI\u2019s vision is for an AI system to develop a detailed self-understanding of the time dimensions of its learned knowledge and eventually be able to \u201cthink in and about time\u201d when exercising its learned task knowledge in task performance.<\/p>\n<\/blockquote>\n

How and Why<\/strong><\/h3>\n

Large amounts of data samples are needed to feed neural networks; however, each data sample exists only in a specific time frame.<\/p>\n

To understand what this means and looks like, the solicitation points out:<\/p>\n

\n

Consider neural networks designed for inference. Such neural networks derive abstract task knowledge from the analysis of a large number of data samples.<\/p>\n

Each data sample exists only in a specific time. For example, features given by a vehicle data sample are associated with that specific vehicle\u2019s age (e.g., rust and dents) and, therefore, are explicitly dependent on time.<\/p>\n

Neural networks incorporate such information as static activation weights; however, using the example above, the activation of these weights should ideally be conditioned on time.<\/p>\n<\/blockquote>\n

What DARPA wants, according to the solicitation, is a learning mechanism that enables \u201ca self awareness of the complex time-conditioned property of neural networks\u2019 knowledge encoding.\u201d<\/p>\n

The TAMI research program will have two phases:<\/p>\n

    \n
  1. Feasibility Study<\/strong>: Performers will develop theories and computational methods to answer fundamental questions regarding time cognition in machine learning<\/li>\n
  2. Proof of Concept Demo<\/strong>: Performers are expected to prototype time-aware meta-learning methods into computational models and demonstrate whether the new model could provide novel machine intelligence capabilities that current state-of-the-art machine learning architectures cannot achieve.<\/li>\n<\/ol>\n

    For the feasibility study, DARPA seeks answers to such questions as:<\/p>\n