Run:AI | April 22, 2020
A virtualized AI infrastructure for DL would run a single workload on multiple shared physical resources.
Article by Google’s Francois Chollet discusses the skill acquisition-based approach to gathering intelligence.
The conventional computing stack – from processor to firmware to virtualization, abstraction, orchestration and operating layers through to end-user software.
Is the recent progress in deep learning true artificial intelligence? A widely-discussed article by Google’s Francois Chollet discusses the skill acquisition-based approach to gathering intelligence – the one currently in use in modern DL. He argues that with huge data sets available for training models, AI is mastering skill-acquisition but not necessarily the “scope, generalization difficulty, priors, and experience” that true AI should incorporate. Even with our progress in AI, and specifically DL, we are nowhere near the limits of what DL can achieve with bigger, better-trained more accurate models, those that take into account not only skill but experience, and generalization of that experience.
Understandably, this has put intense focus on computing power, particularly the hardware that enables data scientists to run complex training experiments.
Nvidia increasing sees DL as a key market for its GPUs and bought Mellanox to speed communication inside a GPU cluster. With its recent acquisition of Habana, Intel is likely betting that custom AI accelerator hardware is a better match.
Other AI-first hardware includes Cerebras’s massive chip in a custom box that’s designed for the specific types of intensive, long-running workloads that training DL models require. In the cloud, Google’s Tensor Processing Units offer another bespoke option.
For companies running their own DL workloads, more compute is generally better. Whether exotic AI accelerators or tried-and-tested GPUs, quicker model training means more iterations, faster innovation and reduced time-to-market. It may even mean we can achieve “strong” AI (i.e., AI than goes beyond “narrow AI,” which is the capability of doing a single, discrete task) quicker.
In 2020, continuing the trend of recent years, companies will invest in ever-more AI hardware, in an effort to satisfy data scientists’ demands for compute to run bigger models to solve more complex business problems. But hardware isn’t the whole picture.
The conventional computing stack – from processor to firmware to virtualization, abstraction, orchestration and operating layers through to end-user software – was designed for traditional workloads, prioritizing high-availability, short-duration operations.Training a DL model, though, is the opposite of this sort of workload. While running a model, an experiment may need 100 percent of all the computing power of one or multiple processors for hours or even days at a time.
Read more: Virtualization can transform your company’s IT infrastructure
O-RAN ALLIANCE | July 06, 2020
The O-RAN ALLIANCE has continued its progress towards making the Radio Access Networks (RAN) truly open, intelligent, virtualized and fully interoperable. The O-RAN ALLIANCE welcomes TELUS Communications Inc. and U.S. Cellular as new operator members, bringing the total to 26 major carriers. O-RAN now has over 200 companies driving the definition and realization of O-RAN technology.
Verizon | June 19, 2020
Verizon Business Group (VBG) is expanding its Virtualized Network Services (VNS) portfolio, by adding Cisco’s Enterprise Network Compute System (ENCS) to its existing catalog of compute devices.
Verizon’s VNS portfolio allows customers to replace traditional network devices, such as routers, firewalls and switches, with virtual network functions (VNFs), which can be managed and orchestrated from a central location.
VBG’s enterprise customers utilizing the Cisco ecosystem can leverage Cisco’s ENCS for a more flexible and agile networking infrastructure.
Verizon Business is expanding its Virtual Network Services (VNS) portfolio for enterprise customers with the introduction of Cisco’s 5000 Series Enterprise Network Compute System (ENCS). The Cisco ENCS purpose-built platform will now be included within Verizon’s catalog of virtual network functions and service chains that are offered to customers.
Verizon’s VNS portfolio allows customers to replace traditional network devices, such as routers, firewalls and switches, with virtual network functions (VNFs), which can be managed and orchestrated from a central location. VNFs help expedite customers’ digital network transformation by reducing or removing the need for manual intervention, building flexibility and agility into an organization’s ability to scale capacity, prioritize application availability quickly, and respond to changing business needs. The Cisco ENCS is a purpose-built compute platform optimized for Network Function Virtualization.
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“Customers need to be able to quickly and easily deploy network services to branch locations as their business needs evolve,” said Aamir Hussain, Senior Vice President of Business Products. “The addition of Cisco’s ENCS compute platform to our VNS portfolio is another way for us to help enterprise customers simply deploy enterprise networking solutions for a more responsive, scalable and flexible network.”
The integration of Cisco’s ENCS solutions into Verizon’s VNS portfolio is another example of how our two companies continue to work together to enhance the possibilities of network virtualization. Cisco’s virtualization solutions can help Verizon Business customers with a preference for Cisco’s ecosystem to easily deploy agile enterprise networking solutions, which is what all companies need today to continue to stay resilient and competitive,
Scott Harrell, Senior Vice President and GM of Cisco’s Intent-Based Networking Group.
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Verizon Communications Inc.was formed on June 30, 2000 and is celebrating its 20th year as one of the world’s leading providers of technology, communications, information and entertainment products and services. Headquartered in New York City and with a presence around the world, Verizon generated revenues of $131.9 billion in 2019. The company offers voice, data and video services and solutions on its award winning networks and platforms, delivering on customers’ demand for mobility, reliable network connectivity, security and control.