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TechArena host Allyson Klein chats with Memverge founder and CEO Charles Fan about his company’s disruptive vision for breaking through data center memory limitations and what the CXL standard will bring to infrastructure innovation.

TechArena host Allyson Klein chats with AMD senior fellow and CXL technical taskforce co-chair Mahesh Wagh regarding AMD’s entry of CXL platforms into the market gen 4 AMD EYPC processors and his organization’s strategy to deliver disruptive innovation utilizing CXL capability in the years ahead.

TechArena host Allyson Klein chats with Arm’s Panch Chandrasekaran about the massive opportunity for innovation at the edge of the network, need for efficiency for vRAN solutions, and his organization’s strategy to deliver disruptive innovation for providers.

TechArena host Allyson Klein chats with Radware CTO David Aviv about the unique challenges of securing the edge and how his company is shaping security solutions to minimize attack threats.

TechArena host Allyson Klein chats with Kartik Sawheny, founder of I-STEM, about his mission for delivering increased accessibility across computing and the challenges inherent in the industry today.

TechArena host Allyson Klein chats with Accenture’s Astha Bhardwaj on initial use cases of the metaverse emerging today and where Accenture sees immersive environments evolving in the future.

TechArena host Allyson Klein chats with Gabriela Zanfir-Fortuna of the Future of Privacy Forum about the state of data privacy and where the industry must plan for future policy alignment.

TechArena host Allyson Klein chats with Canonical’s Arno van Huyssteen and Wajeeha Hamid about the state of opensource for the network and their new solutions for RAN implementations.

TechArena host Allyson Klein chats with Ribbon’s Matt Hurst about the opportunity of 5G services at the edge and how they’re reshaping business.

TechArena host Allyson Klein chats with Cellnex’s Catherine Gull on the state of private 5G deployments and how her company is tapping the technology for deeper engagement with customers.

TechArena Host Allyson Klein discusses the imperatives for 6G as we head deep into standards definition and the need for collaboration between industry and academia on future standards with MIT’s Muriel Medard.

TechArena host Allyson Klein sits down with Dell VP Aaron Chaisson to discuss the company’s strategy for edge, current deployment trends, and a reveal of their new program for private 5G deployment.

TechArena host Allyson Klein chats with NVIDIA’s Rajesh Gadiyar about his company’s strategy to accelerate 5G and edge adoption including cloud native vRAN.

TechArena host Allyson Klein chats with Urban Machine CTO Andrew Gillies about how his company is achieving a breakthrough in sustainable construction through the AI and Robotics powered Machine.

TechArena host Allyson Klein chats with Intel vice president of wireless access networks Cristina Rodriguez about the white hot VRAN market.

Private 5G networks are foundational technology to edge computing proliferation, and we’ve heard about superior capabilities of private 5G deployments from the industry for years. In 2015 the US government opened Citizens Broadband Radio Service (CBRS), a 150 Mhz spectrum band that enabled organizations to establish private 5G networks with a caveat that they must be deployed with the proper security. This was a grand departure in the U.S. for spectrum allocations and brought to the table the opportunity to use the coming 5G network as a wireless solution where WiFi did not fit.  5G was seen as a superior technology due to the number of devices supported by each access point (AP) and for its superior signaling in high noise environments like factory floors where interference could make WiFi unreliable. 5G also offers soft handoff between APs to ensure lossless connectivity valued in industrial applications.

The past half decade has showcased incredible industry innovation in private 5G solutions and proof of concept testing with leading providers. However, the technology, like many communications network solutions, has been slow in gaining mass traction with enterprises. This past week we have seen some news that suggests that large growth is ahead supporting industry forecasts for up to 47% CAGR for private 5G networks through 2030. Nokia announced that they’ve seen a 50% increase in private 5G customer adoption QoQ and have more than 500 private 5G customers in their client base. Not to be left out, Ericsson also shared that sales are up 33%.

These industry stalwarts showing growing momentum give hope that the highlight anticipated hockey stick growth of private 5G is upon us. While these deployments are led from the US, Germany, UK, China and Japan, we are also seeing additional announcements of spectrum allocations for private 5G deployments across the world most recently in Spain and Norway opening the door for customer adoption in these countries.

The the value that was envisioned by industry architects years ago is also coming to fruition. An example is one of the first private 5G deployments in India where Apollo Hospitals is tapping its private 5G network to conduct AI guided colonoscopy procedures utilizing technology from Tech Mahindra and Airtel, a leading use case described by industry leaders during the development of this technology in its creation.

Still, macro-economic headwinds may stand in the way of a fait accompli of private 5G deployments. Verizon, for one, signaled it had miscalculated private 5G demand uptake last week as it provided its 2023 economic outlook, and industry softness in this space would fall in line with broader IT spending conservatism. As we look forward to next month’s Mobile World Congress event in Barcelona, I’ll be looking for more industry examples of successful broad scale deployment of private 5G networks, more news about additional spectrum allocations, and insight about new infrastructure innovation that delivers the performance, scale and security required across enhanced mobile broadband, massive internet of things and mission critical service private 5G use cases.

TechArena host Allyson Klein chats with Fermyon CEO Matt Butcher about WebAssembly and how it addresses many of the challenges that containers and virtual machines have brought to the cloud.

TechArena host Allyson Klein chats with NVIDIA Data Center Product Architect and Universal Chiplet Interconnect Express organization board member Durgesh Srivastava about the new UCIe specification and how it will reshape the foundations of compute architectures.

TechArena host Allyson Klein chats with Oii CEO Bob Rogers about his team’s AI-based solution for real-time modeling and management of supply chains and the opportunity for AI to drive actionable solutions for business and society.

Supply chain management shifted from an operational topic to a crisis worthy of national security concern over the past two years. We all felt supply chain issues viscerally from empty grocery shelves to skyrocketing prices. According to the White House, 36% of small businesses felt material impact from supply shortages during the pandemic with impact concentrated most within trades, manufacturing and construction sectors. The average American also likely has feelings now about the supply of semiconductors, something that likely never was a thought pre-2020. I, for one, wondered how this could all go so wrong. Didn’t we, after all, have computing models and complex analysis for supply chains? It turns out that traditional supply chain management for a lot of industries had much room for improvement with Excel spreadsheets written once every year or two being a go to model for management.

Enter Oii, a new supply chain solution that utilizes AI to map supply variables and custom tune a company’s supply chain to optimize for business objectives. Oii CEO Bob Rogers is an expert in enterprise data management formerly serving as the Chief Data Scientist at Intel and running a hedge fund that utilized advanced data analytics to predict the stock market. You could say that Bob lives and breathes inventing ways to analyze data to organizational and societal benefit. His team trained their Oii model to establish control of supply from cost, sustainability, and customer response perspectives and give supply chain managers the ability to update the model in real time in order to manage through changes in the market. This is important. Response time to changes in market environment can represent enormous advantage to a company’s ability to thrive in variable conditions.

I loved listening to Bob tell the story of Oii and hope you listen to the episode. He’s a guy who can take something incredibly complex and distill it down to a simple and actionable solution, and he’s great at bringing us mere mortals along for the ride. I’m excited to see Oii’s progress in the market as an incredibly valuable application of AI for business. As for Bob, he discussed his view on Chat GPT as a bold step towards AGI and actually published his book this week co-written by Chat GPT and Theresa Hart entitled “ChatGPT, an AI Expert, and a Lawyer Walk Into a Bar...: The Evolution of Creativity and Communication”. Those following TechArena will know that this is on the top of my reading list. Expect more to come on this topic. As always, thanks for engaging. - Allyson

TechArena host Allyson Klein chats with NASA research scientist Ryan Stauffer about how NASA's SHADOZ program measured increased stratospheric water vapor caused by the Hunga Tonga volcanic eruption and its impact on climate.

Between every two technologists there are three or more definitions of edge computing. There’s nowhere on the tech landscape today that creates more divergence of perspective as the term edge, and in my opinion, lack of crisp taxonomy limits our collective progress. I am, after all, a words person, and therefore am biased on the importance of coalescence on terms. We’ve seen this challenge before. Cloud comes to mind as a term that required ages to get crisp, and today some would argue that we’re still not unified on that definition. We are turning our focus at the TechArena to the edge with a span of compute, industrial, network and mobile edge and will be talking to industry icons and disruptors about how they’re defining their edge implementations and where market adoption is today for edge services. But before we get to all of that, I wanted to ground on my current definition of the edge in terms of what the industry is delivering today that is disrupting the technology landscape.

Let’s start by laying out some TechArena guardrails. The edge is not everything that is not in a data center. It is not all devices that are not directly human controlled (ie PCs, phones and smart watches). The edge is not a single place and it’s not a single thing…but the various edges do have some common characteristics that unify these edgy things as a unified commonality. And at this point of the diatribe, I’m going to promote the edge to the Edge…because there was use of the term edge in many corners of our industry before we started talking about the Edge. Those things may be part of the Edge…but they may not, and there is not a grandfathering clause that if you were once referred to as a part of the “insert term” edge you must be Edge.

With those guardrails, I’d like to explore why the focus on the Edge exists, in other words what problem the Edge is trying to solve for us. In listening to people discuss what they’re doing with Edge I think the three forces that created opportunity for Edge is as follows:

1. Boatloads of data are growing on a distributed computing landscape.
2. There are latency and data movement limitations in a traditional data center computing model where large compute capacity resides in a limited number of locations and network limitations bottleneck data movement.
3. The operational efficiency and scale of cloud architectural models derived in data centers offer a way to unify computing across a growing diversity of compute environments.

If we combine these forces, together we can derive a definition of Edge:

A computing environment residing apart from a traditional data center location and following the core definitions of a cloud operational model to deliver efficient and fast digital services and/or data analysis.

Let’s test this definition against use cases from across the technology landscape.

Industrial Control

A manufacturing floor has deployed sensors and cameras to collect real-time production data to measure factory output and ensure factory safety compliance. This data collection is analyzed by Edge servers to ensure real-time control of the factory while sending summarized analysis to the organization’s data center. In this usage the servers as well as potential on-camera analytics are examples of Edge computing. Smart sensors that provision work across a sensor network may also be part of the Edge implementation within our taxonomy, and it’s the operational model of service provisioning, not the hardware’s existence, that would determine inclusion. Broader “collect only” sensors or “record only” cameras are part of the larger IoT network providing data collection for the Edge. Industrial Edge implementations will often tap 5G private networks for a mobile Edge computing solution within the factory environment – watch this space for more information to come about 5G private networks and mobile Edge.

An example of industrial Edge implementation is Worchester Bosch’s implementation of industrial Edge control of their UK boiler plant leveraging robotics, a sensor network of machine and collision sensors, and Edge server analytics controlled by a private 5G mobile network. This implementation has driven up factory output by 2% while increasing safety within the factory environment. Ericsson provides more information about this implementation on their site.

CDN (Content Delivery Networks)

Content delivery networks saw massive growth during the pandemic while we were all bound to our homes and are one of the fastest growing applications of Edge computing. In this case, an OTT provider deploys Edge servers close to customer locations to serve content to minimize latency and media consumption of core networks. These CDNs also provide Edge network security and microservices for collection of billing data. The CDN is functioning as part of the Edge per our taxonomy as it’s delivering cloud services outside of a traditional data center location and may be providing some analytics on customer traffic patterns to re-deploy most desired content to maximize customer viewing experience.

An example of a CDN in action is Netflix OpenConnect Edge network distributed to the >200 million customers streaming their content daily. This Edge implementation is matched with an AWS cloud backend where Netflix runs its data storage, customer analytics, recommendation engines, transcoding and more services which are not limited by latency requirements. The unified Edge to cloud solution ensures customers do not experience disruptions of service and Netflix is able to continue analyzing customer consumption data to deliver meaningful content recommendations and move content across their network to serve optimal content to customers.

VRAN (Virtualized Radio Access Networks)

In some ways, VRAN is the holy grail of Edge implementations simplifying and speeding radio access network services (those things that keep you and I reliably connected to mobile networks) while unifying core, Edge and RAN in a common platform. To understand VRAN we need to introduce some additional terms including centralized unit (CU) an access control point which provides RAN oversight and non-real time data processing, distributed unit (DU), controlling lower-level protocols including MAC layer control through real time processing, and remote radio unit (RRU), providing physical layer transmission and reception. By virtualizing these three functions, or containerizing them in a cloud-native implementation, telecom providers are able to run their radio access networks on standard server hardware and reduce or eliminate costly proprietary solutions.

While there are various configurations of VRAN solutions, some featuring open interfaces for the RRU, others maintaining priority hardware for this portion of the RAN, the cost savings of these virtualized solutions are driving mass disruption as providers move to 5G networks and seek cloud native service to deliver the full promise of the 5G standard. To do this they require the cloud operational control of services from core to Edge including the RAN. The expected investment in this space is staggering with over $550 billion in collective VRAN investment in the next few years alone.  Watch this space for more information on the state of VRAN and to hear about progress in VRAN solution deployments in the weeks ahead.

These three examples are just scratching the surface on Edge implementations, and the TechArena is exploring other use cases to bring into the discussion. We’re also looking to hone this definition with the industry in the months ahead as we begin discussions with innovation experts from across the multi-faceted Edge landscape. As always, thanks for engaging - Allyson

Today, Intel delivered the 4th generation of Intel Scalable processors to the world complete with a 52 SKU lineup from bronze to new Max Series solutions. With their arrival comes a new battle for data center deployments as Intel seeks to compete more effectively with AMD’s 4th generation EPYC processors. So what is the landscape for data center compute heading into 2023, and how should we view these new Xeon Scalables vs. AMD alternatives? Most importantly, what will enterprise customers choose? Let’s break it down:

Intel takes acceleration to the Max

With today’s launch, Intel doubled down on a message of workload acceleration as it’s both the breadth and type of workload accelerators that give Intel its competitive edge. The new generation of Xeons feature new AI acceleration with the introduction of Advanced Matrix Extensions expanding on the vector processing acceleration of its previous generations and competitive CPU offerings. But Intel has done more here. They’ve re-structured their positioning of embedded accelerators introducing a Data Streaming Accelerator, an In-Memory Analytics Accelerator, and an expansion of Advanced Vector Instructions for VRAN implementations. Imbued with this slew of accelerators Intel is making it very clear that they intend to drive optimized performance across workload classes with unique optimizations from AI and analytics to network functions and security. While the launch notably leaned into gen over gen performance comparisons avoiding competitive bakeoffs, we should expect to see how these accelerators compete with the brute performance of AMD’s EPYC processors in the days ahead. I’d also expect to see competitors trying to dismantle the embedded accelerator approach as costly overhead compared to more nimble designs as we heard earlier from Ampere on the TechArena.

A little help from their friends

Intel expanded on workload acceleration by leaning into the depth of industry and stack expertise at their command including a decades-long history of optimizing workloads to run best on their processors. It’s no surprise that the launch featured cloud stalwarts including AWS, Google Cloud and Microsoft Azure, but there was also a reminder that Intel has invested heavily in network with inclusion of Ericsson and Telefonica and a surprising highlight on NVIDIA while they launched their Max GPUs, potentially as a circling the wagons response to AMD’s recent MI300 announcement.

The TechArena Take

While it would be easy to conclude that though Sapphire Rapids delivers breakthrough capability compared to previous generation it still does not deliver the max performance of EPYC. I, for one, am guilty of focusing on top bin performance headlines. However, we must remember that most customers purchase mid-range CPUs and select processors for myriad reasons including full stack tuning and platform trust. When I think about this battle of the CPU titans my mind drifts to the automotive industry…where similar comparisons are made between car engines and zero to sixty times. There is a small sub-set of enthusiast drivers who purchase based on speed off the line, but most buyers are looking at brand trust, cockpit experience, and other factors to fuel their purchase decision. In 2023, Intel is showcasing its strength of intimate knowledge of what customers care about, and it would be wise to not underestimate the value of this knowledge in the marketplace. I can’t wait to pop some popcorn and see how this plays out. As always, thanks for engaging - Allyson

TechArena host Allyson Klein talks with futurist Brian David Johnson about future and threatcasting, and how taking agency to envision our future places us in the drivers seat to shape it.