Cradlepoint enables the freedom to connect people, places, and things that drive more experiences, more ways to work, and better business results — anywhere.  The company is a pioneer in Wireless WAN, offering advanced 4G and 5G routers and adapters — controlled through Cradlepoint NetCloudTM. Enterprises and public sector agencies rely on Cradlepoint and its Cellular Intelligence to build a reliable, secure network wherever they need it, connecting fixed and temporary sites, vehicles, IoT devices, and remote employees. Headquartered in Boise, Idaho, Cradlepoint is a subsidiary of Ericsson’s Business Area Enterprise Wireless Solutions division. It has international offices in Asia Pacific, Canada, Europe, India, and Latin America. www.cradlepoint.com

Open-world learning (OWL) has taken on new importance in recent years as AI systems continue to be applied in real-world environments where structural violations of expectation or novelty can occur with non-trivial frequency. Novelty can impact AI performance profoundly, ranging from overt catastrophic failures to non-robust behaviors that do not take changing context into account. In this presentation, the University of Southern California's Dr. Mayank Kejriwal argues that designing machine intelligence that can operate in open worlds, including detecting, characterizing, and adapting to novelty, is a critical goal on the path to building systems that can solve complex and relatively under-determined problems. 

He will also discuss and distinguish between three forms of OWL (weak, semi-strong and strong), and between the development of OWL algorithms in active versus passive domains. Finally, he will explore the issue of how we can properly evaluate OWL approaches. Unlike traditional machine learning, an OWL algorithm must be capable of handling situations that are genuinely and structurally unexpected. Hence, their practical evaluation can pose an interesting conceptual challenge.

Key takeaways:
- An overview on open-world learning and why it is so important in real-world infrastructures.
- How open-world learning can provide a competitive advantage.
- Reasons why open-world learning is the next frontier in machine intelligence.
- The key difference between weak, semi-strong and strong open-world learning systems.
- A primer on evaluating and stress-testing open-world learning. 

About the speaker:
Dr. Mayank Kejriwal holds joint appointments at the University of Southern California's Viterbi School of Engineering. His research, funded by the US Department of Defense, corporations and philanthropists, is focused on applying AI to solving complex data-intensive problems. He is the author of four books, including an MIT Press textbook on knowledge graphs.

Explore open-world learning at the edge: the next stage of machine intelligence

With companies all over the world grappling with exponential data growth, data intelligence at the edge is a way for organizations to manage the increasing flow of data in a more efficient manner, optimize information use, reduce costs and improve their business performance. An IBM marketing cloud study indicated 90% of global data was created in the last two years, growing at 2.5 quintillion bytes of data per day.  In order to keep up, companies are now deploying smart-connected sensors and assets daily, requiring machine to machine and internet of things (IoT) networks to alleviate costly inefficiencies of data management in the cloud. IoT networks must embrace centralized architecture, where processing raw data begins at the network edge. 

Companies have utilized data flow, the cloud, or cores or racks of equipment purchased to perform certain calculations and storing these results to bill data center operating expenses. Rather than run up costs by processing and storing data for stretches of time, companies are beginning to use artificial intelligence (AI) and machine learning (ML) to help eliminate wasteful data while streamlining relevant data meaningful to the business. AI-powered edge analytics can aid in improving response and efficiency rates, reducing operating costs and more quickly identifying raw data that hold little to no value for the business.  

Tune into this webinar, presented by industry thought leader, Dr. Sue Tripathi to learn:
1. The use of AI/ML at the edge, requiring increased processing power and logic to be built into edge devices. 
2. Key components to protect critical infrastructure, including security algorithms, encryption keys, and scan updates.
3. Data management at the edge of the network. 
4. Examples of real-time application of data intelligence at the edge with good business outcomes and timely and informed decision making.

Data intelligence at the edge

Real-time information systems impose deadlines for producing control responses, as latency in their data generation, processing and transfer may cause impermissible failures. This characteristic mainly affects data intelligence related to methods and tools for classifying and integrating real-time information. Companies can achieve timely solutions by utilizing local premises rather than supporting centralized servers or clouds. Instead, computing within the network partly takes place near the physical end points which is where edge computing paradigm comes in to help. The ultimate benefit of edge computing is cloud optimization. 

Edge computing enables splitting and sharing data between network data centers and local computing power. Meanwhile, strong authentication techniques ensure confidentiality, integrity and consistency of shared data.

Tune into this in-depth webinar to gain a proper understanding of edge computing and a deeper knowledge of the following concepts:
• Edge vs other computing paradigms.
• Infrastructure on the edge.
• Data intelligence at the edge.
• Edge data privacy.

About the speaker:
Yeghisabet Alaverdyan is currently the Head of Systems Integration Department at EKENG CJSC since 2018. She graduated from the National Polytechnique University of Armenia in 1980 with a specialization in System and Electrical Engineering. She started her professional carrier as an engineer at the RA National Telegraph. Senior Engineer, then Chief of the National Telegraph Computing Complex. In 2003, she began her teaching career as a lecturer teaching Discrete Mathematics; Finite Automata Theory; Cryptography; Programming in C++.  She obtained her PhD in 2012 and is the author of more than 20 scientific papers published in local and international scientific journals. Her current research is in Mathematical Cryptography, AI and Cognitive systems modeling.

Edge computing: Infrastructure and data intelligence

In the aftermath of COVID-19 that forced everyone in isolation, working from home became a normality, resulting in high volumes of day trading and ever-growing gaming communities around the world needing rapid access to information. Because of this minimum latency has increased tremendously. 

Edge can help bring the computing resources closer to where data is generated and consumed, so companies do not have to solely rely on a centralized, cloud-based infrastructure. This has provided the opportunity for the new generations to spend more time with family while working from home, as well as for gaming and to experiment with new endeavors such as day trading. This shift will contribute to the digitalization of our daily lives as we move to a fully developed digital economy and culture. With its benefits, edge computing also also has the potential to significantly increase both physical and logical data security concerns and present companies with a challenge for maintaining and upkeeping these facilities.

Tune into this webinar from industry thought leader Farhad Mehraban as he explores the use of edge computing and its impact on work, trading and other facets of our daily lives.

About the speaker:
Farhad Mehraban is a leading digital economy, information technology, cloud and data center expert who consistently delivers latest and most credible solutions to the industry at large and across vast geographical and vertical coverage terrains.

Edge computing's impact on today's gaming and trading culture

You’re constantly evaluating new technologies to accelerate your organization's success and the benefits they could bring. In tech decisions, you are often forced to respond reactively. Emergency arises. Solution assessed. Solution implemented.

Instead of looking in, take a look at where business is done - at the edge. Edge computing captures and facilitates all of that and moves the business world forward at a never-before-seen pace.

The ever-expanding expectations of our digital world demand that more applications run outside the cloud or data center, close to where they are used by people, devices, and IoT technologies. But managing the sprawl of complex infrastructure to run applications locally in geographically distributed locations is an escalating burden on IT departments. If you need to run applications outside the data center and cloud but with cloud-like simplicity and performance or want to know how automation can help, join this session to learn how running applications at the edge is easier than you think.

Mitch Etchason, Product Manager at Scale Computing, discusses optimizing IT infrastructure at the edge to help you think about where you are today, and where you could be tomorrow.

Expanding to the Edge: Next-Generation IT Infrastructure

With more than 24 billion edge connections expected by 2025 (GSMA, “The Global Economy,” 2020), it’s no surprise that companies are increasingly prioritizing ways to leverage the intelligent edge. Of businesses engaged today, 1 in 3 cite the intelligent edge as critical to their strategy, and 2 in 3 expect it to be critical within the next 5 years. In this webinar held in partnership with the Open Infrastructure Foundation, we’ll review the findings of a third-party study we partnered on that included 578 responses across France, Germany, Spain, the U.K., and the U.S.

What you will learn:

- The key drivers behind the intelligent edge. What are the motivations, expectations, and top use cases?
- The top requirements and concerns when deploying the intelligent edge. How should you think about security?
- The role of open source technology and why it’s becoming pervasive. We’ll share some specific open source projects related to the intelligent edge.

Open Source: The Foundation of the Intelligent Edge

What enterprises should and should not demand and allow in their embrace of edge.

IT on the Edge: Making Edge Computing Work for the Enterprise

According to Gartner, NaaS will be adopted by 15% of all enterprises by the end of 2024, up from under 2% in 2022. With the demand for a highly automated, scalable infrastructure still increasing, Digital Alpha Advisors saw the opportunity to merge PacketFabric and Unitas Global to create the next evolution of Network-as-a-Service. A TruNaaS.   

During this webinar, moderator, Lisa Gerber, Business Develop of Media and Entertainment at PacketFabric, will ask panel speakers Chief Executive Officer, Dave Ward, and Chief Strategy Officer, Carole Girdley, why this is a pivotal moment for revolutionizing enterprise digital infrastructure.

In this webinar, you’ll learn:

+ The meaning of TruNaaS and how it revolutionizes business connectivity
+ How to reimagine business operations with Edge to Everywhere infrastructure
+ The benefits of being able to design and control communication architecture without the burden of owning or operating any part of the network

Edge to Everywhere

Mobile edge computing (MEC) distributes execution resources, such as compute and storage, for applications with networking closer to end users. This includes deploying edge infrastructure at enterprise premises that is managed or hosted by operators that power 5G use cases across industry verticals such as transportation, energy, smart cities and manufacturing.
 
Distributed cloud, including hybrid cloud and multi-cloud, supports the deployment of applications which ensure an execution environment for applications across different sites. Through MEC, operators can generate new revenues by using capabilities such as connected edge compute, distributed data fabrics, and private 5G capabilities to manage more B2B and B2B2C implementations.
 
Tune into this webinar from industry thought leader Ron Westfall to learn how MEC is an enabler for a broad range of use cases, creating opportunity for 5G revenue diversification and monetization as well as improving the enterprise 5G experience.

About the speaker:
Ron is an experienced research expert and analyst, with over 20 years of experience in the digital and IT transformation markets. He is a recognized authority at tracking the evolution of and identifying the key disruptive trends within the service enablement ecosystem, including software and services, infrastructure, 5G/IoT, AI/analytics, security, cloud computing, revenue management, and regulatory issues.

Why edge computing is essential to 5G success

Edge is not a new idea but exploiting the edge effectively does require some new thinking some of which is counter-intuitive in the modern cloud centric world in which we operate. 5G is going to unleash a whole new wave of possibilities around remote devices and as IT functions we are going to be under more and more pressure to deliver on the promise. We need to get our houses in order and build a platform that will act as a springboard and not pitch us flat on our faces.

Tune into this webinar presented by expert Simon Ratcliffe, as he examines edge computing across a variety of environments and discusses how to build a stable, secure and manageable edge environment that can form the foundation for transformational change within organizations.

Digital transformation at the edge in 2023

For use cases involving devices connecting to mobile networks, the edge cannot exist on its own and needs support within the core network to deliver on its potential. The traffic to the edge needs requires specific treatment to ensure optimal routing and quality of service for example. Next to that, many use cases in mobile networks involving the edge are expected to involve multiple networks because they need to reach a larger user base and/or because of the users mobility.
 
The GSMA and its operator and industry members have created initiatives to make using the edge in mobile networks as simple as possible. This involves a federated platform architecture that allows exposing the required capabilities of all operators involved in the federation as services through entry points that each of those operators could offer to their enterprise customers, alignment on the APIs offered and on the models for offering those. This architecture will now be used also to offer other, non-edge-related services that may be of use to enterprise customers.

About the speakers:
Mark Cornall  has been with GSMA for One year as a Technical Director. He has been focusing on the federation of APIs and work within GSMA’s Operator Platform Group. Prior to this he worked for Vodafone Group studying public and private MEC and as technical lead in the deployment of AWS Wavelength into the Vodafone Networks. Within Vodafone he has held a number of earlier technical roles focusing on Video and TCP optimisation, the “Enjoy More” program and performance management. 

Tom van Pelt has been with the GSMA as a Technical Director for over 10 years. Within the GSMA, Tom has been driving and contributing to the specification and interoperability work on RCS messaging and since 2019, he’s also involved in the work on Operator Platform and telco edge cloud. Tom is acting as the director of the GSMA’s Operator Platform Group.

Beyond the edge

The use of IIoT and IIoT devices can help manage water networks, energy, smart grids and mobility. Edge processing can provide the key features for successful IoT at scale, tackling the needs of reliability, quality, low-energy, adoption and cybersecurity. For instance, dedicated IoT architecture and algorithms at the nearest sensors allow for reliable IoT that can manage, digitalize and automatize a water network. However, this requires companies to have the dedicated development and knowledge for such applications. 
 
Tune into webinar presented by Lacroix's Stephane Gervais and Nicolas Guilbaud as they introduce the notion of “smart data,” processed data from the edge that can help steer decision making. This presentation will also address cybersecurity, its importance, and some implementations to reduce the complexity for end professional users.

How Edge can be an enabler of IIoT and AI scalability

Enabling Edge Computing

As more enterprise-generated data is created and processed at the edge of the network, Mobile Edge Compute (MEC) is becoming a driving force behind this trend. Currently, only 10% of data is generated outside traditional data centres or the cloud, but by 2025, Gartner predicts this figure will reach 75%. Cradlepoint is at the forefront of this trend with its ability to run secure Docker containers directly connected to IoT sensors or devices via routers.

Join us for a webinar on the impact of Mobile Edge Compute (MEC) on the IoT market, including customer success stories, where we will explore:
• The types of workload that can be performed at the edge of the network
• How this trend is changing the way enterprises process and store data
• The benefits of running secure Docker containers directly connected to IoT devices
• How our experience with customers in different industry sectors demonstrates best practice in MEC
 
Don't miss this opportunity to learn about the future of data processing and storage. Register now and stay ahead of the curve.

Exploring the Impact of Mobile Edge Compute on IoT Data Processing and Storage

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Exploring the Impact of Mobile Edge Compute on IoT Data Processing and Storage

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