Optimizing the Edge

Chairperson’s Welcome and Opening Remarks

Edge Computing, as we are all aware now, releases the technology stack from the cloisters of data centers and large server racks to where the data is. However, edge computing also has a great impact on how we think not just about the data but how we use the data in smarter predictability and decisions making using new thinking on the Artificial Intelligence and Machine Learning. Metaverse on the other hand is opening the door on how we interact with one another and the world. This presentation takes step back and takes a new look on the area of Artificial Intelligence and Machine Learning and redefines and positions Edge Computing in the context of that new thinking in terms of opening a new outlook to Metaverse to interact with both human and humanoids. This presentation further takes the area of Edge Computing on other areas of modern technology such as Blockchain, Digital Twin, Augmented and Virtual Reality as an extension of Internet of Things (IoT) as well as Quantum Computing. The author describes each of these areas and their relationships to Edge Computing through his own innovative works and beyond.

This Session Will Explore…

• Perspectives on the Edge landscape right now. 
• What are the key challenges being faced across industries that need to be addressed? 
• What questions still need to be answered about the efficacy of this technology? 
• Use cases and demos of how Edge is impacting industries. 

Cloud as we all know has revolutionized the industry. Cloud gives velocity and elasticity to build solutions and businesses. Oftentimes the cost grows with the growth but that is only the best case. The promise of cloud is that you pay only for what you use. The cost optimization does not have to end there, it could just be the beginning. Just like cloud migration, cost optimization in the cloud can be managed and achieved using similar techniques.

• Overview of the legacy problem caused by architecture on edge computing.
• New architecture with help of Kubernetes can improve developer’s efficiency with modularization.
• How AI assistant can play a practical role in edge computing industry.

In this session we’ll discuss the exciting opportunities enabled by Edge computing and virtualization, that allow enterprises to eliminate complexity, save on network costs, add network functionality and more.

Generating prompt insights from data using machine learning (AI ML) and advanced analytics serves as a fundamental catalyst for driving business transformation. This presentation covers:

• • Benefits and basic definitions of AI ML and Advanced Analytics and current challenges with common patterns of implementation in these areas around data volume, latency, and security.
  • Components  for a successful strategy and why distributed computing should be considered as a critical component in this strategy
  • How Edge Computing as a distributed computing paradigm can address challenges related to data volume, latency, and security by processing data closer to the source, therefore, enabling more real-time insights, improved data privacy, and efficient resource utilization.
  • Edge Computing design patterns, future of Edge Computing, and examples.

• Edge AI enables real-time data processing, increasing efficiency and speed.
• In home security, edge AI provides customized solutions and real-time alerts without internet connection.
• Benefits: real-time processing, better security, cost reduction, quick responses, scalability, personalization, reliability, and enhanced analytics/customer experience.
• Edge AI applications: supply chain optimization, disaster response, sustainability, workforce impact.
• Ethical considerations: algorithmic bias, privacy, security, transparency, job impacts.
• Collaboration: responsible and ethical deployment, addressing challenges, maximizing societal benefits.

This is a pre-recorded presentation and is available on demand for 2-weeks post event on our event platform.