Manish Rajendran, Managing Director & 5G Edge Domain CTO of Deloitte Consulting, driving 5G and edge innovations for global enterprises.
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Not so far ahead in the future, new solutions like tactile internet, robot swarms and intelligent automation are envisioned to transform everyday life as it exists today. Imagine a surgeon performing a complex operation remotely, feeling every tissue and suture as if they were in the operating room. Or robots and drone swarms working autonomously to extinguish forest fires, dynamically changing firefighting strategies in real time. Or how about autonomous vehicles communicating with each other and traffic systems at intersections to avoid vehicle collisions, optimize traffic routes and significantly improve pedestrian safety? These next-generation use cases are no longer science fiction and are increasingly becoming a reality—but not without significant challenges.
The Challenges Of Implementing The Technology Of The Future
Implementation of these technologies face several challenges today—most of them stemming from the limitations of current networking, computing and data processing capabilities.
• Latency And Bandwidth Constraints: Next-generation applications such as remote surgery could use holographic representations of patients, tools and organs to assist remote procedures. However, the tactile feedback, precision and synchronization to deliver these in tandem with a holographic presence requires data bandwidth and latency that current 5G access would struggle to deliver.
• Computation Power And Data Processing Limitations: Swarm robots and autonomous systems generate vast amounts of data that need to be processed locally for instant feedback and closed-loop decisions. Additionally, the computational power needed for AI models that power these use cases is growing exponentially, creating a bottleneck for rapid scaling.
• Security And Privacy Concerns: As technologies become pervasive, the risk of cyberattacks also increases. The massive amounts of data transmitted and analyzed—especially those involving personally identifiable information (PII) from the financial and healthcare sectors—raises security and privacy concerns. With the growing compute capacity, current encryption and data protection methodologies may not be sufficient to safeguard against sophisticated cyberattacks.
• Scalability And Interoperability Challenges: As new graphics processing units (GPUs), central processing units (CPUs) and neural processing units (NPUs) continue to evolve, ensuring that your technology stack is easily scalable across a variety of applications, irrespective of model requirements and hardware accelerators, comes down to the ability to operate across diverse interfacing systems and protocols.
How Emerging Technologies Can Help Solve These Challenges
To overcome these limitations and enable next-generation use cases, emerging technologies like 6G, quantum connectivity, high-performance interconnects, heterogeneous computing and the convergence of edge and cloud computing are becoming essential.
• 6G Networks: 6G networks are expected to provide global reach (integrating multiple network types like host access protocol, satellite and terrestrial radios) with a combination of capabilities such as submillisecond latency, terabit-per-second (Tbps) bandwidth, precision sensing and localization. This will help realize use cases like autonomous drone fleets for global disaster response.
• Heterogeneous Computing: Heterogeneous computing leverages different types of processors—such as CPUs, GPUs, field-programmable gate arrays (FPGAs) and tensor processing units (TPUs)—to optimize workloads across various applications. This approach allows each processor type to handle specific tasks more efficiently based on the needs of the use case, enhancing overall system performance and reducing power consumption.
• High-Performance Interconnects: Technologies like NVLink, InfiniBand and Compute Express Link (CXL) play a crucial role in facilitating rapid data transfer between processors and memory. These high-performance interconnects are essential for heterogeneous computing environments where GPUs, CPUs, FPGAs and other accelerators work together to execute complex algorithms for AI, machine learning and big data analytics. When data interconnects like traditional PCIe buses get choked with high volumes of data between next-generation GPUs and CPUs, evolution to high-performance interconnects will become a necessity.
• Quantum Connectivity: Quantum connectivity introduces new paradigms in secure communication that’s increasingly important for environments that require high security and quick computation. This is particularly important in the future for these environments, which include autonomous vehicle fleets and smart grids.
• Edge And Cloud Computing: The convergence of edge and cloud computing creates a balanced computing ecosystem where data can be processed either near its source (at the edge) or centrally (in the cloud), depending on the application’s requirements. Edge computing reduces latency and bandwidth use by processing data closer to where it’s generated, which is essential for real-time applications like smart cities, industrial automation and connected health. Conversely, cloud computing provides vast computational resources for tasks that require high processing power and are less sensitive to latency, such as large-scale data analysis and machine learning.
Conclusion
In conclusion, the seamless integration of 6G, quantum connectivity, high-performance interconnects, heterogeneous computing and edge-cloud convergence is pivotal for enabling the next generation of use cases. These technologies address the limitations of current systems, providing the necessary bandwidth, latency, computational power and security to bring these futuristic applications to life. As these technologies continue to develop and mature, they will unlock new possibilities and drive the next wave of innovation across various industries, transforming how we live, work and interact with the world around us.
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