Communication Interchange for Artificial Intelligence Systems

The rise and proliferation of Artificial Intelligence (AI) technologies are bringing transformative changes to various sectors, signaling a new era of innovation in fields as diverse as medicine, manufacturing, and even day-to-day social interactions. Notable advancements are not just confined to textual understanding, as seen in models like GPT, but also extend to visual cognition through image recognition and more. Beyond surface interactions and predictions, AI finds profound applications in life-saving domains such as medical diagnostics and becomes an integral part of daily life through chatbot- based customer interactions. However, as the horizon of AI expands, a crucial yet often overlooked aspect emerges- the underlying mission-critical infrastructure required to support and deploy these models effectively. The intricacies of efficient communication systems, foundational for real-time AI model operations, take center stage in ensuring the seamless functioning of AI -driven applications. This paper explores the quintessential changes needed in communication paradigms to keep pace with the evolving AI landscape. Specifically, we highlight the pivotal role of multipath communication in enhancing the responsiveness and efficiency of AI applications [1]. As a case in point, we investigate its impact on mission-critical operations in robotics. Through experimentation and analysis, the results elucidate the substantial benefits of this approach, revealing a significant improvement in delay metrics. This work underscores the imperative of aligning communication systems with the ever-growing demands of AI, ensuring that infrastructural capabilities do not lag in the race for innovation.