Eagle-Lanner tech blog

 

AI plays a crucial role in enabling autonomous mobile robots to perceive, reason, and make intelligent decisions in dynamic and unstructured environments. AI for autonomous mobile robots is a rapidly evolving field, driven by advancements in computer vision, machine learning, and robotics. It finds applications in various domains, including logistics and warehousing, manufacturing, healthcare, agriculture, and search and rescue operations. The goal is to develop robots that can operate autonomously, adapt to changing environments, and interact effectively with humans to perform complex tasks.

Safeguarding critical infrastructures is crucial for maintaining the smooth operation of essential services such as power substation, oil refinery, water treatment, and transportation systems. With the increasing integration of operational technology (OT) and the rise of sophisticated cyber threats, the role of artificial intelligence (AI) in OT security has become increasingly important. AI can play a significant role in enhancing the security of critical infrastructures by detecting and responding to cyber threats in real-time, improving incident response capabilities, and enabling predictive maintenance to prevent system failures.

The advent of the 5G has ushered in a new era of connectivity with its unparalleled speed, low latency, and massive device capacity. While 5G has garnered significant attention for its faster internet speeds and improved mobile experiences, its true potential lies in transforming industrial networking. In this blog, we delve into the realm of Industrial 5G, exploring how this cutting-edge technology is revolutionizing the manufacturing sector and propelling it into the future.

This rapid evolution of AI is impacting many aspects of modern life, and businesses must now consider where and how to use these tools. One of the critical areas where AI is being used today is in the field of network security. Network security is an essential aspect of modern-day business operations as it protects sensitive information and data from cyber threats.

Artificial intelligence (AI) is transforming the way we interact with technology and industries across the board, and edge AI is no exception. Edge AI refers to AI algorithms and models that run on devices or hardware at the edge of a network, as opposed to being processed in the cloud or on a centralized server. This approach reduces latency, conserves bandwidth, and increases privacy by keeping data local. From autonomous vehicles to intelligent drones and robots, the demand for high-performance AI processing solutions continues to grow. One such solution is Nvidia’s Jetson family of AI-enabled edge devices, which includes the Jetson Xavier NX, Jetson Orin NX, and Jetson Orin Nano. Let’s explore and compare these devices, focusing on their AI capabilities and processing power.

As 5G networks continue to roll out across the globe, the demand for high-speed connectivity has continued to escalate. This surge in demand for agile, high-performance, and scalable networks has led to an increase in the deployment of virtual radio access networks (vRANs), which separate the hardware and software components of a mobile network. To enhance the performance of vRANs, Intel has introduced the Intel vRAN Boost solution. Another factor expected to drive the adoption of Intel vRAN Boost is an increase in complex applications beyond mobile broadband that require different 5G network behavior.

The new connected world requires wireless connectivity everywhere you go – whether it is at home, on the go, or at work. The rapid increase in the volume of data, plus the need to process said data in multiple places – at the endpoint, the edge, and in the cloud – has created a challenge and made faster movement of data a priority. We have discussed previously how Open RAN provides Communications Service Providers (CSPs) more choice and flexibility to efficiently and cost-effectively deploy their radio networks, let's further explore the abilities of accelerator cards.