3 steps to master real-time AI with a 5G ecosystem

Artificial Intelligence (AI) is touching all corners of the business. It enables automation and real-time insights that can revolutionise industries. AI can improve efficiency, optimise operations, and create new business models.

Today, a factory forklift operator can get notified about a potential collision up ahead with help from an AI working with surveillance cameras. A surgeon-in-training can practise, plan, and execute an operating procedure in augmented reality without endangering a patient's life. Key off-site personnel can receive alerts to security threats using AI capable of video analytics.

You have the opportunity for high-level, real-time AI. Your organisation's data system can be proficient enough to manage rapidly changing data streams and machine learning models. A high-level data system will provide valuable insights and automate decision-making, so your team can respond to dynamic situations quickly.

To achieve an AI-enabled environment, you must allow your organisational data to flow freely and quickly without sacrificing security. However, as a growing enterprise in a competitive industry, you may find that managing data is challenging, and you may be missing out on AI unknowingly.

While enterprises are excited to adopt AI solutions, many fail to innovate or scale quickly. They may unknowingly face three common obstacles:

● Managing multiple siloed systems
● Deploying latency-sensitive applications ineffectively
● Managing a growing number of connected devices

Across these obstacles, your data gets choked and fails to achieve its purpose of informing your AI solutions in real-time.

A holistic 5G ecosystem with the right tools, infrastructure, and connectivity can solve these issues. This ecosystem can create a powerful combination for deploying versatile applications across an infrastructure while maximising capital and operational costs.

With this ecosystem, you can easily connect AI solutions, other latest devices, and technologies with 5G in three steps:

By leveraging intelligence at the edge, you can run AI solutions close to the data source to automate insights and drive real-time decision-making.

For instance, you can receive insights rapidly from a video-capturing camera with the help of lightweight machine-learning tools. This way, you enable AI video analytics without disrupting or relying on remote devices or distant systems. In a 5G ecosystem, you can run AI solutions and machine learning models close to the data source.

You need an infrastructure that provides what low latency applications require to be helpful.² These applications require minimal delay or response time between a user's action and the application's reaction or output. In other words, they demand rapid processing and fast communication between various application components.

Low latency is crucial in specific applications where real-time or near-real-time performance is essential. Any significant delay could lead to undesirable consequences or reduced user experience.

Your data infrastructure must enable heavy machine learning. In a 5G ecosystem, you can access more advanced compute infrastructure and heavier AI workloads.

This would be especially important when rendering a mixed reality setting to train employees in high-risk activities. For instance, a construction company can develop a training module for a virtual reality (VR) workplace where employees get immersed in heavy equipment or hazardous situations, acquiring hands-on experience without being exposed to real-world dangers.

Whether you require light or heavy machine learning, your organisation should be able to transmit data across a vast network quickly and at low latency. With an end-to-end orchestrated platform, you can break down silos readily, ensuring only the heavier and more critical data traverses the 5G network. This approach opens up exciting opportunities, allowing for a seamless adoption of AI technology or even enabling distributed video analytics to provide real-time data at the edge.

For example, city surveillance teams can use video streams from high-definition cameras in a public location to gain timely, actionable insights. With the help of AI, security officials can detect behavioural anomalies, identify potential security threats, and take the necessary steps to prevent them.

Adopting a single pane, cloud-native management for edge platforms can enable you to innovate at scale, expanding or reducing the number of applications and devices across broad environments as needed. By embracing a fully orchestrated 5G ecosystem, you can maximise the potential of AI and drive greater efficiency, agility, and innovation within your organisation.

Staying ahead of the competition requires agility and innovation in today's rapidly evolving business landscape. A 2022 study by IDC confirmed this, stating that leaders adopting digital agility have gained a competitive advantage, doubling the number of APAC agility leaders from 20% to 38% in the last two years.³

A ready-to-install 5G ecosystem can help your organisation capitalise on the power of AI efficiently and effectively. This is where Singtel Paragon supports your business. The industry-first orchestration platform revolutionises 5G MEC, edge computing, AI, and cloud services adoption. It enables enterprises to manage cloud, MEC, connectivity, and slicing in one platform, helping you do away with complex and time-consuming coordination.

With advanced IT tools and infrastructure across a reliable 5G network, you can achieve real-time insights and make data-driven decisions. This ecosystem provides a powerful combination for deploying versatile applications across an infrastructure while maximising capital and operational costs.

Step into a hyper-connected future today and unlock the full potential of AI. Contact us to learn more about our 5G ecosystem and how it can help you achieve your organisation's goals.