Artificial intelligence is more accessible to consumers than ever. Every day, more developers leverage machine learning to create new solutions and upgrade others to bring more value. As the technology that shapes our world becomes more democratized, innovation will follow.

As the 5th Generation (5G) mobile network rolls out across the world, more people will have access to higher speeds that many may not have thought possible just a few years ago. When these speeds are globally available to AI developers, new ideas and ways to use the technology will spread at rates as fast as 5G. From tasks as simple as laundry and as complex as remote surgery, 5G connectivity will catalyze AI development in ways we’ve never seen before.

The Intersection of 5G and AI

If you have powerful edge devices, the AI models running on these devices will receive data faster with 5G connectivity. Through this network, we can develop robust and efficient AI offerings that make more accurate inferences at greater speeds. As we see AI in more applications that affect our day-to-day lives, we must leverage 5G to create effective communications between interconnected programs. The intersection between 5G and AI creates pathways to improving distributed intelligence.

In an environment where speed and efficiency are crucial, such as manufacturing, leveraging 5G for better connectivity is a key advantage for businesses that rely on automation. Say an AI-based solution analyzes video feeds from factory cameras to detect defects in products on an assembly line. The dataflow starts with the camera that collects the image, but the AI model could be running on another server situated in a different location with proximity to all elements of the assembly line. 5G can be the fastest way to transfer the images to the server for inferencing by the AI solution while also streamlining the program’s ability to learn.

Collaborated Working and Privacy

As we innovate through an increasingly hybridized business world, the intersection of 5G and AI lays the groundwork for novel collaboration methods. AI will also play an important role in the augmented reality (AR)-centric concepts that drive the metaverse. AI can be used to automatically detect and identify objects in a scene as part of augmenting information in AR. 5G technology can accelerate the development and adoption of augmented reality and mixed reality solutions.

In industries like aerospace, for example, work and collaboration have typically happened in the field. To perform maintenance and repair operations in the aerospace domain, boots on the ground were the only way to get the job done. These processes demand a high level of communication and collaboration to ensure quality, and with 5G, it will be easier for technicians to inform and get assistance from others remotely should any problems arise.

By leveraging 5G connectivity, AI programs can easily be implemented to facilitate remote maintenance. On a collaborative level, augmented reality or other technology can be leveraged to bridge the communication gaps between expert technicians and their on-site teams. 5G adds value to these settings by ensuring that these channels of communication are accessible enough that workflows can be executed seamlessly through digital connections. 5G’s potential can also be used for the remote control of machines, and when paired with AI, the possibilities for various industries are endless.

As new technology emerges, developers will need to figure out how best to navigate privacy and data security in these incredibly accessible environments. Building AI models, especially deep learning models, involve training on large sets of data. This data can be stored either on the cloud or a centralized data server. However, in an industry like the medical field, privacy is critical. The data belongs to the patient. Transferring their data to another singular location for training would be a violation of privacy. As a solution, we can implement programs with federated learning models where the model learns from the data on the local edge devices.

In this approach, the program is able to train on the local data, but it only communicates its aggregated learnings—no client data needs to be communicated. 5G can enable the faster transfer of model weights between the federated server and clients, which reduces the burdens of navigating privacy in data management. In facilitating processes like edge training, 5G is one of the few means of connectivity that can expedite these processes without compromising privacy in critical verticals.

Quest Global at the Forefront of AI and Connectivity

AI runs throughout Quest Global. Our teams implement programs for ourselves and clients across every sector that we serve. The ways we can extract learnings and datasets from diverse AI models empower our ability to develop strong programs.

We leverage this combination of industry and domain expertise to cultivate programs that meet the needs of the present day while creating pathways to the innovations of tomorrow. We not only identify problems, but we can articulate the problem statements that guide us toward providing industry solutions and software solutions through both 5G and AI.

We’re constantly evaluating our programming to maintain our expertise in both edge and cloud-based AI solutions. We run focus groups that include CEOs and other industry leaders in the AI space to focus on advancements. The knowledge we gain through these key connections allows us to offer the best solutions to our partners.

The relationship between 5G and AI will result in many new, impactful innovations which can help improve efficiency from results and speed. So many use cases have yet to be imagined. These ideas will come to fruition by leveraging the connectivity of 5G with the power of AI. Quest Global is the partner with the diverse industry knowledge necessary to not only uncover these problems but to begin developing solutions today.

Written by Sindhu Ramachandran

on 14 Dec 2022

CoE leader (AI), QuEST Global

Sindhu Ramachandran leads the Deep Learning (DL) and Image Analytics Practice as well as the Artificial Intelligence (AI) Center of Excellence for Electronics & Embedded Systems at QuEST. Her primary responsibility is to provide the best of Artificial Intelligence solutions to customers and end-users. She and her team strive to provide quality solutions in Natural Language Processing, Machine Learning (ML) and Deep Learning (DL) through consultancy services, proof of concepts, pilots, onsite AI workshops and proactive proposals.