The proliferation of 5G wireless networks will encourage communities of AI application developers to create new solutions that take advantage of 5G speed and low latency.
Cellular communications have reached the next stage of evolution, supporting real-time, machine-to-machine connectivity as well as telephone services. 5G or fifth-generation wireless technology has increased the speed and responsiveness of wireless networks so data can be transmitted at multigigabit speeds, with theoretical speeds up to 20 Gbps. In fact, 5G wireless networks exceed the speed of most wired networks. The increased performance of 5G wireless connectivity also enables complex computing applications like artificial intelligence (AI), creating new opportunities for wireless applications. Adding no-code AI development brings an even greater potential to 5G networking.
The availability of 5G high-speed wireless technology promises the expansion of technologies such as the Internet of Things (IoT), which connects devices. Using 5G wireless systems and IoT sensors, you can remotely monitor traffic conditions, monitor patients, monitor conditions to activate farm irrigation systems, and manage autonomous things like smart cars or drones. You can improve the performance of 5G networks even further with edge computing, where you place the computing resources needed to process application data closer to the location where the data is used to minimize response time.
5G wireless infrastructures can easily support AI processing. Where 5G simplifies and speeds up the integration of multiple technologies, AI gives those systems intelligence and the ability to learn from the available data. AI simulates human intelligence by applying three cognitive skills: learning which includes acquiring data and applying rules, reasoning by choosing the right data to create the desired result, and self-correction, which is fine-tuning data sorting for more accurate results.
The marriage of 5G and AI is already shaping the future of wireless ecosystems, and with no-code AI development platforms, applications that take advantage of AI and machine learning (ML) will increase. Putting AI development in the hands of IT professionals and domain experts will eliminate the need for data scientists to automate next-generation wireless applications.
See also: Manufacturing Ahead of the Curve via AI, 5G, and Edge
AI and ML Are Powering 5G
AI is already an integral part of cellular networking. Mobile communications services use AI to optimize network performance and reduce capital expenditures. 5G service providers use AI to improve customer service and provide personalized support. Service providers also use AI for 5G network planning, network performance management, lifecycle management, and revenue management.
AI is also having a direct impact on 5G network performance. While phones have become smarter, the core smartphone algorithms haven’t changed since the 1990s. As a result, 5G systems use more power and achieve lower data rates than expected. Using AI-enabled algorithms with deep learning capabilities reduces power consumption and improves performance. AI also is being used to resolve issues related to available RF frequencies for cellular signals to alleviate bandwidth overcrowding.
Low latency also makes 5G networks ideal for applications that benefit from faster response times, such as real-time video, which depends on AI to function. Using AI/ML for 5G systems also powers proactive network responses, creating dynamic cellular clusters that use learned data to improve latency, efficiency, and reliability.
Enabling a New Generation of 5G AI Applications
While AI/ML is being used to power a new generation of 5G applications as well as the 5G infrastructure. No-code developer tools will make these AI/ML applications available to everyone.
There is an ongoing shortage of AI developers. To bridge the skills gap, no-code AI development tools are putting the power of article intelligence in the hands of IT managers and subject-matter experts. No-code platforms abstract AI complexity to make building, experimenting, and deploying AI/ML software easier. Rather than requiring data scientists with deep AI expertise, no-code AI platforms provide a drag-and-drop interface so any enterprise manager can create their own AI applications.
The proliferation of 5G wireless networks will encourage communities of AI application developers to create new solutions that take advantage of 5G speed and low latency. No-code AI development platforms will promote innovation. A growing user community and an open architecture platform will make 5G more accessible and enable new, best-in-class models and tools that can be incorporated into AI/ML workflows.
Organizations are building private 5G networks as well. Organizations with a large number of IoT sensors or endpoints benefit from private 5G because a dedicated network delivers ultra-low latency and extremely high bandwidth. 5G was initially designed to accommodate massive sensor grids for IoT applications. IoT devices and sensors generate large volumes of data, so a conventional core network or centralized cloud infrastructure can’t handle the traffic. Using edge computing for low latency is ideal for AI applications that need real-time efficiency.
Looking to the Slow Evolution of 5G
While 5G technology is proving ideal for real-time applications, there are still obstacles that are slowing 5G adoption. There are different flavors of 5G, each with different performance characteristics. Carriers are still building towers, power stations, data centers, sensors, and infrastructure to make 5G available to everyone in the United States, but it could take years to complete a 5G infrastructure.
In the meantime, entrepreneurs are stepping in to solve the complex problems posed by 5G networking. Innovators backed by investors and government policies are creating easy-to-use AI solutions that take advantage of the existing 5G infrastructure. The growth of no-code AI/ML development tools will lower the barriers to entry for 5G innovators and empower a new class of AI users.
