BEL Sign in AI in networks Building cognitive networks and human trust in AI Read the blogpost Table of contents HOME AI IN NETWORKS AI in networks AI is creating business value in terms of improved performance, higher efficiency, enhanced customer experience as well as creating new business models and use cases for 5G, IoT and enterprise. AI and machine learning AI enabling intelligent networks As 5G, IoT and Edge gains traction, the shift that transforms industries and enterprises, becomes a reality. It also brings new complexities of network operations – co-existing of new and legacy technologies, hybrid networks, a variety of frequency bands and spectrums, and an abundance of connected devices. In addition, new requirements from IoT and industrial use cases require further performance enhancements and optimization of the network. This is the context for our efforts in AI and we use it to cut through the complexity, address requirements of new technologies and use cases, increase network performance and enable network automation. AI and automation By using a combination of currently available and well-understood AI techniques within a flexible architecture, we are able to reach a high degree of practical autonomous operation. This will lead us into an era of intelligent, autonomous networks with close to zero touch. The real value of AI is not limited to applications which connect to the network but will ultimately be realized in the networks. Intent-based networks | Machine reasoning Trustworthy AI To realize the full potential of AI, trust needs to be established in the development, deployment and us of AI. This is critically, why we build human trust in AI addressing aspects spanning from explainability and human oversight to security, and built-in safety mechanisms. Trustworthiness is a prerequisite for AI and we are building it into the system by design. Explainable AI | UX design to trust AI Discover a world of new possibilities Ready to create the future? Imagine a world where limitless connectivity means limitless possibility. By creating connections that make the unimaginable possible, we are helping to shape an exciting and positive future. A world where limitless connectivity improves lives, redefines business and pioneers a sustainable future. We invite you to explore the potential and power of limitless connectivity and what it means for our future world. Explore the possibilities Hear from experts about AI Remote robotics and AI Hear from Elena Fersman, Head of Research Area Artificial Intelligence at Ericsson Research, how the relationship between humans and robots is changing. Discover why it’s paving the way towards zero-touch operations and a landscape in which the network will automatically adjust and react based on the needs of the robots. Watch here On demand: Ericsson Unboxed – AI for good From the Terminator and the Matrix in pop culture, to facial recognition and ethical issues, AI has always been a hot topic - and it’s had a history of negative press. But in fact, AI is a force for good. How has AI actually helped in the fight against coronavirus? And how is it helping in other areas, for example preventing climate change? Watch here AI and its necessity for a better 5G AI adoption is essential to efficient network management and operations. In this video, Jonas Åkeson, Head of Automation & AI, explains how AI and automation will help address the complexity of 5G networks, drive efficiencies and improve customer experience as well as open new revenue streams. Watch here Our AI solutions in action Our artificial intelligence solutions target service providers to address their challenges to maximize efficiency and end-customer experiences and create new revenue streams. They are embedded throughout the network, built by people with extensive AI and telecom expertise, and with an AI-first mindset and technology in every product or service. 5G-aware traffic management With AI embedded in the RAN Compute software, 5G capable devices can be directed to the best 5G capable cells, keeping users with 5G phones in 5G coverage. Cells are ranked based on AI models and dual connectivity capability. Up to 25% better 5G coverage Augmented MIMO sleep In Ericsson Radio System, AI algorithms run on the baseband to predict traffic patterns and autonomously turn off antennas as required to reduce energy usage. It’s also possible to combine with Cell sleep and the Low Energy Scheduler solutions for even better savings. 14% - average saving for a proof-of-concept cluster Self-organizing networks Intent driven proactive and reactive optimization workflows combined with AI to optimize Cell Clusters at scale. Machine Learning-based unsupervised clustering techniques is applied to discover Network Topology. 18% better network load redistribution Cognitive design & optimization Industry-leading suite of cognitive software solutions for network planning, design, tuning and optimization. 15min execution of performance diagnostics across 1M cells Energy infrastructure operations AI and data analytics to create energy efficiencies on the radio network. ~15% energy OPEX reduction through intelligent energy optimization Machine Learning assisted paging Machine learning improves the existing patented MME features of adaptive paging so that it becomes topology-aware and reduces signaling, which in turn frees up capacity and defers investment for carriers. 80% reduced signaling (paging) More about the main areas we address with our AI solutions Take a deep dive into AI To deliver cognitive networks, we build human trust in AI To deliver cognitive networks by 2030, that learn, reason and act on business intent almost autonomously, we must build trustworthy AI. Hear from our CTO Erik Ekudden how our networks will become the platform of choice for future digital enterprise. Read the blog post Ensuring energy efficient networks with AI Finding ways to make networks more energy efficient without negatively impacting experience is critical to network operators for both cost and sustainability reasons. To assist in these efforts, we are exploring the potential of using AI techniques to recommend energy-efficient configuration settings for network nodes. Read the research article Explainable AI – how humans can trust AI The increased application of AI to gain automation has grown the complexity and scalability of the systems, and consequently the need for transparency, understandability and explainability of the AI-based systems. Explainable AI provides methods and techniques to produce explanations about the used AI and the decisions made by it, consequently, helps attaining human trust. Read the white paper Trustworthy AI: explainability, safety and verifiability As AI becomes more prominent across the globe, building trustworthy AI systems is paramount. Here, we discuss the foundations in the design of every AI system: explainability, safety and verifiability. Read the blog post Cognitive processes for adaptive intent-based networking Autonomously operated and self-adapting networks will make it possible to utilize the capabilities of 5G networks in new business models and achieve an unprecedented level of efficiency in service delivery. Intents will play a critical role in achieving this zero-touch vision, serving as the mechanism that formally specifies what the autonomous system is expected to do. Read the research article Adopting AI in organizations This report reveals what challenges might occur when implementing AI, and related solution strategies. The report shares insights from research in 5 countries, involving 2,525 managers in a cross-section of organizations which are at different stages of the AI implementation journey – AI-leaders, AI-followers and AI-beginners. Read the report Stay updated White papers & reports Ensuring energy efficient networks with AI Explainable AI – how humans can trust AI UX design in AI Adopting AI in organizations Artificial intelligence in RAN - a software framework for AI-driven RAN automation Cognitive processes for adaptive intent-based networking Privacy-aware machine learning with low network footprint Employing AI techniques to enhance returns on 5G network investments PDF AI and automation – trends shaping the digital economy PDF Blog posts NOV 10, 2021 | Blog post AI bias and human rights: Why ethical AI matters NOV 09, 2021 | Blog post Closing the digital divide: how machine learning and data science can help Giga map the next million schools NOV 05, 2021 | Blog post Continuing the journey to protect the mangroves in the Philippines: AI solutions show promise in wildlife and site protection NOV 04, 2021 | Blog post How to tackle air quality prediction using machine learning NOV 04, 2021 | Blog post Enabling smarter networks: capitalizing on cloud native in NWDAF use cases Read more News Read more We have AI capabilities that solve major problems for service providers We are not building a general-purpose artificial intelligence platform, trying to solve problems in every industry. Instead, we have developed our skills and capabilities in telco AI to address the challenges of service providers. Working closely with our customers’ challenges, data and products, we are providing them with a different approach to getting value from their networks. We have identified and prioritized four AI capabilities that make our AI as effective as possible. Telecom & AI expertise Our AI is anything but artificial, it’s built on a strong foundation of combining deep telecom domain expertise and data science- and AI knowledge. These skills always work hand in hand, close to customer problems, collaborating to solve them. This means that we know the right problems to solve and how to solve them with the right AI solutions. AI-ready technology Ericsson’s technology is AI-ready. We have made architectural decisions that make AI easy to deploy and use and that works together holistically across the network. Combined with our telecom domain expertise, this means that we can use AI where it makes sense, solving the right problems for our customers. AI use case co-creation We have learned through experience that co-creation in developing solutions together is critical. We develop our AI in the field together with our customers, using real network data, our domain expertise. Together with a portfolio of ready-made use cases and pre-trained algorithms, we adapt to various customer contexts and problems. In this way, we can solve the right problems for our customers instead of providing an untrained general platform or solutions to only address very specific challenges. AI-powered portfolio We are not a niche player, focusing on one use case. Instead, we build AI into every part of our portfolio where it makes sense, from baseband to centralized clouds. With AI spread out through all our products, we can see the whole end-to-end context and how we make every part of the network work together. Unique access to data Through access to multiple and diverse data sets from CSPs that we collaborate with, we can train our algorithms. This valuable data creates a unique foundation to build powerful algorithms, benefitting CSPs and their end-users. Explore related offerings AI in operations How we are taking network and IT operations from manual, reactive, and incident-driven, to proactive and data-driven operations – all based on AI and automation. AI in radio access networks How do you improve your network performance and user experience in today’s densified networks? AI is one of the keys in conquering these challenges, for LTE as well as 5G. Cognitive network In the future mobile network, all operational processes and tasks will be executed with 100% automation. The network will become cognitive – it will be continuously self-learning at scale from its experiences with and observations from its environment and from its interactions with humans. 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