Fullmoonfever
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I recall, well pretty sure anyway, FF mentioning a BRN staff like Sean or Jerome or someone discussing telecom applications not thought of before or telco discussing with BRN. Or was it EAP client...too many webs these days haha but anyway.
Not saying we're involved as no deep dive but just looking at Ericsson site at the mo and they seem AI big and interested to see where we could fit.
Some application cases below.
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.
Up to 25% better 5G coverage
14% - average saving for a proof-of-concept cluster
18% better network load redistribution
15min execution of performance diagnostics across 1M cells
~15% energy OPEX reduction through intelligent energy optimization
80% reduced signaling (paging)
Intent-based networks | Machine reasoning
Not saying we're involved as no deep dive but just looking at Ericsson site at the mo and they seem AI big and interested to see where we could fit.
AI in telecom networks: intelligent and autonomous
AI enabling intelligent networks.
www.ericsson.com
Some application cases below.
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)
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 robotsAI 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