Generation of new and optimization of existing services based on artificial intelligence methods (Deep Learning and Machine Learning).
What is Artificial Intelligence about?
Artificial Intelligence (AI) has a long history, starting in the 1950s with the theoretical concept of the Turing test and gaining considerable momentum since the early 2000s. This development has been driven by the significant increase in computing power which makes computation-intensive Deep Learning algorithms easy and effortless to handle. The intelligent processing of images (computer vision) and speech (natural language processing) is becoming a routine part of our customers’ daily lives as found in mass market applications such as Apple’s Siri or Amazon’s Alexa.
Artificial Intelligence is defined as the imitation of human intelligence or intellectual processes by machines, especially computer systems. These processes include learning, reasoning, and automatic correction. AI’s mathematical foundations are recursive statistical procedures which were originally developed well over one hundred years ago.
The principal domain of AI is machine learning, which can be divided into supervised and unsupervised learning. Unsupervised learning is essentially the decomposition of large data sets into different, mathematically well-defined clusters which enable predictions to be made from data from the same source. In situations that are perceived as complex by humans, machine-generated error diagnoses or recommendations can be produced. Currently, the most fascinating discipline of AI is Deep Learning. Here, the mathematical model of a “neural network” mimics the way a human brain works. Intuitive human accomplishments such as understanding speech or emotions, or a brilliant move in a chess match are thus to be made accessible to algorithmic processing.
Why is T-Labs intensifying its work in the field of artificial intelligence?
A telecommunications company simply has to continuously evaluate the current breathtaking developments in artificial intelligence, to see how they can make communication for both people and devices (Internet of Things) easier and better. This goes far beyond obvious things such as speech interfaces, to include every part of the value chain and innovative services. Improvements in the operation of the communications networks, in the efficiency of internal processes and in comprehensive security solutions all result from these innovative developments as well as e.g. improvements in predictions of where a free parking space can be found.
Of particular interest in this respect is the tailoring of artificial intelligence techniques for the emerging next generation of communication networks (5G). The technical innovations in 5G networks enable AI algorithms to be distributed over a variety of computing instances, thus opening up the development of disruptive new applications.
Working together with our partners, T-Labs’ goal is to research and develop best practices, to quickly produce proof-of-concepts and minimum viable products (MVP) both within the telecommunications value chain and beyond.
Photo: Dong Wenjie / gettyimages.de