By: Anasia D’mello

Nokia has announced that it has digitalised 100% of its 5G network deployments around the world, bringing high-quality, agility and transparency to customers globally.

Through the use of digitalisation, machine learning and automation, Nokia is simplifying the deployment of the network infrastructure, accelerating both time-to-market and return on the 5G investment (ROI) for operators.

Traditional network deployments rely on combinations of both paper-based and digital documentation that can often lead to errors and inefficiencies. With digital project orchestration and data inventories, Nokia is enabling network rollouts to be carried out swiftly and cost-effectively, matching the agility demands from customers and helping them to bring new services to market faster. This is leading to reductions in site visits (30%), as well as improvements in installation quality (30%), back office transactions (30%) and cycle times (25%).

By completely digitalising its 5G network deployments, Nokia is enabling a simpler, faster, more efficient and higher-quality delivery of services. Nokia’s industry-first digital deployment services have helped over 100 customers around the world by bringing transparency to every phase of a project.

The digital deployment offering enables CSPs to easily and comprehensively manage their assets by providing a digital database of network assets that can be used to remotely and virtually access sites, making it much easier to upgrade and expand their estate. Additionally, it makes deployments more sustainable as it minimises the CO2 footprint by reducing truck rolls and eliminating paper, saving an estimated 1,500 trees a year.

Read more at: https://www.vanillaplus.com/2020/09/21/54899-nokia-digitalises-100-global-5g-network-deployments-faster-time-market-roi/

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Artificial intelligence has moved into the commercial mainstream thanks to the growing prowess of machine learning algorithms that enable computers to train themselves to do things like drive cars, control robots or automate decision-making.

But as AI starts handling sensitive tasks, such as helping pick which prisoners get bail, policy makers are insisting that computer scientists offer assurances that automated systems have been designed to minimize, if not completely avoid, unwanted outcomes such as excessive risk or racial and gender bias.

A team led by researchers at Stanford and the University of Massachusetts Amherst published a paper Nov. 22 in Science suggesting how to provide such assurances. The paper outlines a new technique that translates a fuzzy goal, such as avoiding gender bias, into the precise mathematical criteria that would allow a machine-learning algorithm to train an AI application to avoid that behavior.

“We want to advance AI that respects the values of its human users and justifies the trust we place in autonomous systems,” said Emma Brunskill, an assistant professor of computer science at Stanford and senior author of the paper.

Read more at: https://www.technologynetworks.com/informatics/news/bots-behaving-badly-can-we-trust-in-an-algorithm-controlled-society-327530?utm_campaign=NEWSLETTER_TN_Breaking%20Science%20News&utm_source=hs_email&utm_medium=email&utm_content=79781295&_hsenc=p2ANqtz-_TmdSunp6ClmtSsWTLS27Iqco6dBUdA9zJDockkECzhIYVZbiqColNIhKO-UalFMMBMUoFp5TZV5gQJEZLz1nUyv4nbg&_hsmi=79781295

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