We hear a lot about how smart machine learning-based tools and platforms are going to change the world of work. Some commentators, like Stephen Hawking, have made apocalyptic prophecies about how the world as we know it will end as the machines take over, and there are no more jobs.
Application programming interfaces, otherwise known as APIs, are set to radically change the face of analytics. These little bits of code are working behind the scenes, hidden treasures that allow two pieces of code to talk to each other. This means that developers can borrow functionality from other apps.
“Anyone who wants to be 100% sure, will be 100% late.” I heard this sentence recently at the IoT Forum in Munich. It is a very good summary of the feeling that is emerging in the debate on Industry 4.0. The buzzword battles of the past 48 months seem to
A spectre is haunting economy – the spectre of digitization. All the powers of old economy have entered into a holy alliance to exercise this spectre. But other than the communism (obviously the first two sentences are stolen from the Communist Manifesto by Marx and Engels from 1848) – this
Artificial intelligence (AI) is the subject of considerable discussion across industry sectors around the world. Telecoms companies are showing considerable interest in the potential of AI, whether at the front end—customer service—or to improve service delivery via better network performance and reliability. There are a number of different AI technologies
Stephen Hawking’s latest warning is stark. Robots and artificial intelligence (AI) have already played havoc with working class jobs in factories and heavy industry. Now they are set to do the same with middle class jobs, from legal work, through financial services to computer programming. Cue economic turmoil, unemployment, and
It is a truth universally acknowledged that there is huge potential for public services to be transformed by artificial intelligence (AI). Longevity is rapidly increasing. We are living longer and healthier lives and the population growth is slowing down. The working age population is shrinking and with that comes a
Telecoms players don’t get a lot of positive press coverage, if we’re honest. With roaming charges and expensive long-term contracts, it can be hard to find anyone prepared to stand up for the telco industry. I think that needs to change. I have been part of this community for almost 20
Predictive modelling solutions typically rely on the availability of good quality data and subsequent models which are estimated in advance using historical data. For example, a credit scoring framework to predict propensity of customer default requires the use of clean processed transactional and demographic data. Datasets used for this type
Governments are already using data and analytics in a number of ways to help them become better informed and provide superior services for their citizens. For both central and local governments, an increasing number of back end processing and citizen engagement opportunities are emerging for smart use of artificial intelligence
