Over the last few years, a quiet and gradual, but nonetheless important, evolution has been taking place. There has been a move from traditional business intelligence or analytics software towards the use of open platforms that underpin analytics activity, and can integrate customers’ own solutions, reducing reliance on proprietary software.
Will AI dramatically accelerate the division of our society into the “elite” and the “worried rest”? For example, will there be highly effective personalized medicine that only very few can afford? Will AI take over the automatable jobs of the middle class, while the highly qualified elite maintains or even
On Friday, 5th October, I slept out rough in London with a team from SAS, along with about 1500 others across the UK, as part of Byte Night. This is an annual event to raise awareness and critical funds for the charity Action for Children, which helps to prevent youth
Since the 1950s, with machine learning, deep learning and cognitive computing developing over time, for some of us AI has been around for a while. What has changed recently is perhaps the sheer volume of data available. This has made it both possible to train AI-based models in a way
British Prime Minister Theresa May made it clear that her ambition is for the UK to become the global beacon for innovation in artificial intelligence when she spoke at the Annual General Meeting of the World Economic Forum earlier this year. Great news, then, that two UK master’s in data
Developments in artificial intelligence (AI) are expected to change the world of work across the board. We have already witnessed the impact on marketing communication endeavours and strategies. The ripples spreading across the water include ethical issues and questions of accountability. I caught up with Anabel Gutiérrez, Senior Lecturer in
According to the Organisation for Economic Cooperation and Development (OECD), “service performance, citizen satisfaction and public trust are closely connected. Yet how can governments overcome citizens’ declining levels of trust in the way that their data is collected and used in order to improve service accessibility and quality? It’s not difficult
Enterprisewide analytics and AI have the power to prepare insurers for a customer-centric future and transform the relationship with policyholders. But will only a handful realise that their current approach to analytics leaves them poorly prepared for the challenge? As I noted in my previous post, success in the new
IDC’s April 2017 white paper Data Age 2025 posits that in 2025 the digital economy will multiply by 10 the volume of data now generated, attaining something like 163 zettabytes. Life-critical data - data captured from devices having a direct impact on human life, for example: autonomous cars, remote monitoring
Blinking, I can barely see what’s in front of me. The sun is shining right in my face. The light is blinding and intense – I realise I have to be vigilant. I do my best to see what’s in front of me because I’m travelling at 60 kmh, and
