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Tag: Machine Learning (ML)
Traditionally, cybersecurity entailed a reactive approach where organisations used learnings from previous compromises to improve their defences. With technology evolving and people embracing the likes of mobile wallets, banking apps, and other solutions to manage transactions, businesses must rethink how best to bolster anti-fraud mechanisms. The answer lies in artificial intelligence (AI).
By now, decision-makers have realised the importance of data in driving businesses towards a digitally-based future. It is therefore surprising that the concept of the knowledge economy has largely been ignored. And yet, this will be the foundation on which modern organisations will be built.
‘Line of sight’ in the supply chain has taken on a new meaning in the age of Artificial Intelligence (AI) and Machine Learning (ML). Rather than simply tracking stock movements and using this data to attempt to influence the end consumer to buy a product, there is now massive investment in trying to ‘own’ the retailer from a data perspective.
Auditable AI provides the documentation and records necessary to pass a regulatory review. With novel artificial intelligence (AI) applications multiplying like rabbits these days, it may seem like the current wave of AI innovation is all beer and skittles.
Public cloud has taken centre stage in the global IT space, thanks in large part to the pandemic forcing accelerated adoption of next-generation technology solutions. According to Forrester Research, the global public cloud infrastructure market will grow 35% to 120 billion USD in 2021, as several new trends emerge around cloud technology.
Higher education institutions have long been considered to be the repositories of knowledge and learning and the structures through which knowledge is produced and disseminated. They have survived sweeping societal changes created by technology – the moveable-type printing press, previous industrial revolutions, information and communication technologies, electronic media and computers.
For those who survived the initial shock of the COVID-19 crisis, the question is: Now what? Since there is no going back to business as usual, it is time for companies to turn the page and concentrate on planning for mid- to long-term priorities.
Over the last few decades, technology has slowly shaped our world into one our grandparents wouldn’t recognise. Some of that change has been about the gadgets in our homes and in our pockets. Much else has been driven by researchers and scientists using powerful supercomputers to answer life‑changing questions and make ground-breaking discoveries in life sciences, physics, chemistry, and astronomy.
The Internet of Things (IoT) has been a hot topic for a number of years, but the pervasive and affordable connectivity required for successful deployment has held back its progress. This is rapidly changing, with the rollout of fibre to the home, 5G and even Elon Musk’s recently launched Starlink satellite.
Over the last few months, I have found it increasingly difficult to verify information. The Tembisa 10, the story of the alleged decuplet birth is case in point. It was accepted as fact and reported around the world. But it was fiction and rightfully condemned by the South African Editors Forum (SANEF).