While Amazon is raking in the lion's share of money spent by public-cloud users, Oracle is doubling down on its hybrid-cloud strategy, appealing to enterprises that want to put data and applications behind their firewall while taking advantage of cloud pricing models and technology.
The leveraged buyout of Dell that resulted in its merger with EMC and the computer giant going private was the first of what appears to be many similar moves. Private equity firms are looking to gobble up some of the enterprise giants and in the process, take them private.
In the wake of yet another ransomware attack—this time named NotPetya—I have a special message specifically for those of you working in organizations that continue to run Microsoft Windows as the operating system on either your servers or your desktops:
Software is now dominating IT spending.My research shows that the combination of SaaS and on-premises software is now a $650 billion market that has seen a steady growth of 6 percent per annum over the past five years. Today, almost all areas of IT are sold at least partially as software, including applications, security, storage and network infrastructure. Software is agile, enables rapid innovation and is a key component of digital transformation.
Computer scientists are developing a mind-reading computer that deciphers symbols that people have looked at.
Business Continuity Awareness Week 2017 is here, and hopefully it will present a fresh opportunity to review some of the cloud’s limitations in this area.
Cloud-native architectures will become the default option for customer-facing applications by 2020, according to a new study from IT consultancy Capgemini, Cloud Native Comes of Age. However, that move is predicated on whether the business leaders will allow it.
When Google first told the world about its Tensor Processing Unit, the strategy behind it seemed clear enough: Speed machine learning at scale by throwing custom hardware at the problem. Use commodity GPUs to train machine-learning models; use custom TPUs to deploy those trained models.
I’ve been reading and writing daily about the Internet of Things (IoT) for about a month, and I have not found ground truth. I’m not new to the field, but now focused on IoT I am trying to find a relative measure of the importance of IoT developments.
Many a blog line has been penned on the rich topic of the Internet of Things (IoT) but not much has been written about the real world challenges between our today and the many promises of the IoT tomorrow. Technology considerations can easily blind us “techies” to more mundane realities but, when you work as deeply in the Smart City space as I do, it is difficult to avoid them. In my opinion, the technology challenges surrounding the IoT are relatively small compared to the real world challenges that are perhaps not so obvious.
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