Smart Infrastructure intelligently connects energy systems, buildings and industries to adapt and evolve the way we live and work. We work together with customers and partners to create an ecosystem that intuitively responds to the needs of people and helps customers to better use resources. It helps our customers to thrive, communities to progress and supports sustainable development. We do this from the macro to the micro level, from physical products, components and systems to connected, cloud-based digital offerings and services.
Granted these are experiments, especially the fibre research and Tesla/SolarCity story, but some of these experiments will succeed. The infrastructure of landlines (analogous to the infrastructure of the centralized grid) and the steady uni-directional business model (you use the phone and you pay a fee) have given way to free phone calls to my childhood friends in Lagos over WhatsApp. In 13 years business models have been upended. Financial cycles tend to be between 7-9 years so it's taken about two cycles for phone service provider business models to change. This power shift in the utility industry started roughly around a cycle and a half ago (2006).
The successful application of machine learning for artificial intelligence (AI) requires several contexts to be addressed, primarily the technical, data and business considerations. From a technical standpoint, in building an AI-ready framework there are choices to be made such as which machine learning framework to select, the type and structure of learning function and the style of training algorithm to use. These decisions are normally based on the skill, experience and judgment of the computer scientist. A practitioner should be able to coordinate these aspects and focus on business outcomes without overly burdening the line of business with technical detail. The exception to this is when core design decisions in some way will impact business outcome.
Big Data is likely to be a key element in the digital transformation taking hold in the enterprise, but there are still questions as to how it will influence future business processes and what steps to take now to ensure it provides optimal support in a fast-changing economy. According to a recent report by Verizon and the Harvard Business Review, most organizations are looking forward to dramatic improvements in services and business models through Big Data, but few are implementing technology and infrastructure as part of a strategic approach to transformation. The study found that 52 percent expect Big Data to lead to new services for the Internet of Things (IoT), while 44 percent say it will transform their business models. However, upwards of 78 percent are currently leveraging only limited amounts of IoT data or none at all, while an equal percentage say they need new networking technologies to fully implement Big Data operations. In fact, most Big Data initiatives today are being carried out on an ad hoc basis, not as part of a strategic imperative.
Amazon will highlight the Amazon Web Services architecture under its fast-growing ad business at re:Invent. In a session on Tuesday, Amazon and its AWS unit will walk through the infrastructure behind Amazon Ads. Amazon's ad business is growing rapidly and falls into the company's "other" category on the financials. In the third quarter, Amazon's other revenue was $8.1 billion. That revenue line is increasingly seen as a proxy for Amazon's ad business.