Unsurprisingly, markets in Asia-Pacific are investing heavily in research and development to support the rollout of IoT. Various governments in the region, e.g. Hong Kong and Australia, are earmarking substantial amounts to build out accelerators and innovation hubs. Meanwhile, Asia-Pacific’s longstanding roots as a manufacturing hotbed have caused the region to witness the rollout of IoT firsthand in its production lines and factories, showcasing efficiencies and vertical integrations.
For Federal agencies accustomed to building their own, independent IT shops where data is siloed to each agency, these mandates may be a tall order to fill. So how can they succeed?
My colleagues and I here at Equinix have recently witnessed a significant uptick in both interest and practical application of artificial intelligence (AI) solutions while leveraging Interconnection Oriented Architecture™ (IOA)™ best practices on our global interconnection and data center platform
We inside the technology industry do love our terminology. Think about it – does the average person outside of the tech industry really know what we mean by human augmentation, mesh networks, blockchain, intelligent assistants and the like?
The future is data-driven. Cisco predicts that by 2021, every person will have 3.5 connected devices generating 35 gigabytes of traffic per month. Business traffic is also expected to grow to more than 45 exabytes per month in the same time period.  People, machines and software are all contributing to an ever-growing volume of data sets that need to move both faster and on an increasingly distributed basis. If businesses are to compete in this data intensive era, they will need to move on from process-driven models and harness the power of data analytics instead. As a result, more and more companies are turning to Artificial Intelligence (AI) to support their business.
Meeting the new AI mandate is a tall order for U.S. Federal Government agencies, with a lot at stake. It not only requires investment in AI and cognitive technologies, but a focused strategy on how to integrate them with other technologies (e.g., cloud, data management, analytics and cybersecurity) for governments to succeed in an increasingly digital world.
The Internet of Things (IoT) is a network of physical objects, such as smart appliances, car navigators, drones, etc. that can communicate, interact and exchange data over the internet. One of the earliest examples of the IoT was a connected Coca Cola machine on the Carnegie Mellon University campus in the early 1980s. Local programmers were able to connect to the machine by the internet to see if a cold drink was available before making the trip
The data center landscape is undergoing radical changes. To compete in this rapidly evolving digital economy, organizations are moving workloads to the cloud, tapping into ecosystems of partners and leveraging artificial intelligence (AI) to deliver faster and better digital experiences. These trends are reshaping the underlying infrastructure. No longer centralized, data centers are rapidly becoming distributed and intelligent to manage these increasingly complex workloads.
Data center efficiency is about optimizing the physical world equipment to match the digital demand with the highest degree of accuracy possible. That means having the right number of servers, power, cooling needed to support demand in that location at that time. Predicting that demand across a distributed infrastructure will be far more challenging as the number of variables that impact it increase.
Artificial intelligence (AI) has been around since the 1950s, but it has recently grown into a real force in the digital transformation of businesses and our personal lives. From digital twins that create “living” digital simulation models of physical things (e.g., avatars for airplanes, cars, etc.) to voice recognition applications in smartphones and home assistants, machines are busy learning all there is to know about us and our world.