Tag: platform equinix vision paper

We are celebrating the launch of the nearly $60 million expansion to our MI1 facility on the Equinix Miami campus. Today, MI1 is one of the most interconnected gateway data centers in the U.S., offering unsurpassed connectivity options to LA&C markets. It is where domestic and international companies, service providers and government agencies can gain access to rich ecosystems of enterprises and network, cloud and SaaS providers under one roof.

The potential impact of quantum computing on technologies such as security and artificial intelligence will enable new applications and capabilities in the fields of healthcare and pharmaceuticals, financial services, aerospace and defense. However, a lot must happen in quantum computing development, with the methods in which quantum computers operate and communicate with each other, and how new quantum native algorithms get developed before any of its practical applications can see the light of day.

All these innovations make France a destination of choice for digital businesses that want to establish themselves in a vendor-neutral colocation data center facility at the digital edge, regardless of industry. Digital businesses need a vendor-agnostic, multi-tenant data center provider that delivers world-class interconnection solutions, which open-up access to state-of the-art French digital infrastructure, global business ecosystems, personal and data security controls, and renewable energy resources.

A change as fundamental as the shift to software-defined networking infrastructures doesn’t just happen in a moment. But it is happening now. Software-defined networking (SDN) is at the core of many virtualized network infrastructures and has gone through a lot of maturing to become a mainstream technology.

The recent rise of artificial intelligence (AI)/machine learning (ML) in the cloud — and related capabilities such as predictive analytics — has started to push DevOps organizations to explore the implementation of a new data analysis model that relies on mathematical algorithms.

According to LogicMonitor’s Cloud Vision 2020: The Future of the Cloud Study, 66% of the enterprises surveyed see AI/ML as one of the leading factors driving greater public cloud adoption in 2020. A modern data architecture is imperative in today’s global digital economy to give enterprises the speed and agility required to transform into digital businesses, leverage cloud, and quickly access and unify data using evolving technologies such as AI/ML and the Internet of Things (IoT).

What does it mean to be connected? Is it your Smartphone in your hand? An augmented reality helmet on your head? Or the wireless sensors that surround us everywhere we go? We now have multiple ways to be plugged into both the physical and virtual worlds. But would it surprise you to know that today’s businesses that bring you the Internet of Things (IoT) technologies and those connected products, could be more connected to you as a consumer? Or to the IoT and digital supply chain partners that enable them to develop and distribute those connected devices on a worldwide basis?

The major difference between the public and private blockchain is the consensus mechanism. In public blockchain, you do not trust any of the other members, so the amount of computation overhead that is involved in verifying or validating every transaction is quite high and time consuming. Whereas in a private blockchain there’s usually a greater amount of permission-based trust involved, so you can use simpler and faster consensus algorithms.

When we think of “platform companies,” it’s typically Airbnb, Alibaba or Amazon that come to mind. According to the book by authors Parker, Van Alstyne and Choudary, “Platform Revolution: How Networked Markets are Transforming the Economy – and How to Make Them Work for You,” platform companies follow a “business model that uses technology to connect people, organizations and resources in an interactive ecosystem in which amazing amounts of value can be created or exchanged.”  

The problem of learning and decision-making is at the core of human and artificial thought, which is why scientists introduced machine learning (ML) into artificial intelligence (AI). AI is a platform or solution that appears to be intelligent and can often exceed the performance of humans. It is a broad description of any device that mimics human or intellectual functions, such as mechanical movement, reasoning or problem solving.