«What is the next step in the evolution of IoT systems? The answer is data, information, which is a radical shift from assets, from things to input for decision making,» stated Michael Minkevich, VP of Technology Services at Luxoft, in this SYS-CON.tv interview at @ThingsExpo, held November 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA.

read more

(c)iStock.com/davincidig

It’s not words, but how we say them that speaks volumes. By analysing your tone of voice, a new computer algorithm can predict whether your relationship will last, and it arguably does so more accurately than professional therapists.

Now, I’m not here to advise you on couples therapy. What I’m interested in is how algorithms like this one are going to change the way we live and provide a massive opportunity for the cloud industry.

Data + machine learning algorithm = AI

Popular culture leads us to believe that the future of artificial intelligence (AI) will be a single, magical supercomputer. Think HAL 9000 from 2001: A Space Odyssey, or the ship’s computer on Star Trek. But we’re starting to understand now that we’ve been looking at it all wrong.

x.ai has created an AI-powered personal assistant that schedules meetings for you. In the US alone, there are 87 million knowledge workers who spend up to five hours a week scheduling meetings

The future of AI isn’t about one giant super-intelligence. Instead, it’s about many small, dedicated agents that know you intimately and work on your behalf to improve your everyday life. That could be helping you shop, get to work or, even, find a partner. Each is focused on a discrete task, and each gets better over time and adapts to your needs as they evolve.

This kind of smart software isn’t new. It’s been almost 20 years since chess Grandmaster Garry Kasparov lost to IBM’s Deep Blue in a chess match.

Amazon has had machine learning for many years too. Every time the giant retailer serves up a recommendation, AI made the decision and what would be the best option for you on that particular day.

But if Amazon can have AI working to sell you more things, shouldn’t you have your own AI working to find better deals from other vendors, looking for reliable reviews, or keeping you ahead of the latest trends?

Of course, algorithms are also nothing new, but it’s become vastly easier to write and use them in recent years. The main driver behind this has been cheap and ubiquitous computing, an abundance of data, and a platform that brings these elements together: cloud computing.

For AI to be useful it needs all three: a good algorithm, millions of relevant data points, and computing power to process it quickly so it can drive actions in real-time. Lose any one of these and it’s not nearly as useful in the modern world.

The point is this: your business is going to get disrupted by AI, but not in the way you might have thought. Rather than preparing yourself for one monolithic, all knowing consciousness, it’s going to be a trillion tiny agents all focused on specific tasks, and all of them hungry for data.

Finding the time

One example of this focused approach is x.ai. The New York City startup has created an AI-powered personal assistant that schedules meetings for you. It’s a simple enough to use. You connect your calendar to x.ai and then CC in amy@x.ai whenever a discussion starts about scheduling. Once you copy in Amy, she takes over the thread, finds a mutually agreeable time and place, and sets up the meeting for you. The person at the other end has no idea she’s not a human.

How brilliant is that? In the US alone, there are 87 million knowledge workers who spend nearly five hours per week scheduling meetings. I don’t imagine many of us enjoy the process and would more than happy to delegate to a virtual assistant instead.

It’s not such a simple fix though. The technology that powers the virtual assistant is complex. Amy passes each email through natural language processing and supervised learning engines that understand the context of the information. The data is then enriched and stored in MongoDB where it is combined with other information such as the user’s preferred working hours and their current time zone. Based on these inputs Amy determines the appropriate course of action and crafts a response. There’s no app to install. Amy exists only in the cloud.

This is only one example of how algorithms are changing our lives. Cities are starting to automatically adjust traffic flow based on weather, construction, congestion, events, and other real-time factors. Ads you land on while browsing your favourite sites run an algorithm over your data and match it with their calculated preferences about you to serve up something that is highly relevant.

Many of the most popular cloud and data technologies are already responding to this trend. Apache Spark is full of machine learning libraries that come built into the framework. Google released TensorFlow as an open source project, which makes the machine learning technology behind Google Translate and many other products, freely available to anyone.

With these tools easily accessible by developers, it’s easy to see how many different tasks could be quickly re-imagined as algorithms that delivered as convenient services. In fact Peter Sondergaard at Gartner is predicting a whole new Algorithm Economy.

Things you can’t algorithm

Cloud computing solved the two biggest hurdles for AI: abundant, low cost computing and a way to leverage massive volumes of data. However, a number of challenges remain. Chief among those challenges is the one affecting the whole industry: skills.

Cloud computing solved the two biggest hurdles for AI – abundant, low cost computing, and a way to leverage massive volumes of data – however a number of challenges remain

While open source libraries make it easy to get started, for genuinely powerful AI you need actual data scientists. People with strong programming backgrounds, a deep understanding of mathematics and statistics, as well as business domain knowledge. Needless to say, those people are rare.

The other challenges will mainly be around the data. Most modern data is inherently unstructured – it’s geographic data, sensor data, and social data. If your stack is built on decades-old relational technology you are going to struggle to feed modern algorithms running in the cloud.

Despite the challenges, the main lesson is this: small, focused, cloud-based algorithms are going to be the AI that changes our lives over the next decade. It’s better to solve one problem really well, than it is to solve 100 problems poorly. Today’s markets reward companies that maintain their focus.

To take advantage of these trillion robots in the cloud, you’re going to need a thoroughly modern infrastructure.

(c)iStock.com/baona

To understand hybrid cloud, it is important to understand the basics of cloud computing services, its models – software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) – and deployment methods – private, public, and of course hybrid. But why choose between public or private cloud when you can have the best of both worlds?

Hybrid clouds take advantage of the benefits of both environments to create a super breed of cloud built to help enterprises get the most return on investment by managing mission critical data on-premises in a private cloud while moving less critical or ‘bursty’ applications to a public cloud.

Hybrid cloud can be a hybrid SaaS, a hybrid PaaS or hybrid IaaS and can be really valuable for dynamic or highly changeable workloads. Hybrid SaaS combines SaaS solutions with an on-premise software application to provide the benefits of SaaS with more security and user control.

The functional aspect of the software is presented through the cloud, hosted by the software provider. A user logs into the application from a web browser and accesses a cloud-hosted environment including the user interface, functionality, and mechanism that moves files. The users’ data, however, is stored in whatever environment they choose until it is encrypted and transferred over the Internet.

With hybrid SaaS, you can store data on an on-premise server that is managed by your organisation or you can use the cloud. The user now has more control over where to keep the storage. Security concerns are eliminated without sacrificing the benefit of cloud software.

Whilst the most common needs to adopt cloud computing in an organisation remain the same, such as full elasticity, measured service, broad access, self service and resource pooling, understanding the unique business needs is also crucial to adopt the best cloud offering. These needs can be unique and change over time, hence why choosing a cloud that communicate and shares information securely in the private cloud or hybrid cloud is critical.

Some products can provide a powerful suite of solutions to enable internal and external collaboration, client engagement, and help manage complex transactions and processes. Ideally, having a platform that combines internal and external collaboration in one secure space which can be accessed from anywhere and from any device proves to be the most effective when it comes to collaboration and managing data in the cloud.

Manufacturing has widely adopted standardized and automated processes to create designs, build them, and maintain them through their life cycle. However, many modern manufacturing systems go beyond mechanized workflows to introduce empowered workers, flexible collaboration, and rapid iteration.
Such behaviors also characterize open source software development and are at the heart of DevOps culture, processes, and tooling.

read more

Electric power utilities face relentless pressure on their financial performance, and reducing distribution grid losses is one of the last untapped opportunities to meet their business goals. Combining IoT-enabled sensors and cloud-based data analytics, utilities now are able to find, quantify and reduce losses faster – and with a smaller IT footprint. Solutions exist using Internet-enabled sensors deployed temporarily at strategic locations within the distribution grid to measure actual line loads.

read more

The time of year when crystal balls get a viewing and many pundits put out their annual predictions for the coming year. Rather than thinking up my own, I figured I’d regurgitate what many others are expecting to happen.
7 Future Predictions for the Internet of Things – IoT is one of the hottest terms and trends. From connected cars, homes, businesses and more, connected devices are becoming more prevalent in our lives. Stable Kernel looks at the future economic growth, development of smart cities, wearables, privacy challenges and how voice commands will become the norm.
Top 10 Humanoid Robots Designed To Match Human Capabilities And Emotions – While once a dream of The Jetsons, companion robots in the home will become as common as pets, even if the pet is a robot. WT VOX explores whether robots could fully replace humans by 2045 as some predict and takes a look at the top 10 that are starting to match human capability.

read more

Mobility and cloud computing have combined to obliterate any so-called network security perimeter. Corporate data has now been let loose to roam in a world of cyber thieves, manipulators and untrusted infrastructure. What is a security professional to do?
According to Bill Odell, the Dell Vice President of Marketing for Endpoint Device Management, you need to protect the enterprise front door. Since devices are the network’s gateways, endpoint device management is now the key to protecting your enterprise data. That is why I was truly excited to speak with Bill at Dell Peak Performance in Las Vegas earlier this year.

read more

This IBM Redbooks® Point-of-View publication discusses cloud workloads on the mainframe. A cloud built on a mainframe, such as IBM® zEnterprise® or others in the IBM System z® family, has several distinct advantages.

read more

One cloud does not fit all organizations.
That’s true whether it is a public or private cloud. A hybrid cloud option allows your business to create a custom solution that fits your organizational needs.
However, there are always questions with new solutions. We reached out to industry thought leaders to answer some of the marketplace’s most pressing questions on hybrid cloud.
In this eBook, you’ll learn why thought leaders like Kevin Jackson, founder and CEO GovCloud Network, look at hybrid cloud from the viewpoint of hybrid IT. You’ll also hear from Shelly Kramer, co-CEO, V3+Broadsuite, on what CIOs need to consider when adopting hybrid cloud.

read more