Living with technology a decade from now. Dell Technologies and the Institute for the Future conducted an in-depth discussion with 20 experts to explore how various social and technological drivers will influence the next decade and, specifically, how emerging technologies will recast our society and the way we conduct business by the year 2030.
There is no universally agreed upon determination of which technologies are considered emerging. For the purpose of this study, IFTF explored the impact that Robotics, Artificial Intelligence (AI) and Machine Learning, Virtual Reality (VR) and Augmented Reality (AR), and Cloud Computing, will have on society by 2030. These technologies, enabled by significant advances in software, will underpin the formation of new human-machine partnerships, according to the IFTF.
Talk of digital transformation is virtually everywhere in Information Technology circles and Operations Technology circles. My long and varied experiences have often placed me at the boundaries where the two meet—and are now increasingly overlapping.
The take on robotics is right on target. And forget about all the SciFi scare stories that mainstream media loves to promote. The future is definitely all about human-machine partnership or collaboration. For example I often talk with EMTs about life in the rescue squad. These people are always in the gym. Our population in the US has gotten so large and obese that they often have to lift 300+ lb. people who haven’t the strength to help themselves up. Think about a robot assistant helping the EMT.
The AI discussion is also fraught with prominent people like Ray Kurzweil or Elon Musk giving dystopian SciFi views of the future. We are a long way from “intelligence.” Where we are is really the use of machine learning and neural networks that help machines (and us) learn by deciphering recurring patterns.
Back to the study, the authors state, “If we start to approach the next decade as one in which partnerships between humans and machines transcend our limitations and build on our strengths, we can begin to create a more favorable future for everyone.”
Jordan Howard, Social Good Strategist and Executive Director of GenYNot, sees tremendous promise for the future of human-machine partnerships: “Many of the complex issues facing society today are rooted in waste, inefficiency, and simply not knowing stuff, like how to stop certain genes from mutating. What if we could solve these problems by pairing up more closely with machines and using the mass of data they provide to make breakthroughs at speed? As a team, we can aim higher, dream bigger, and accomplish more.”
Liam Quinn, Dell Chief Technology Officer, likens the emerging technologies of today to the roll-out of electricity 100 years ago. Quinn argues that we no longer fixate on the “mechanics” or the “wonders” of electricity, yet it underpins almost everything we do in our lives. Similarly, Quinn argues, in the 2030s, today’s emerging technologies will underpin our daily lives. As Quinn provokes, “Imagine the creativity and outlook that’s possible from the vantage point these tools will provide: In 2030, it will be less about the wonderment of the tool itself and more about what that tool can do.”
By 2030, we will no longer revere the technologies that are emerging today. They will have long disappeared into the background conditions of everyday life. If we engage in the hard work of empowering human-machine partnerships to succeed, their impact on society will enrich us all.
While offshoring manufacturing jobs to low-cost economies can save up to 65% on labor costs, replacing human workers with robots can save up to 90% of these costs.
China is currently embarking upon an effort to fill its factories with advanced manufacturing robots, as workers’ wages rise and technology allows the industry to become more efficient. The province of Guangdong, the heartland of Chinese manufacturing, has promised to invest $154 billion in installing robots.
Buoyed by their commercial success, the adoption of robots will extend beyond manufacturing plants and the workplace. Family robots, caregiving robots, and civic robots will all become commonplace as deep learning improves robots’ abilities to empathize and reason. Google recently won a patent to build worker robots with personalities.
Artificial Intelligence and Machine Learning
Approximately 1,500 companies in North America alone are doing something related to AI today, which equates to less than 1% of all medium-to-large companies. We’re seeing this in the financial services industry already, with data recognition, pattern recognition, and predictive analytics being applied to huge data sets on a broad scale. In a 2015 report, Bank of America Merrill Lynch estimated that the AI market will expand to $153 billion over the next five years—$83 billion for robots, and $70 billion for artificial intelligence-based systems.
In addition to their ability to make decisions with imperfect information, machines are now able to learn from their experiences and share that learning with other AI programs and robots. But AI progress also brings new challenges. Discussions surrounding who or what has moral and ethical responsibility for decisions made by machines will only increase in importance over the next decade.
Virtual Reality and Augmented Reality
Although both Virtual and Augmented Reality are changing the form factor of computing, there is a simple distinction between the two. VR blocks out the physical world and transports the user to a simulated world, whereas AR creates a digital layer over the physical world.
Despite the difference, both technologies represent a fundamental shift in information presentation because they allow people to engage in what Toshi Hoo, Director of IFTF’s Emerging Media Lab, calls “experiential media” as opposed to representative media. No longer depending on one or two of our senses to process data, immersive technologies like AR and VR will enable people to apply multiple senses—sight, touch, hearing, and soon, taste and smell—to experience media through embodied cognition.
Over the next decade, Hoo forecasts that VR, combined with vast sensor networks and connected technologies, will be one of many tools that enable distributed presence and embodied cognition, allowing people to experience media with all their senses.
It’s important to recognize that Cloud Computing isn’t a place, it’s a way of doing IT. Whether public, private, or hybrid (a combination of private and public), the technology is now used by 70% of U.S. organizations. This figure is expected to grow further, with 56% of businesses surveyed saying they are working on transferring more IT operations to the cloud, according to IDG Enterprise’s 2016 Cloud Computing Executive Summary.
While the cloud is not a recent technological advancement, cloud technology only really gathered momentum in recent years, as enterprise grade applications hit the market, virtualization technologies matured, and businesses became increasingly aware of its benefits in terms of efficiency and profitability. Increasing innovation in cloud-native apps and their propensity to be built and deployed in quick cadence to offer greater agility, resilience, and portability across clouds will drive further uptake. Start-ups are starting to use cloud-native approaches to disrupt traditional industries; and by 2030, cloud technologies will be so embedded, memories from the pre-cloud era will feel positively archaic by comparison.
Human Machine Partnership
Recent conversations, reports, and articles about the intersection of emerging technologies and society have tended to promote one of two extreme perspectives about the future: the anxiety-driven issue of technological unemployment or the optimistic view of tech-enabled panaceas for all social and environmental ills.
Perhaps a more useful conversation would focus on what the new relationship between technology and society could look like, and what needs to be considered to prepare accordingly.
By framing the relationship between humans and machines as a partnership, we can begin to build capacity in machines to improve their understanding of humans, and in society and organizations, so that more of us are prepared to engage meaningfully with emerging technologies.
Digital (Orchestra) Conductors
Digital natives will lead the charge. By 2030, many will be savvy digital orchestra conductors, relying on their suite of personal technologies, including voice-enabled connected devices, wearables, and implantables; to infer intent from their patterns and relationships, and activate and deactivate resources accordingly.
Yet, as is often the case with any shift in society, there is a risk that some segments of the population will get left behind. Individuals will need to strengthen their ability to team up with machines to arrange the elements of their daily lives to produce optimal outcomes. Without empowering more to hone their digital conducting skills, the benefits that will come from offloading ‘life admin’ to machine partners will be limited to the digitally literate.
Work Chasing People
Human-machine partnerships will not only help automate and coordinate lives, they will also transform how organizations find talent, manage teams, deliver products and services, and support professional development. Human-machine partnerships won’t spell the end of human jobs, but work will be vastly different.
By 2030, expectations of work will reset and the landscape for organizations will be redrawn, as the process of finding work gets flipped on its head. As an extension of what is often referred to as the ‘gig economy’ today, organizations will begin to automate how they source work and teams, breaking up work into tasks, and seeking out the best talent for a task.
Instead of expecting workers to bear the brunt of finding work, work will compete for the best resource to complete the job. Reputation engines, data visualization, and smart analytics will make individuals’ skills and competencies searchable, and organizations will pursue the best talent for discrete work tasks.
Walking through one of the Halls at the Hannover Messe, you suddenly find yourself in the Cloud—computing that is. There was Amazon Web Services, Microsoft Azure, and Google Cloud. The Manufacturing IT section just keeps growing. And getting more interesting.
One interesting aspect—I’m beginning to see articles speculating on the “end of Cloud computing.” Wonder what could come next?
Meanwhile, here is one piece of Cloud news I picked up. Amazon Web Services (AWS), an Amazon company, announced the general availability of AWS IoT Analytics, a fully-managed service that makes it easy to run simple and sophisticated analytics on massive volumes of data from IoT devices and sensors, empowering customers to uncover insights that lead to more accurate decisions for their IoT and machine learning applications.
AWS IoT Analytics collects, pre-processes, enriches, stores, and analyzes IoT device data at scale so companies can easily identify things like the average distance traveled for a fleet of connected vehicles, or how many doors are locked after work hours in a smart building, or assess the performance of devices over time to predict maintenance issues and better react to changing environmental conditions. With AWS IoT Analytics, customers don’t have to worry about all the cost and complexity typically required to build their own IoT analytics platform. AWS IoT Analytics is available today in the US East-1 (N. Virginia), US East-2 (Ohio), US West (Oregon), and EU (Ireland) regions, with support for additional regions coming soon.
“AWS IoT Analytics is the easiest way to run analytics on IoT data. Now, customers can act on the large volumes of IoT data generated by their connected devices with powerful analytics capabilities ranging from simple queries to sophisticated machine learning models that are specifically designed for IoT,” said Dirk Didascalou, VP, IoT, AWS. “As the scale of IoT applications continues to grow at a rapid rate, AWS IoT Analytics is designed to provide the best tools for our customers to mine their raw data, gaining insights that lead to intelligent actions.”
AWS IoT Analytics also has features like a built-in SQL query engine to answer specific business questions and more sophisticated analytics, enabling customers to understand the performance of devices, predict device failure, and perform time-series analysis. Also, AWS IoT Analytics offers access to machine learning tools with hosted Jupyter Notebooks through seamless integration with Amazon SageMaker. Customers can directly connect their IoT data to a Jupyter Notebook and build, train, and execute models at any scale right from the AWS IoT Analytics console without having to manage any of the underlying infrastructure.
Using AWS IoT Analytics, customers can apply machine learning algorithms to device data to produce a health score for each device in a fleet, prevent fraud and cyber intrusion by detecting anomalies on IoT devices, predict device failures, segment fleets of devices, and identify other rare events that may have great significance but are hard to find without analytics. And, by using Amazon QuickSight, a fast, cloud-powered business analytics service, in conjunction with AWS IoT Analytics, it is easy for customers to surface insights in easy-to-build visualizations and dashboards.
AWS IoT Analytics can accept data from any source, including external sources using an ingestion API, and integrates fully with AWS IoT Core. Launched in 2015, AWS IoT Core is a managed cloud platform that lets connected devices easily and securely interact with cloud applications and other devices. AWS IoT Analytics also stores the data for analysis, while providing customers the ability to set data retention policies.
Modjoul, Georgia Pacific, Teralytic, Siemens, OSIsoft, Pentair, 47Lining, Domo, NetFoundry, and Laird Technologies are just a few of the customers and Amazon Partner Network members using AWS IoT Analytics to uncover valuable insights within their data and use those findings to innovate across their specialized businesses.
Modjoul is a data invention company for wearable technology that is focused on keeping employees safe. “Our mission is to keep industrial workers safe, whether they’re working in or out of a vehicle,” said Eric Martinez, CEO and Founder, Modjoul. “In an eight-hour shift, we collect data 28,800 times per day from our connected activity tracker worn by each of our employees that includes 40 metrics including heart rate and activity level. With AWS IoT Analytics, we not only analyze all that health data, but also enrich it with location and environmental data, such as outdoor temperature, to get accurate analytics that prevent injuries and save lives. Today, we’re operating better and faster.”
Georgia Pacific is one of the world’s leading makers of tissue, pulp, paper, packaging, building products, and related chemicals. “At Georgia Pacific, our industry-leading dispensers allow us to deliver solutions to customers, not just sell products,” said Erik Cordsen, IoT Program Architect and Product Leader, Georgia-Pacific. “Now we are focused on making our dispensers ‘smart’ by adding sensors and connectivity that allow us to improve customer experience by providing real-time information about product levels and other statistics. With thousands of endpoints continuously feeding in data, we are using AWS IoT Analytics to enrich messages with location and product metadata in order to calculate platform health and value to our customers. AWS lets my team focus on solving the business problem instead of wrestling with technology.”
Teralytic is a soil health company focused on improving farmer’s yield by monitoring and improving the condition of their soils. “We have a network of soil-sensing IoT devices embedded in the soil from which data are collected, fed, and analyzed for us to understand the health of our customers’ agricultural ecosystems,” said Dan Casson, Vice President of Engineering, Teralytic. “We chose AWS IoT Analytics for its ability to filter outlier readings from our calculations and proactively detect issues as they arise so we can resolve them faster. In some cases, we’re able to identify and prevent issues before they occur. With AWS IoT Analytics, we use Machine Learning models to help detect situations where nutrients in the soil are at risk of leeching into ground water or runoff into surface water so the farmer can adjust the watering schedule, if needed. In addition to the environmental benefits, these machine learning models can help reduce a farmer’s costs as well as potentially increasing their yield.”
47Lining develops big data solutions and delivers big data managed services — built from underlying AWS building blocks like Amazon Redshift, Kinesis, Amazon Simple Storage Service (Amazon S3), and Amazon DynamoDB — to help customers manage their data across a variety of verticals including energy, life sciences, gaming, and financial services. “Because AWS IoT Analytics is designed around time-series data, it’s a great fit for our customers in industrial, energy, and oil & gas, who seek real-time decision support and process optimization,” said Mick Bass, Senior Vice President, Big Data Practice, 47Lining.
Domo is a computer software company that specializes in business intelligence tools and data visualization. “Since our inception in 2010, AWS has been a trusted service provider that keeps up with the demands of our dynamic business,” said Jay Heglar, Chief Strategy Officer, Domo. “We extended our relationship with AWS to IoT Analytics because we wanted a flexible option to enable faster access to machine-generated data for our customers. Through our proprietary connector to AWS IoT Analytics, we are ensuring our customers have access to one of the most innovative solutions, allowing them to leverage machine-generated data at scale.”
Laird Technologies designs, develops, manufactures, and supports wireless systems solutions and performance materials for wireless and other advanced electronics applications. “By combining our long range wireless sensor and gateway products with AWS IoT, our customers have been able to quickly and securely get data from their devices into the cloud,” said Paul Elvikis, Business Development Director for Industrial, Laird Technologies. “Unfortunately, they would often get overwhelmed with the amount of sensor data that would start coming in. Customers would struggle to figure out how to do anything with it. AWS IoT Analytics has been a great help in extending our capabilities to solve that issue for our customers.”
NetFoundry gives its customers and their applications control of their networks without any telco, hardware, or private circuit constraints. “The capabilities of AWS IoT Analytics in enabling the transformation of vast amounts of data into actionable information, without the high costs and steep learning curve of other IoT platforms, enables NetFoundry’s IoT customers to get the ROI they need,” said Michael Kochanik, Co-founder and Global Head of Channel Revenue, NetFoundry.“With AWS IoT Analytics, we can integrate IoT networking capabilities to provide our IoT customers with ‘one-stop shopping’ including data collection, networking, analysis, transformations, storage and visualization. Partnering with AWS enables our customers to get integrated, end-to-end agility, security, performance and cost efficiency at scale.”
AWS offers over 125 fully featured services for compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, virtual and augmented reality (VR and AR), media, and application development, deployment, and management from 54 Availability Zones (AZs) within 18 geographic regions and one Local Region around the world, spanning the U.S., Australia, Brazil, Canada, China, France, Germany, India, Ireland, Japan, Korea, Singapore, and the UK.
The Internet of Things ecosystem is changing computing in almost a seismic shift. But like geology, it builds up over time and then the event happens before you know it.
We had centralized, on-site computing revolutionized by PCs. We networked PCs and wound up with centralized computing in the cloud. Demands from building the Internet of Things (or Industrial Internet of Things for us manufacturing and production geeks) expose the flaws of cloud computing. The next hot thing—edge.
Yesterday the CEO/co-founder of Zededa talked with me about the computing platform his company is building with no less a mission than to build the largest computing company on Earth without owning infrastructure. Its vision—create a new edge economy that allows applications to run anywhere.
Some of what follows may sound familiar. I’ve talked with many companies doing a piece of what Zededa has laid out, but none are as audacious as this.
In brief, Zedeta…
- Closes $3.06M in Seed Funding
- Pioneering a secure, cloud-native approach to real-time edge applications at hyperscale for solutions ranging from self-driving cars to industrial robots
- Built a team comprised of distinguished engineers from top tech companies in cloud, networking and open source to solve the edge computing puzzle and disrupt the status quo
- Seed round was led by Wild West Capital; other investors include Almaz Capital, Barton Capital and Industry Veteran Ed Zander, former CEO of Motorola and former COO of Sun Microsystems
“Tomorrow’s edge computing environment that enables digital transformation will be distributed, autonomous and cooperative. The edge is complex and not only has to scale out securely, but simultaneously must become friendlier for app developers. That’s the problem we are solving at ZEDEDA,” stated ZEDEDA CEO and Co-Founder Said Ouissal. “It will require a drastic shift from today’s embedded computing mindset to a more secure-by-design, cloud-native approach that unlocks the power of millions of cloud app developers and allows them to digitize the physical world as billions of ‘things’ become smart and connected.”
ZEDEDA will use the funding for continued research and product development, investment in community open-source projects for edge computing as well as further investment in sales and marketing initiatives. ZEDEDA investors include Wild West Capital and Almaz Capital, whose funding was part of a broader group investors, some of whom also invested in IoT/edge companies Theatro and Sensity Systems (now Verizon).
In the coming wave of pervasive computing, real-time apps, cyber-physical systems and data services such as machine learning and analytics will become commonplace. ZEDEDA envisions an open ecosystem and a completely new technology stack that creates a service fabric essential to achieving the hyperscale that will be required in edge computing.
To realize that goal, ZEDEDA has pulled together a distinguished roster of industry veterans from legendary technology companies with expertise in areas of operating systems, virtualization, networking, security, blockchain, cloud and application platforms. This unique blend of skills combines with the team’s deep connections to core open-source projects and standardization bodies. The team’s work has directly contributed to software and system patents as well as industry standards used by billions of people around the world today.
“A new paradigm and massive innovation is needed to meet demand for IoT and edge computing,” said Kevin DeNuccio, Founder of Wild West Capital and ZEDEDA’s lead investor. “Massive shifts in technology, including the proliferation of IoT, paves the way for industry disruption, which large incumbents tend to inhibit. Disruption takes a combination of an entrepreneurial team with a very unique set of collective experience, groundbreaking ideas, and the ability to garner immediate traction with global industrial leaders, who can transform their business with machine learning and artificial intelligence delivered by the Edge connected IoT world. ZEDEDA is simply one of the most promising edge computing startups out there.”
“Operations Technology teams face major challenges when it comes to fully realizing the advantages of an IoT world. Their worlds are becoming massively connected systems dealing with virtualization, networking and security,” stated Christian Renaud, Research Director, IoT at 451 Research. “Our recent research shows that while OT teams have the application plans for leveraging IoT, the vast majority of organizations’ IT resources and capabilities are maxed out. This leaves open the question of how these edge applications and IoT will scale out without compromising security or taxing resources even further in the future.”
Ouissal told me, “Edge is the next big wave, bigger than cloud, simply because of the sheer size of the number of devices. The goal is ubiquitous compute where applications want to interact real-time. The problem with the cloud is that it’s centralized. This ecosystem is truly Cyberphysical—just like your Industry 4.0.”
The current IoT model of sending all data to the cloud for processing, won’t scale due to:
- Privacy issues
Three problems that the company is attacking:
1. Moving apps now running in the cloud to the edge
2. Edge-to-edge communication, key for autonomous systems, peer-to-peer
3. Security, cloud requires cyber security, but at the edge we must add physical security—someone could walk in and carry out an intelligent device
Ouissal often mentioned the need to rethink management of the edge. There exists a big difference between managing cloud and edge. Zedeta is tacking the variety of management challenges for updating and managing thousands to millions of embedded devices.
Solutions the team are developing include:
1. Security-built on platform, use keys, trusted, health check with every plug in, embedded virtualization
2. management-virtualization->can run multiple sessions on a device, eg robot motion on one session and analytics on another all on same embedded system, can scale this to millions of devices
3. Networking-monitor, watch lists, anomaly detection, analyze why, VPN architecture
This is all fascinating. I can’t wait to talk with competitors and potential competitors in a couple of weeks in Hannover and during some upcoming trips to get responses.
Gathering data, visualization on many devices and screens, and connecting with standards including OPC UA and BACnet attracted a crowd of developers and users to the Iconics World Wide Customer Conference this week in Providence, RI.
“Connected Intelligence is our theme at this year’s summit and it has a dual meaning for us,” said Russ Agrusa, President and CEO of Iconics. “First, it refers to our extensive suite of automation software itself and how it provides out-of-the-box solutions for visualization, mobility, historical data collection, analytics and IIoT. The second point is that Iconics, over the last 30 years, has built a community of partners and customers who will have the opportunity to meet our software designers and other employees and have one-on-one discussions on such topics as; Industry 4.0, IIoT, cloud computing, artificial intelligence (AI) and the latest advances in automation software technology. It is truly a high energy and exciting event.”
Key technologies showcased at the Iconics Connected Intelligence Customer Summit included:
1. Industry 4.0 and the Industrial Internet of Things
2. Unlocking data and making the invisible, visible
3. Secure strategies and practices for industrial, manufacturing and building automation
4. Predictive AnalytiX using expert systems such as FDD and AI Machine Learning
5. Hot, warm and cold data storage with plant historians for the cloud and IIoT
Integration With AR, VR, and Mixed Reality Tech
The recent v10.95 release of GENESIS64 HMI/SCADA and building automation suite includes 3D holographic machine interface (HMI), which can be used with Microsoft’s HoloLens self-contained holographic computing device. This combination of Iconics software with Microsoft hardware allows users to visualize real-time data and analytics KPIs in both 2D and 3D holograms. When combined with Iconics AnalytiX software, users can take advantage of additional fault detection and diagnostics (FDD) and Hyper Historian data historian benefits, providing needed “on the spot” information in a hands-free manner.
“These new hands-free and mixed reality devices enable our customers and partners to ‘make the invisible visible’,” said Russ Agrusa, President and CEO of ICONICS. “There is a massive amount of information and value in all that collected and real-time data. Data is the new currency and we make it very easy to uncover this untapped information. We welcome this year’s summit attendees to get a glimpse at the future of HMI wearable devices such as Microsoft’s HoloLens and RealWear HMT1, HP and Lenovo Virtual reality devices.”
Mobile-Head-mounted tablet-style device
The V10.95 release of GENESIS64 HMI/SCADA and building automation suite includes Any Glass technology, which can be used with self-contained head-wearable computing devices. HMT-1 from RealWear demonstrated the visualization of real-time and historical data KPIs with voice driven, hands-free usage.
Featuring an intuitive, completely hands-free interface, the RealWear HMT-1 is a rugged head-worn solution for industrial IoT data visualization, remote video collaboration, technical documentation, assembly and maintenance instructions and streamlined inspections right to the eyes and ears of workers in harsh and loud field and manufacturing environments.
Support for multiple OSs and devices
Iconics has always been Microsoft Windows application and will continue to do so. However, IoTWorX Industrial Internet of Things (IIoT) software automation suite includes support for multiple operating systems including Windows 10 IoT Enterprise and Windows 10 IoT Core, as well as a large variety of Linux embedded operating systems including Ubuntu and Raspbian.
Users can connect to virtually any automation equipment through supported industry protocols such as BACnet, SNMP, Modbus, OPC UA, and classic OPC Tunneling. Iconics’ IoT solution takes advantage of Microsoft Azure cloud services to provide global visibility, scalability, and reliability. Optional Microsoft Azure services such as Power BI and Machine Learning can also be integrated to provide greater depth of analysis.
The following Operating systems are currently being certified for IoTWorX:
• Windows 10 IoT Enterprise
• Windows 10 IoT Core
• Red Hat Enterprise Linux 7
• Ubuntu 17.04, Ubuntu 16.04, Ubuntu 14.04
• Linux Mint 18, Linux Mint 17
• CentOS 7
• Oracle Linux 7
• Fedora 25, Fedora 26
• Debian 8.7 or later versions, openSUSE 42.2 or later versions
• SUSE Enterprise Linux (SLES) 12 SP2 or later versions
Hot, Warm, Cold Data Storage
Hyper Historian data historian integrates with and supports Microsoft Azure Data Lake for more data storage, archiving and retrieval.
When real-time “hot” data is collected at the edge by IoT devices and other remote collectors, it can then be securely transmitted to “warm” data historians for mid-term archiving and replay. Hyper Historian now features the ability to archive to “cold” long-term data storage systems such as data lakes, Hadoop or Azure HD Insight. These innovations help to make the best use of historical data at any stage in the process for further analysis and for use with machine learning.
Among the new analytical features are a new 64-bit BridgeWorX64 data bridging tool, a new 64-bit ReportWorX64 reporting tool, several new Energy AnalytiX asset performance charts and usability improvements. In addition, Iconics has introduced a new BI Server.
• AnalytiX-BI – Provides data aggregation using data modeling and data sets
• ReportWorX64 – Flexible, interactive, drag & drop, drill-down reporting dashboards
• BridgeWorX64 – Data Bridging and with drag-and-drop workflows that can be scheduled
• Smart Energy AnalytiX – a SaaS based energy and facility solution for buildings
• Smart Alarm AnalytiX – a SaaS based alarming analysis product that uses EEMUA
In 2030 every organization will be a technology organization and as such businesses need to start thinking today about how to future-proof their infrastructure and workforce, according to a report published by Dell Technologies. The research, led by the Institute for the Future (IFTF) alongside 20 technology, academic and business experts from across the globe, looks at how emerging technologies such as artificial intelligence, robotics, virtual reality, augmented reality and cloud computing, will transform our lives and how we work over the next decade. The report, titled ‘The Next Era of Human-Machine Partnerships‘ also offers insight on how consumers and businesses can prepare for a society in flux.
Interesting thing about this report is that it is not simply Dell’s technology or market strategy wrapped in the guise of a “research” report like the typical analyst job.
The report forecasts that emerging technologies, supported by massive advancements in software, big data and processing power, will reshape lives. Society will enter a new phase in its relationship with machines, which will be characterized by:
- Even greater efficiency and possibility than ever before, helping humans transcend our limitations
- Humans as “digital conductors” in which technology will work as an extension of people, helping to better direct and manage daily activities
- Work chasing people, in which by using advanced data-driven matchmaking technologies, organizations can find and employ talent from across the world
- People learning “in the moment,” as the pace of change will be so rapid that new industries will be created and new skills will be required to survive
Dell Technologies commissioned the study to help companies navigate an uncertain world and prepare for the future. Today, digital disruption is ruthlessly redrawing industries. For the first time in modern history, global leaders can’t predict how their industry will fare further down the line. According to Dell’s Digital Transformation Index, 52 percent of senior decision makers across 16 countries have experienced significant disruption to their industries as a result of digital technologies. And nearly one in two businesses believe there’s a possibility their company will become obsolete within the next three to five years.
Not your usual analyst firm, Institute for the Future (IFTF) is an independent, nonprofit 501(c)(3) strategic research and educational organization celebrating nearly 50 years of forecasting experience. The core of our work is identifying emerging trends and discontinuities that will transform global society and the global marketplace. The Institute for the Future is based in Palo Alto, California.
IFTF relied on its decades-long study on the future of work and technology, in-depth interviews with key stakeholders, and the opinions and ideas generated during an all-day facilitated workshop with a diverse set of experts from across the globe.
They studied robotics, artificial intelligence and machine learning, augmented reality and virtual reality, and cloud computing with the goal of projecting the impacts of these technologies by 2030. I had the opportunity to talk with Liam Quinn, sr. vice president and CTO of Dell Technologies about this report and he added comments about the Internet of Things. More on that interview in my next reflection of the report.
“Never before has the industry experienced so much disruption. The pace of change is very real, and we’re now in a do-or-die landscape. To leap ahead in the era of human-machine partnerships, every business will need to be a digital business, with software at its core,” said Jeremy Burton, chief marketing officer, Dell. “But organizations will need to move fast and build capacity in their machines, ready their infrastructure and enable their workforce in order to power this change.”
“We’ve been exposed to two extreme perspectives about machines and the future: the anxiety-driven issue of technological unemployment or the over optimistic view that technology will cure all our social and environmental ills,” said Rachel Maguire, research director, Institute for the Future. “Instead we need to focus on what the new relationship between technology and people could look like and how we can prepare accordingly. If we engage in the hard work of empowering human-machine partnerships to succeed, their impact on society will enrich us all.”
Other report highlights include:
- In 2030 humans’ reliance on technology will evolve into a true partnership with humans, bringing skills such as creativity, passion and an entrepreneurial mindset. This will align with the machines’ ability to bring speed, automation and efficiencies, and the resulting productivity will allow for new opportunities within industries and roles.
- By 2030 personalized, integrated artificial intelligence (AI) assistants will go well beyond what assistants can do now. They’ll take care of us in predictive and automated ways.
- Technology won’t necessarily replace workers, but the process of finding work will change. Work will cease to be a place but a series of tasks. Machine learning technologies will make individuals’ skills and competencies searchable, and organizations will pursue the best talent for discrete tasks.
- An estimated 85 percent of jobs in 2030 haven’t been invented yet. The pace of change will be so rapid that people will learn “in-the-moment” using new technologies such as augmented reality and virtual reality. The ability to gain new knowledge will be more valuable than the knowledge itself.
Exploring the technology areas:
Robotics—Buoyed by their commercial success, the adoption of robots will extend beyond manufacturing plants and the workplace. Family robots, caregiving robots, and civic robots will all become commonplace as deep learning improves robots’ abilities to empathize and reason.
Artificial Intelligence and Machine Learning—According to Michelle Zhou, an expert in AI, development can be thought of in three stages. The first is recognition intelligence—algorithms that recognize patterns; followed by cognitive intelligence—machines that make inferences from data; with the final stage being virtual human beings. It is plausible that, by 2030, we will enter the second stage in AI as this technology progresses.
Virtual Reality and Augmented Reality—Despite the difference, both technologies represent a fundamental shift in information presentation because they allow people to engage in what Toshi Hoo, Director of IFTF’s Emerging Media Lab, calls “experiential media” as opposed to representative media. The information layer that both technologies create will accelerate the melding of digital and physical identities, with digital drails and traces forming a digital coating over individuals’ physical environments.
Cloud Computing—It’s important to recognize that Cloud Computing isn’t a place, it’s a way of doing IT. It is already in wide use. For example, Chitale Dairy (in India) launched a ‘cow to cloud’ initiative in which each cow is fitted with RFID tags to capture data that is held in the cloud. The relevant analysis of this data is then sent to the local farmers via SMS and the web, to alert farmers when they need to change the cows’ diet, arrange vaccinations, etc. The timely delivery of this information is increasing the cows’ yield, supporting local farmers, whose livelihoods depend on the dairy farms, and enabling Chitale to manage a part of the supply chain which is normally fraught with uncertainty.
You can also check out the Dell blog.