BetaGroup - Tech Trends in 2017, a snap shot by BetaGroup

@BetaGroup /betagroup

In order to complete Thierry Geert’s Google New Trends presentation, here are some extra trends that might interest you…

Summary-1) Artificial Intelligence and Machine Learning

-2) Intelligent Apps

-3) Intelligent Things

-4) Virtual and Augmented Reality

-5) Digital Twins

-6) Blockchain

-7) Converssational Systems (Dialog System)

-8) Digital Technology Platforms

-9) Adapative Security Architecture

-10) Mesh App & Service Architecture

-11) Humanized Big Data

-12) Physical Digital Integrations

-13) Everything on Demand

1) ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

Artificial intelligence (AI) and advanced machine learning (ML) are made up of technologies and processes like deep learning and neural networks. What began as algorithms to automate manual tasks, borrowing from advanced statistical techniques has developed into a broader framework and architecture that learns like a human might, and can use historical data to predict the future. These systems will become more adaptable and potentially operate autonomously.

In banking, you could use AI and machine-learning techniques to model current real-time transactions, as well as predictive models of transactions based on their likelihood of being fraudulent. Organizations seeking to drive digital innovation with this trend should evaluate a number of business scenarios in which AI and machine learning could drive clear and specific business value and consider experimenting with one or two high-impact scenarios..

There are also a lot of startups who deals with Machine Learning:

Below are 5 examples of machine learning that really ground what machine learning is all about.

-Spam Detection: Given email in an inbox, identify those email messages that are spam and those that are not. Having a model of this problem would allow a program to leave non-spam emails in the inbox and move spam emails to a spam folder. We should all be familiar with this example.-Credit Card Fraud Detection: Given credit card transactions for a customer in a month, identify those transactions that were made by the customer and those that were not. A program with a model of this decision could refund those transactions that were fraudulent.-Digit Recognition: Given a zip codes hand written on envelops, identify the digit for each hand written character. A model of this problem would allow a computer program to read and understand handwritten zip codes and sort envelops by geographic region.-Speech Understanding: Given an utterance from a user, identify the specific request made by the user. A model of this problem would allow a program to understand and make an attempt to fulfil that request. The iPhone with Siri has this capability.-Face Detection: Given a digital photo album of many hundreds of digital photographs, identify those photos that include a given person. A model of this decision process would allow a program to organize photos by person. Some cameras and software like iPhoto has this capability.

2) INTELLIGENT APPSIntelligent apps, which include technologies like virtual personal assistants (VPAs), have the potential to transform the workplace by making everyday tasks easier (prioritizing emails) and its users more effective (highlighting important content and interactions). However, intelligent apps are not limited to new digital assistants – every existing software category from security tooling to enterprise applications such as marketing or enterprise resource planning (ERP) will be infused with AI enabled capabilities.

Using AI, technology providers will focus on three areas — advanced analytics, AI-powered and increasingly autonomous business processes and AI-powered immersive, conversational and continuous interfaces. By 2018, Gartner expects most of the world’s largest 200 companies to exploit intelligent apps and utilize the full toolkit of big data and analytics tools to refine their offers and improve customer experience.

3) INTELLIGENT THINGSFor good reason, much has been written about the power of the Internet of Things. Intelligent things will leverage AI and ML to interact with humans and surroundings. Prominent examples are self-driving cars, drones, the artifacts that will increasingly make up the smart kitchen and smart home. Gartner predicts that these will increasingly be woven together into a fabric that will enhance our lives.

As intelligent things evolve and become more popular, they will shift from a stand-alone to a collaborative model in which intelligent things communicate with one another and act in concert to accomplish tasks. However, nontechnical issues such as liability and privacy, along with the complexity of creating highly specialized assistants, will slow embedded intelligence in some scenarios.

4) VIRTUAL & AUGMENTED REALITYVirtual reality (VR) and augmented reality (AR) transform the way individuals interact with each other and with software systems creating an immersive environment. For example, VR can be used for training scenarios and remote experiences. AR, which enables a blending of the real and virtual worlds, means businesses can overlay graphics onto real-world objects, such as hidden wires on the image of a wall. Immersive experiences with AR and VR are reaching tipping points in terms of price and capability but will not replace other interface models. Over time AR and VR expand beyond visual immersion to include all human senses. Enterprises should look for targeted applications of VR and AR through 2020.The differences between virtual and augmented reality is not often well defined. True virtual reality completely blocks out the real world whereas augmented reality adds to the already existing real world. Sometimes these forms that are somewhere between virtual and augmented reality are defined by other terms. For example, mixed reality is a mix of a digitized model of the real world combined with computer-generated models.

For example AR can be showed on a head-mounted display (HMD) which is a display device paired to the forehead such as a harness or helmet. HMDs place images of both the physical world and virtual objects over the user's field of view. Modern HMDs often employ sensors for six degrees of freedom monitoring that allow the system to align virtual information to the physical world and adjust accordingly with the user's head movements. HMDs can provide VR users mobile and collaborative experiences. Specific providers, such as uSens and Gestigon, are even including gesture controls for full virtual immersion.

Other displays are: -Eyeglasses, -HUD, -Contact Lenses, -Virtual retinal display, -Eye Tap, -Handheld, -Spatial, -Tracking, -Input devices.

5) DIGITAL TWINSWithin three to five years, billions of things will be represented by digital twins, a dynamic software model of a physical thing or system. Using physics data on how the components of a thing operate and respond to the environment as well as data provided by sensors in the physical world, a digital twin can be used to analyze and simulate real world conditions, responds to changes, improve operations and add value. Digital twins function as proxies for the combination of skilled individuals (e.g., technicians) and traditional monitoring devices and controls (e.g., pressure gauges).

Their proliferation will require a cultural change, as those who understand the maintenance of real-world things collaborate with data scientists and IT professionals.

Digital twins of physical assets combined with digital representations of facilities and environments as welldetailed digital representation of the real world for simulation, analysis and control.

as people, businesses and processes will enable an increasingly

One example of digital twins can be the use of 3D modeling to create a digital companion for the physical object. It can be used to view the status of the actual physical object, which provides a way to project physical objects into the digital world. For example, when sensors collect data from a connected device, the sensor data can be used to update a "digital twin" copy of the device's state in real time. The term "device shadow" is also used for the concept of a digital twin. The digital twin is meant to be an up-to-date and accurate copy of the physical object's properties and states, including shape, position, gesture, status and motion.

In another context, Digital twin can be also used for monitoring, diagnostics and prognostics. In this field, sensory data is sufficient for building digital twins. These models help to improve the outcome of prognostics by using and archiving historical information of physical assets and perform comparison between fleet of geographically distributed machines. Therefore, complex prognostics and Intelligent Maintenance System platforms can leverage the use of digital twins in finding the root cause of issues and improve productivity.

6) BLOCKCHAINBlockchain is a type of distributed ledger in which value exchange transactions (in bitcoin or other token) are sequentially grouped into blocks. Blockchain and distributed-ledger concepts are gaining traction because they hold the promise of transforming industry operating models in industries such as music distribution, identify verification and title registry.

They promise a model to add trust to untrusted environments and reduce business friction by providing transparent access to the information in the chain.

While there is a great deal of interest the majority of blockchain initiatives are in alpha or beta phases and significant technology challenges exist.Based on the Bitcoin protocol, the blockchain database is shared by all nodes participating in a system. The full copy of the blockchain has records of every Bitcoin transaction ever executed. It can thus provide insight about facts like how much value belonged a particular address at any point in the past.

Blockchain is secured way of online transaction. It typically follows following workflow:

Step 1: Digitally signed transaction initiation

Step 2: Transaction is sent to miner. Miner is technically verifier of all transactions

Step 3: Transaction is broadcast to all connected nodes as block

Step 4: Network accepts transaction if data is valid

Step 5: Receiver receives the transaction

7) CONVERSATIONAL SYSTEMS (DIALOG SYSTEM)Conversational systems can range from simple informal, bidirectional text or voice conversations such as an answer to “What time is it?” to more complex interactions such as collecting oral testimony from crime witnesses to generate a sketch of a suspect. Conversational systems shift from a model where people adapt to computers to one where the computer “hears” and adapts to a person’s desired outcome. Conversational systems do not use text/voice as the exclusive interface but enable people and machines to use multiple modalities (e.g., sight, sound, tactile, etc.) to communicate across the digital device mesh (e.g., sensors, appliances, IoT systems).

There are many different architectures for dialog systems. What sets of components are included in a dialog system, and how those components divide up responsibilities differs from system to system. Principal to any dialog system is the dialog manager, which is a component that manages the state of the dialog, and dialog strategy.

1)The user speaks, and the input is converted to plain text by the system's input recognizer/decoder, which may include:-automatic speech recognizer (ASR)-gesture recognizer-handwriting recognizer2)The text is analyzed by a Natural language understanding unit (NLU), which may include:-Proper Name identification-part of speech tagging-Syntactic/semantic parser3)The semantic information is analyzed by the dialog manager, that keeps the history and state of the dialog and manages the general flow of the conversation.

4)Usually, the dialog manager contacts one or more task managers, that have knowledge of the specific task domain.5)The dialog manager produces output using an output generator, which may include:-natural language generator-gesture generator-layout engine6)Finally, the output is rendered using an output renderer, which may include:-text-to-speech engine (TTS)-talking head-robot or avatarDialog systems that are based on a text-only interface (e.g. text-based chat) contain only stages 2–5.

A typical activity cycle in a dialog system contains the following phases:

8) DIGITAL TECHNOLOGY PLATFORMSDigital technology platforms are the building blocks for a digital business and are necessary to break into digital. Every organization will have some mix of five digital technology platforms: Information systems, customer experience, analytics and intelligence, the Internet of Things and business ecosystems. In particular new platforms and services for IoT, AI and conversational systems will be a key focus through 2020. Companies should identify how industry platforms will evolve and plan ways to evolve their platforms to meet the challenges of digital business.

There are five major focal points to enable digital capabilities and business models:

-Information systems-Customer experience-Analytics and intelligence-IoT-Business ecosystems

Organizations will increasingly have a mix from across these five digital technology platforms.

9) ADAPTIVE SECURITY ARCHITECTUREThe evolution of the intelligent digital mesh and digital technology platforms and application architectures means that security has to become fluid and adaptive. Security in the IoT environment is particularly challenging. Security teams need to work with application, solution and enterprise architects to consider security early in the design of applications or IoT solutions. Multilayered security and use of user and entity behavior analytics will become a requirement for virtually every enterprise.

Sun Microsoft lists the following as the objectives of Adaptive Security Architecture:

-Reduce threat amplification – it restricts the potential spread of a pandemic in a monoculture.-Shrink the attack surface – make the target of an attack smaller-Decrease attack velocity – slow the rate of attack-Reduce remediation time – respond to an attack quickly

-Facilitate the availability of data and processing resources – prevent or contain attacks that try to limit resources-Promote correctness of data and the reliability of processing resources – respond to attacks intended to compromise data or system integrity.

10) MESH APP & SERVICE ARCHITECTUREIn the mesh app and service architecture (MASA), mobile apps, web apps, desktop apps and IoT apps link to a broad mesh of backend services to create what users view as an "application." The architecture encapsulates services and exposes APIs at multiple levels and across organizational boundaries, balancing the demand for agility and scalability of services with composition and reuse of services. The MASA enables users to have an optimized solution for targeted endpoints in the digital mesh (e.g., desktop, smartphone, automobiles) as well as a continuous experience as they shift across these different channels.

consumers can invoke services by sending messages. These messages are typically transformed and routed by a service bus to an appropriate service implementation. This service architecture can provide a business rules engine that allows business rules to be incorporated in a service or across services. The service architecture also provides a service management infrastructure that manages services and activities like auditing, billing, and logging. In addition, the architecture offers enterprises the flexibility of having agile business processes, better addresses the regulatory requirements like Sarbanes Oxley (SOX), and changes individual services without affecting other services.

An example of service architecture is :

11) HUMANIZED BIG DATA

Big data has been a big topic for the past five years or so, when it started making headlines as a buzzword. The idea is that mass quantities of gathered data—which we now have access to—can help us in everything from planning better medical treatments to executing better marketing campaigns. But big data’s greatest strength—its quantitative, numerical foundation—is also a weakness.

In 2017 we’ll see advancements to humanize big data, seeking more empathetic and qualitative bits of data and projecting it in a more visualized, accessible way.

12) PHYSICAL DIGITAL INTEGRATIONS

Mobile devices have been slowly adding technology into our daily lives. It’s rare to see anyone without a smartphone at any given time, giving us access to practically infinite information in the real-world. We already have things like site-to-store purchasing, enabling online customers to buy and pick up products in a physical retail location, but the next level will be even further integrations between physical and digital realities. Online brands like Amazon will start having more physical products, like Dash Buttons, and physical brands like Walmart will start having more digital features, like store maps and product trials.

13) EVERYTHING ON DEMANDThanks to brands like Uber (and the resulting madness of startups built on the premise of being the “Uber of ____”), people are getting used to having everything on demand via phone apps. In 2017, we all expect to see this develop even further. We have thousands of apps available to us to get rides, food deliveries, and even a place to stay for the night, but soon we’ll see this evolve into even stranger territory.

Anyone in the tech industry knows that making predictions about the course of technology’s future, even a year out, is an exercise in futility. Surprises can come from a number of different directions, and announced developments rarely release as they’re intended.

Still, it pays to forecast what’s coming next so you can prepare your marketing strategies (or your budget) accordingly.

Another example is Just Eat which is an online food order and delivery service. It acts as an intermediary between independent take-out food outlets and customers. It is headquartered in the United Kingdom and operates in 13 countries in Europe, Asia, Oceania, and the Americas. The platform allows customers to search for local take-out restaurants to place orders online, and to choose from pick-up or delivery options.

We hope that this document was interesting for you. As it was mentioned above:

Anyone in the tech industry knows that making predictions about the course of technology’s future, even a year out, is an exercise in futility.

Surprises can come from a number of different directions, and announced developments rarely release as they’re intended.

Still, it pays to forecast what’s coming next so you can prepare your marketing strategies (or your budget) accordingly.

BetaGroup Team

Sources: Forbes, Gartner, Wikipedia & innovationexcellence.com

@BetaGroup /betagroup