Technology Trends 2020
4 trends shaping innovation in ICT
Keeping up with the relentless pace of change in the ICT industry is a daily challenge for modern tech companies. The key to long-term success lies in the ability to understand change almost before it occurs and seize the opportunity to shape evolving technologies.
#1: Spreading intelligence throughout the cloud
Connected smart machines, such as robots and autonomous vehicles, are fundamental to the evolving Networked Society. Enhanced cloud architecture that can distribute and share machine intelligence will enable smart connected machines to work on an increasingly higher level.
Supported by advancements in artificial intelligence (AI) – particularly in the areas of big data analytics, machine learning and knowledge management – rapid progress has been made in terms of what smart machines can do. Developments in connectivity and cloud technologies are making it possible to distribute and share machine intelligence more easily, at a lower cost, and on a much wider scale than before.
When connected to the cloud, smart machines will be able to use the powerful computational, storage and communication resources of state-of-the-art data centers. Today’s intelligent software robotics systems are capable of supporting repetitive administrative tasks with current development pushing toward advisory tasks. Codification shifts the capabilities of these systems into a new sphere that includes complex problem-solving and decision-making on a mass-market scale.
Connect, store, compute… and share
Shifting systems into the cloud enables communities of collaborating robots, machines, sensors and humans to process and share information. Each new insight collected within a community can be shared instantly, which increases the effectiveness of collaborative tasks, and improves performance throughout the system, with a common awareness of system state shared by all participants, as well as a shared knowledge base.
A distributed machine intelligence architecture offers lower implementation costs. Sharing a backbone of almost unlimited computational power makes it possible to build lightweight, low-cost robots and smart machines that require a low level of control and a minimum amount of sensors and actuators. Application-specific requirements related to responsiveness and speed will determine whether a local or global cloud is most suitable, and how much intelligence can be distributed.
Smart and mobile capabilities virtually everywhere
Intelligent clouds will create new value chains in many industry segments, but some of the forerunners include mining, agriculture, forestry and health care. New opportunities will open up for all organizations and people involved in the supply chain from the manufacturer to the customer. Consider an automated agriculture application. The application remotely controls farm machines to carry out various farming tasks. To harvest mature crops, for example, the system will control the necessary machines to cut, gather and transport them. Each individual machine will take local decisions to ensure secure completion of its set tasks, working in conjunction with all the machines involved in the harvesting. Weather reports gathered from another distributed cloud application are used by the system to carry out harvesting in an optimal way. Contact with the farmer occurs only when participating machines cannot resolve issues themselves.
The harvesting example highlights just one of the many coming applications that will rely on multiple information sources, cloud, and distributed machine intelligence. To ensure scalability and widespread uptake of such applications, the challenge lies in the rapid development and proliferation of universally accessible mobile capabilities. 5G will provide a resilient, high-availability, low-latency network that offers applications with integrated computing and storage resources that are ideally placed to meet latency requirements. 5G is well matched to industrial robotics applications because, like other radio technologies, it removes the need for cabling and minimizes infrastructure adaptions, but it also offers identity management, optimum placement of resources, and encryption for security and privacy.
#2: Self-managing devices
Combining sensory data with AI techniques enables the data from massive numbers of sensors to be merged and processed to create a higher-level view of a system.
Connected smart devices will change our lives in many ways. These range from simple services that open your garage door as your car approaches, for example, to radically new business opportunities involving services yet to be invented and markets yet to be discovered. Combined with intelligent handling of data, smart devices can boost the productivity and profitability of any business. But to enable the deployment of billions of smart devices, the cost of managing and monitoring them needs to be low. Evolving software and communications technology are shifting toward the creation of autonomous and self-managing devices.
The Internet of Things (IoT) means automation and intelligence in everything that is connected. This implies that a collective intuitive behavior among a wide range of devices for a wide range of applications is possible in the future. The connectivity allows objects to be sensed and actuated remotely, creating a bridge between the physical and digital world.
It’s the combination that triggers the effect
Beyond the physical devices embedded with processors, software, sensors, actuators, and connectivity, it is the combination of sensory data and AI that enables more effective and accurate interactions. It is by merging data from a multitude of sensors that a superior baseline for intelligent processing is created. These are the common denominators that push IoT development further.
From a connectivity perspective, two distinct and different use cases emerge. One extreme is the massive machine-type communication (massive MTC) that can support millions of connected devices such as energy meters and logistics tracking. Here, we are looking at device battery lifetimes beyond 10 years and cost reduction in the order of 80 percent as well as 20dB better coverage compared with present state-of-the-art solutions.
The other extreme is the critical machine-type communication (critical MTC), which entails real-time control and automation of dynamic processes in various fields such as vehicle-to-vehicle, vehicle-to-infrastructure, high-speed motion, and process control. Critical parameters to enable the performance required are network latency below milliseconds, ultra-high “five nines” (99.999 percent) reliability. The future network architecture needs to cater for both MTC scenarios.
#3: Fundamental technologies reshaping what networks can do
The laws of physics are the only real restriction on the development of communication networks. Ericsson is firmly committed to pursuing innovations that challenge present system limitations to help us reach beyond what is possible today.
While becoming increasingly versatile, the network’s fundamental building blocks are also becoming much smaller, mimicking the way living things have evolved. The network of the future will be akin to the digital embodiment of an intuitive organism that is able to handle vast amounts of consciously intelligent automated resources. New materials in combination with innovative manufacturing technologies promise to radically enhance network capabilities.
Which technologies have the greatest potential to spur network evolution in the near future?
In the semiconductor area, a wide range of new materials and manufacturing technologies will soon become mainstream. New packaging and integration technologies offer substantially increased bandwidth in addition to power reductions.
The semiconductor industry is also at the cusp of leveraging new memory technologies that will be able to take on different roles in the system memory hierarchy, as well as offering substantial improvements in system input and output performance.
The semiconductor industry advances through continuous scaling of traditional CMOS. Major players are working on the 10nm node, and industry roadmaps include 7nm and 5nm manufacturing technologies. Advanced 2.5D/3D integration techniques for non-monolithic integration have the capability to offer a whole system function integrated on a single chip. These solutions are both cost and energy efficient. The introduction of multicore central processing unit solutions at equal or lower power consumption than their predecessors is a predominant trend. Other trends include the development of various types of architectures aimed at significantly accelerating processing speed, such as massive parallel computing.
Electrons and light blending in new ways
Advances in silicon photonics allow for optical integration directly into the processing unit and other vital components in a communication network. Photonics will add properties such as low propagation loss, high data-transfer density, and excellent signal integrity. Bridging the gap between optical and electronic components, silicon photonics will shrink everything including the footprint, power consumption, and cost of high-speed network applications. Furthermore, silicon photonics will allow for greater disaggregation of functions, which opens up for more efficient hardware architectures, while enabling more aggregated data traffic.
Qubits – small but powerful
Slightly further into the future, quantum computing promises to bring about an exponential increase in computational power. Quantum computing is a technology that builds on the quantum properties of elementary particles (qubits). Qubits can be entangled with each other and can take on intermediate values compared with ordinary bits, which can only be either 1 or 0. This way, a quantum computer can increase parallelism and radically reduce the computing efforts needed to address certain types of problems. Researchers have already succeeded in creating qubits within a semiconductor, and the first fully operational quantum computer was displayed at the end of 2015. One of the main challenges is to keep the quantum state unperturbed, which requires extremely low temperatures and very good insulation from the surrounding environment.
By matching the exponential expansion of the digital universe with computational power that also grows exponentially, we are confident that we will be able to continue to stay on top of future demands for communication.
#4: Weaving security and privacy into the IoT fabric
In a world where everyone’s personal and financial information is available online, cyber security and privacy are very serious issues for consumers, corporations and governments alike. And the rapid rise of wearables, smart meters, and connected homes and vehicles makes security and privacy more vital than ever.
The complexity and heterogeneous nature of future networks and connected devices will require security and privacy controls to be made an intrinsic part of every device, network, cloud and application. However, controls are only valuable if they can be managed in a fast and coordinated manner across all layers – preferably in an automated fashion, steered by policies and analytical insights rather than by the choices of an individual. Automated security and privacy management that is pervasive yet observable and auditable are the core characteristics that can enable the future Networked Society.
Weaving intelligence on three levels
Three layers of technology make it possible to weave security and privacy protection into every layer of ICT: actual security controls, security analytics, and an adaptive security posture.
Over the next decade, key security controls will include data sovereignty and novel identity management controls that are tailored for people and devices, as well as encryption technologies. Some encryption technologies are in the early phases of development but will begin to appear on the market in the next three to five years, as the underlying technologies mature. New root-of-trust technologies that are applicable to both physical and virtual environments also show great promise, and significant effort will be put into making them a reality.
Novel security analytics technologies can now provide insights that make it possible to create predictive security systems as opposed to reactive ones. These technologies could be used to create disruptive data management solutions in the near future, but for this to happen, we need to have context-aware security feeds and security analytics algorithms that correlate these feeds, often across multiple domains.
The third technology layer, the adaptive security posture, is achieved through automation, based on security analytics insights and policy-based automated orchestration of security controls.
It will all be built on trusted networks
No single industry player will be able to address all of these challenges on its own. Industry-wide collaboration, joint development, and standardization – including vendors, service providers, and users – will be essential in order to realize the vision of a secure Networked Society that protects business assets and everyone’s privacy.
Traditionally, network service providers rank among the most trusted industry players. With this in mind, I believe that network service providers and their networks will be the foundation upon which the trust for everything else – devices, clouds, communications and applications – is built. At Ericsson, our focus is on enabling networks to play this key role across multiple industries.