Digital Technology is everywhere and it is redefining how we live, communicate, and work. Most importantly, it accelerates how we innovate.
Our digitized world accelerates innovation in many ways. The unprecedented pace of innovation we experience is powered by a massive digital ecosystem of resources, tools, infrastructure, and advanced capabilities that a few years ago would have been classified as ‘science fiction’. Our social structures and work models are impacted by recent innovations leading to new forms of communication and collaboration.
Movements such as the open-source and open collaboration both drive innovation and benefit from it.
The following summarizes the state of digital technologies, the things to come, and opportunities for innovation.
The world’s network of humans and machines generates astronomical volumes of data. It is estimated that our digital universe will size about 175 zettabytes by 2025 [1]. And this volume is growing exponentially. Of course, a significant percentage of this is just noise or even fake, low-quality, and unreliable data. But subsets of this data describe most types of human activity at a global scale, and at the same time, at an amazing level of detail.
Along with the events coming from connected devices and the measurements from billions of sensors — this massive, growing data set forms a new type of global memory: a vast amount of time-series of events and signals, machine states, news, opinions, research findings, discoveries, social interactions, decisions, environmental measurements and more.
The historians of the future will be able to look back and reproduce the planet’s activity with a granularity of seconds.
The machines of the future will be able to consume and make sense of our reality in ways we cannot even imagine. Of course, there are substantial ethical questions and concerns regarding ownership and usage of this data: how might we use, protect and leverage humanities’ accumulated data in an ethical way and for the greater good? This question could be an excellent theme for innovation on its own as we should not rely on the political will and corporate social responsibility; regulation is only a part of the solution. Technology itself can provide excellent ways of data ownership and ethical use.
Current data processing technologies are capable of making sense of the vast amounts of content we produce. Sophisticated algorithms can identify non-obvious patterns in the data and generate insights that make applications and devices smart.
Statistical and machine learning algorithms allow optimal, real-time decision-making in complex situations — for example, powering autonomous cars to react in optimal ways, enabling systems to identify cyber-attacks or controlling the traffic load of a smart city.
Artificial Intelligence empowers computers to see, to listen, to smell [ii], and soon to infer — to deduce new information from existing knowledge. Machines can already recognize human emotions, and they can communicate verbally at an impressive level.
But still, there is massive untapped value in the immense volumes of data and content we produce. The amount, the breadth, and depth of the world’s accumulated data create the need for new ways to summarize, visualize, and present information and insights.
To deal with the potential of information overload, companies will soon feel the need to move from regular reports and dashboards, to automatically synthesized data stories and smart insights. Corporate executives will soon interact with Business Intelligence agents providing instant answers to business questions instead of multi-page reports and worksheets.
The world needs novel methods to experience and make sense of the massive data we generate.
Intelligent content synopsis, personalized insights, ‘data navigation’ systems, VR and AR experiences to visualize complex ‘data worlds’, voice-driven insights are just some examples of potential innovations in the data space.
Computer vision and Natural Language Processing are characteristic examples of recent advances in the field of AI. Simply put, Computer Vision is the class of algorithms that allow a computer to see — to analyze images and videos and identify entities, objects, and specific instances such as locations, persons, things — or even the situation and the particular occasion visualized in an image.
Combined with other technologies such as fast networking and edge computing, Computer Vision creates opportunities for breakthrough innovations across domains, including transportation (autonomous cars, self-organizing fleets, navigation systems, and smart cities), medical systems (diagnosis), robotics and more.
At the same time, Language Understanding is making tremendous progress — making digital assistants more intelligent, contextual, and proactive. Your smart speaker will soon perform in a conversational mode, able to drive meaningful dialogues instead of just responding to an isolated question.
Digital assistants of the future will know who they are discussing with by analyzing the voice in real-time, and thus, they will be able to respond in personalized ways — matching the communication style and information needs of each specific user. By leveraging accumulated knowledge about the user, conversational experiences will become more personal, useful, and relevant for the particular user, the moment in time, and the estimated mood.
AI-powered translation is becoming more accurate and faster — recent advances allow speech to speech translation while maintaining the tone of voice and other voice attributes of the original speaker.
With the help of Artificial Intelligence, communication with machines is becoming seamless — hence the term Natural User Interfaces. People are already interacting naturally with smart devices — we can control simple functions of our home via our smart speaker or digital assistant or use voice commands to perform a web search and manage our calendar. Soon, we will be able to use not only voice but also haptic interfaces — a technology recreating the sense of touch by applying force feedback, vibrations, or motions to the user.
Technology is not only changing how we interact with our intelligent machines but also how we see and understand the world. Typically delivered through smart glasses, Augmented Reality (also known as extended or mixed reality) provides an extra layer of information relevant to the particular object a user is looking at or interacting with. It is what we get when physical and digital worlds blend into a single experience.
This area will grow rapidly — the space for innovation is unlimited: New content experiences, data exploration, and visualization techniques, dynamic mapping of the physical world, industrial applications for field workers — are just some examples of the applications that are on the way and are about to change the ways we understand the world.
Analogous progress and opportunity for innovation exist for Virtual Reality — which allows new digital worlds to be created and helps experience remote environments or situations e.g. join a human activity happening elsewhere.
Content creation and new experiences for VR/AR defines a great new stage for innovations across multiple domains and business scenarios, including e-commerce, gaming, social applications, learning and education, and healthcare.
Another significant advance is in digital tech is the Distributed Ledger Technologies (DLTs) such as the Blockchain. Such systems are based on an extensive network of nodes, each running on a different machine and maintaining a complete copy of a database of transactions. Nodes communicate with each other on a peer-to-peer fashion — with no single entity or authority controlling the system. A process of transaction verification and voting among the nodes makes these systems trustless and decentralized — they are not controlled by specific entities, and they don’t require trust between transaction participants.
Blockchain is considered to be one of the most disruptive technologies of our times. It is already powering cryptocurrencies, and it is expected to drive massive transformation in social, government, and financial sectors — as the solution for distributed, decentralized, and immutable storage of data or code (smart contracts).
Either purpose-specific or general-purpose, robots are already here in various forms. The discipline of Robotics combines multiple technologies, including sophisticated hardware, advanced software systems, and AI algorithms, to develop smarter, autonomous robots that can perform a widening range of tasks.
Robots are powered by advanced Artificial Intelligence and take advantage of the fast connectivity and edge computing, to perform complex cognitive tasks in real-time. Robots may come in multiple form factors — humanoids, nano-robots, military, industrial, and so on. New generations of robots are connected — they take advantage of the world’s knowledge and digital infrastructure to become smarter and more adaptive. In the near future, general-purpose robots will become truly proactive and autonomous with advanced context understanding and the ability to recognize complex situations and act accordingly. They will have a ‘personality’, individual communication styles, and strategies.
At the same time, advances in biotechnology, bio-engineering, and bioinformatics are driving massive changes across industries, from medical and pharmaceutical to agriculture and food engineering. Research in Quantum Computing presents significant progress — recent announcements of quantum supremacy demonstrate how this new class of systems outperforms the most powerful computing systems we currently have.
The years to come will bring impressive technological breakthroughs with a massive impact on our lives, markets, and societies. In our connected world, with the unprecedented level of information, knowledge, and ideas exchange, innovation is happening continuously, at scale, and in several forms. It may be driven by corporations, secret research labs, and universities but also from startups, individual scientists, or simply by thousands of creative individuals across the globe.
[1] https://www.seagate.com/files/www-content/our-story/trends/files/idc-seagate-dataage-whitepaper.pdf
Originally published in The Innovation Mode Blog
Cover image by Prawny from Pixabay