SAP recently posted a new report titled: Trend Report 2018 - Emerging Technology Trends. This report takes a look at new technology trends that will impact all businesses over the next few years. In part one of our blog post, we focused on emerging technology, in this post, we will focus on technology that is further down the horizon. Here are a few major hightlights from the report.
ON THE HORIZON - Technology or concepts in prototyping or design phase
Brain Computer Interfaces
Autonomous Robots/Drones/Vehicles – The Rise of the Machine
The robotics market is highly dynamic now, companies outside the classical robotics market invest and with China, a new international player has emerged. Hardware costs will go down and light-weight materials and 3D printing will allow to create new and cheaper models faster than before. Battery and energy efficiency will be a decisive factor. Robots are now able to learn, and they have gained flexibility, speed, and manual finesse. The advances in data processing will free robots from former computing restraints. Advanced sensors, voice recognition, and machine learning algorithms will drive the interactivity of robot and human-robot collaboration will make major breakthroughs including voice, face, emotional and behavioral recognition. For now, robots have no broad understanding of the context nor the environment and they do not understand complex human behavior. Empathy seems to be out of scope for now but would have with big implications for employment and the future of work and life.
Industrial robots will increasingly use intelligent features such as predictive analytics, self-learning and swarm behavior. Developments are adaptive robots with scanning and sensor technologies, 3D printing, high level semantics, collaboration with operator and new human-machine interfaces. Professional service robots will mostly found in medical, field, and entertainment but increasingly classical services such as butler, kiosk, service robot. The ratio of connected and autonomous cars will rise fast. Nontraditional tech companies are gaining traction in the very technology that makes cars run, such as driver assistance systems, dashboard functions and autonomous driving and mapping.
Drones in all variants are now a stable technology with demand rising mainly around agriculture use cases, delivery, remote maintenance as well as asset and inventory tracking.
Personal robots are developed for household/daily care, assisting functions, and multipurpose work. They still have problems with most daily tasks, which will need another 10 years of development.
Intelligent Assistants – Smart Support for Humans The intelligent assistant would be an advanced version of conversational systems, using machine learning and robotics. Assistants have the potential to transform the way we interact with IT, with each other, how we learn and do our jobs and tasks. They would erase the borders between humans and IT/machines and create true co-workers. Intelligent assistants would not only be able to take over tasks that previously only humans could do but assisting humans as well, including context sensitivity, human-machine interactions via voice, language and gesture, potentially neuronal interfaces and learning capabilities. Assistants will be able to predict and recommend actions, too, and to build relationships with humans over time.
Up to now, conversational systems still need to learn the full human communication spectrum including emotional intelligence and the ambiguity of human behavior is still a problem for algorithms.
Individuals may use several different assistants and we will probably see a mix of very specialized and more generic ones. If and to what extend these assistants will be embedded in devices or robots or have human-like features will be a matter of role, context and working environment. If assistants will merge partly or fully with humans via neuronal links or implants will depend on feasibility, costs, risks and acceptance by the society and we will need to answer many ethical considerations.
Bio Computing – Using Nature‘s Computation One way to solve the limits of current miniaturization is to use biological molecules for computing. Biological computing uses synthesized biological components – mostly DNA – to store and manipulate data, analogous to processes in the human body. It computes by using enzymes, that react with DNA strands.
Biological computing allows very small and fast and potentially parallel computing process, with great accuracy and unmatched energy eﬃciency. The first DNA based computer was launched in 2002 but the technology is still in very early prototype stage, with the MIT being one of the most prolific re-search institutes.
Present barriers result in low accuracy, the need for new methodologies, and interoperability issues with other computing systems. Use cases would be ID cards, DNA chips, cryptography, and genetic programming.
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