Trends Identified
Neurotechnology
Convergence of emerging science, engineering and technology over the past decade has resulted in the emergence of neurotechnology, which can be defined as the manipulations of technical and computational tools to measure, analyse and re-wire the working of the nervous system in order to identify the properties of nerve cell activities, diagnose illnesses, restore and/or rescue neurological functions and even controlled by external devices. Application of neurotechnology is not limited to medical industry; it can be applied in financial market, law enforcement, marketing, education and warfare (ESET Neurotechnology Report, ASM, 2017)
2017
Science & Technology Foresight Malaysia
Malaysia, Academy of Sciences Malaysia
Neurotechnologies
Emerging neurotechnologies offer great promise in diagnosis and therapy for healthy ageing and general human enhancement. However, some neurotechnologies raise profound ethical, legal, social and cultural issues that require policy attention.
2016
OECD Science, Technology and Innovation Outlook 2016
OECD
Neurostimulation
Neurostimulation covers those technologies that stimulate, or block, certain parts of the nervous system, particularly within the brain. The technology is used to treat various severe neurological disorders, such as Parkinson’s disease, depression and insomnia. Neurostimula on can also be used to augment human cognitive function. Neurostimulation has historically been performed through both invasive (surgery) and non-invasive means (taking pills, electrical stimulation). Wearable headsets are now being marketed that work by adding a slight voltage to neurons, letting them fire more easily. These devices use transcranial direct current stimula on (tDCS), which has the potential to enhance language, learning, attention, problem solving, coordination and memory functions; help combat insomnia, anxiety, and depression; and manage pain. The future use of both “smart drugs” and tDCS could allow some people to gain a competitive advantage over others.
2013
Metascan 3 emerging technologies
Canada, Policy Horizons Canada
Neuroscience: 'We'll be able to plug information streams directly into the cortex'
By 2030, we are likely to have developed no-frills brain-machine interfaces, allowing the paralysed to dance in their thought-controlled exoskeleton suits. I sincerely hope we will not still be interfacing with computers via keyboards, one forlorn letter at a time. I'd like to imagine we'll have robots to do our bidding. But I predicted that 20 years ago, when I was a sanguine boy leaving Star Wars, and the smartest robot we have now is the Roomba vacuum cleaner. So I won't be surprised if I'm wrong in another 25 years. Artificial intelligence has proved itself an unexpectedly difficult problem. Maybe we will understand what's happening when we immerse our heads into the colourful night blender of dreams. We will have cracked the secret of human memory by realising that it was never about storing things, but about the relationships between things. Will we have reached the singularity – the point at which computers surpass human intelligence and perhaps give us our comeuppance? We'll probably be able to plug information streams directly into the cortex for those who want it badly enough to risk the surgery. There will be smart drugs to enhance learning and memory and a flourishing black market among ambitious students to obtain them. Having lain to rest the nature-nurture dichotomy at that point, we will have a molecular understanding of the way in which cultural narratives work their way into brain tissue and of individual susceptibility to those stories. Then there's the mystery of consciousness. Will we finally have a framework that allows us to translate the mechanical pieces and parts into private, subjective experience? As it stands now, we don't even know what such a framework could look like ("carry the two here and that equals the experience of tasting cinnamon"). That line of research will lead us to confront the question of whether we can reproduce consciousness by replicating the exact structure of the brain – say, with zeros and ones, or beer cans and tennis balls. If this theory of materialism turns out to be correct, then we will be well on our way to downloading our brains into computers, allowing us to live forever in The Matrix. But if materialism is incorrect, that would be equally interesting: perhaps brains are more like radios that receive an as-yet-undiscovered force. The one thing we can be sure of is this: no matter how wacky the predictions we make today, they will look tame in the strange light of the future.
2011
20 predictions for the next 25 years
The Guardian
Neuromorphic technology
Even today’s best supercomputers cannot rival the sophistication of the human brain. Computers are linear, moving data back and forth between memory chips and a central processor over a high-speed backbone. The brain, on the other hand, is fully interconnected, with logic and memory intimately cross-linked at billions of times the density and diversity of that found in a modern computer. Neuromorphic chips aim to process information in a fundamentally different way from traditional hardware, mimicking the brain’s architecture to deliver a huge increase in a computer’s thinking and responding power. Miniaturization has delivered massive increases in conventional computing power over the years, but the bottleneck of shifting data constantly between stored memory and central processors uses large amounts of energy and creates unwanted heat, limiting further improvements. In contrast, neuromorphic chips can be more energy efficient and powerful, combining data-storage and data-processing components into the same interconnected modules. In this sense, the system copies the networked neurons that, in their billions, make up the human brain. Neuromorphic technology will be the next stage in powerful computing, enabling vastly more rapid processing of data and a better capacity for machine learning. IBM’s million-neuron TrueNorth chip, revealed in prototype in August 2014, has a power efficiency for certain tasks that is hundreds of times superior to a conventional CPU (Central Processing Unit), and more comparable for the first time to the human cortex. With vastly more compute power available for far less energy and volume, neuromorphic chips should allow more intelligent small-scale machines to drive the next stage in miniaturization and artificial intelligence. Potential applications include: drones better able to process and respond to visual cues, much more powerful and intelligent cameras and smartphones, and data-crunching on a scale that may help unlock the secrets of financial markets or climate forecasting. Computers will be able to anticipate and learn, rather than merely respond in pre-programmed ways.
2015
Top 10 emerging technologies of 2015
World Economic Forum (WEF)
Neuromorphic Hardware – Using Nature’s Designs
Neuromorphic hardware is based on conventional processors that are conceptually inspired by neurobiological architectures. Neuromorphic systems are at the very early prototype stage between basic and applied research but the topic is gaining traction within the industry. Companies such as IBM, Intel, Samsung, HP and Google are using the neuromorphic concept to build energy-effi cient networks inspired by biology. Neuromorphic hardware promises new designs for diff erent ways of computing and extreme performance while using little energy. It is suitable for use cases based on machine learning, in particular for pattern recognition, event-driven vision processing, and robotics. It is in competition with quantum computing and in both cases the complexities are potential threats. For now, classical GPUs are more accessible and easily programmable than neuromorphic silicon and programming neuromorphic hardware requires new methodologies that still have to be developed. Based on our learning from the neuromorphic hardware research project within the “Human Brain Project” at University Heidelberg, but we believe that the neuromorphic approach will lead to new concepts in combination with machine learning and powerful graphical GPUs.
2018
Trend Report 2018 - Emerging Technology Trends
SAP
Neuro-technology
Smart technologies will be crucial technologies until 2030 and beyond. They will help societies to monitor, detect as well as respond or adapt to changes in their environment. Smart technologies are already and will become a part of our daily lives. 37 For example, smart electricity metering has addressed the problem of the losses of electricity due to theft. 38 Emerging technologies in the area of artificial intelligence have received much attention in which computer systems that carry out tasks normally done by humans, such as speech recognition and decision making. Another example is robotics which is understood as machines or mechanical systems that automatically handle tasks. Mesoscience 39 powered virtual reality gives us the possibility to realize the logic and structural consistence between problems, physical models, numerical methods and hardware, which, together with the dramatic development of computing technology, is opening a new era for virtual reality. Digital Automation characterizes the increasing ability of computers to overtake cognitive - and not just physical - tasks, enabling recent innovations like driverless cars, IBM Watson, e-discovery platforms for legal practice, and personalization algorithms for Web search, e-commerce, and social networks. The potential consequences of automation and artificial intelligence on employment are emerging areas in need of examination; the expansion of computing and machine intelligence is likely to affect healthcare, education, privacy and cybersecurity, and energy and environmental management. Recent studies are pointing to the possibility that a significant number of jobs - or job tasks - are amenable to automation, leading to a job polarization where demand for middle-income jobs are reduced while non-routine cognitive jobs (e.g., financial analysis or computer programming) and non-routine manual jobs (e.g., hairdressing) would be less unaffected. At this point, more study is warranted to understand implications for employment and socio-economic development in a specific national context. Autonomous vehicles or self-driving cars hold the promise to increase traffic efficiency, productivity, reduce traffic congestions and pollution, and save driving time. In 2016, the Dubai Autonomous Transportation Strategy was launched which foresees 25 per cent of all trips in Dubai to be driverless by 2030. The Autonomous Transportation Challenge as launched as a request for proposals to global R&D centres to apply this technology in Dubai. It will make Dubai the world’s largest R&D lab for driverless transportation. 40
2016
Global sustainable development report 2016
United Nations
Neural stem cell therapy
The technology that collects adult stem cells from the patient’s body (skin) and cultivate it to neural stem cells, and implant it onto damaged brain. There is currently no treatment for degenerative brain diseases such as Alzheimer’s and Parkinsons disease. We expect this could provide a fundamental treatment method to replace dead brain cells into neural stem cells.
2013
KISTEP 10 Emerging Technologies 2013
South Korea, Korea Institute of S&T Evaluation and Planning (KISTEP)
Network Growth
Technological advances, and a greater understanding of social, physical and virtual network behaviour, will converge to drive new types of network architecture and applications. These will be increasingly accessed by remote and distributed means. Technology applications such as those supporting social networking will continue to reconfigure and enable new social models and means of interacting. This will raise fundamental issues about privacy, security, legal frameworks and the mechanisms for influence. The rate of growth of hardware development is unlikely to reduce before 2020, and software technology may fail to keep pace with these advances, contributing to an increasing proportion of major project failures. The growth of many networks is unlikely to be governed by top-down planning; such growth is likely to occur in a decentralised manner, often analogous to nature. In order to improve effectiveness and reduce vulnerability increased understanding of network topology and nodal behaviour, including people, will be required. There will be changes in network technology driven by: the need to improve end-to-end security; the requirement to support large numbers of Internet-enabled devices; and the ability to directly convert from optical to wireless connectivity. The evolution of ICT devices will be driven by their increasingly wide range of applications and rising demand by society. Increased Internet penetration across the globe, particularly in heavily populated areas, will influence Internet content and ownership.
2010
Global strategic trends - out to 2040
UK, Ministry of Defence