Trends Identified
Alternative internet delivery
Affordable access to the internet remains one of the major challenges to getting more poor people online. The poorest people in the least developed countries pay more for internet access than citizens in developed countries in absolute and relative terms.
2016
Ten Frontier Technologies for International Development
Institute of Development Studies (IDS)
Alternative food sources
Insects have been a food staple in some countries for centuries, but they are now beginning to disrupt Western agriculture and aquaculture with their high feed efficiencies and attractive environmental credentials. With increasing demand for high-protein food and new products appearing regularly, this is a breakthrough market to watch.
2018
Global opportunity report
DNV GL
Alternative data, machine learning and artificial intelligence are a powerful combination
Enterprises need to become data driven to succeed in the current business environment. The ability to make both structured, unstructured and alternative datasets actionable can be a significant differentiator. In some cases it is necessary just to stay relevant. This is true across all industries, including finance. Traditionally, investor analysis involved looking at a company’s 10Ks and 10Qs, market data and the technical analysis of the trading activity. Nowadays, investors see an opportunity to use alternative datasets from sources such as Quandl to make better decisions. For example, they might look at month-over-month sales and compare those figures to the company’s peer group, and track the company’s supply chain for insight into future production flows, sales and sources of risk. Clearly, alternative datasets, analytics, and machine learning/ artificial intelligence (AI) are a powerful combination. The advancements in AI are coming rapidly. New techniques such as reinforcement learning as well as generative adversarial networks (GANs), which are a type of deep learning neural network, are starting to attract attention. They are also extending capabilities beyond what was possible with standard machine learning and deep learning algorithms. GANs for instance will allow AI to compete with itself to come up with an optimal model in real time, resulting in greater accuracy. A potential application is in risk management. All these technology enhancements have not brought us much closer to having a generalized AI (capable of super-humanlike intelligence across any subject). However, companies are achieving success by focusing on narrow AI applications where an algorithm can be trained to do one thing extremely well, surpassing the capabilities of what a human could do on their own. Financial firms are doing this to detect spoofing behavior or risky trading activity. For example, they use these narrow AI algorithms to build applications that are much more sophisticated and accurate than their traditional counterparts. Generalized AI – the ability for a machine to successfully perform any intellectual task that a human being can – is still about a decade away. Yet it is becoming easier to interact with Siri, Alexa and Google Assistant, and every question people ask is another narrow AI application. Before long, it will be possible to put together millions of questions and answers, drawing us farther down the path to generalized AI – especially as the technology improves.Until then, the greatest opportunity and challenge is knowing the right narrow AI applications to develop. Commercial success is dependent on having a clear understanding of how, when and why people will use something new rather than relying on their tried and tested human intelligence. Behavioral science methods are becoming recognized as the differentiator to deliver this understanding, and the way forward could be through “collaborative intelligence”, involving a reimagining of people and machines working together. Achieving this requires behavioral scientists to do a new depth of analysis of clients’ cognitive and manual working processes. This ensures the best of human and machine capabilities can be leveraged to deliver this new way of working. In the meantime, Nasdaq’s strategy is to build a community of data suppliers and connect them with a community of data consumers, and then provide the services they need to make the data actionable. As we build up our data repositories, and we connect them to Nasdaq Financial Framework, those datasets and technologies will become available to an array of market participants.
2019
NASDAQ DECODES: TECH TRENDS 2019 -The technology trends that are driving the world of markets forward
Nasdaq
Alternative aquaculture
Aquaculture is expected to grow significantly to meet the forecast aggressive demand for fish and shell sh. Improving environmental standards through modular, land-based systems, as well as alternative feedstocks and closed-loop systems, can provide new business opportunities and conserve natural marine ecosystems.
2018
Global opportunity report
DNV GL
Altered Identities
Identity is an umbrella term used to describe how people perceive themselves and others. An individual belongs to multiple identity groups, through birth, assimilation, or achievement and each particular group influences their values and beliefs. Historically key influences for identity have been often along ethnic, racial, national and religious lines, however out to 2040 new influences are likely to emerge. For example, online social interaction is likely to increase in sophistication and scale. Social networking sites fused with ‘virtual reality’ networking sites, such as Second Life, may lead to new ways of interacting, new variations of language and the formation of complex relationships between individuals on a global scale.
2010
Global strategic trends - out to 2040
UK, Ministry of Defence
All products have become services
“I don't own anything. I don't own a car. I don't own a house. I don't own any appliances or any clothes,” writes Danish MP Ida Auken. Shopping is a distant memory in the city of 2030, whose inhabitants have cracked clean energy and borrow what they need on demand. It sounds utopian, until she mentions that her every move is tracked and outside the city live swathes of discontents, the ultimate depiction of a society split in two.
2016
Eight predictions for 2030
World Economic Forum (WEF)
Algorithms for Quantum Computers - Developers are perfecting programs meant to run on quantum computers
Quantum computers exploit quantum mechanics to perform calculations. Their basic unit of computation, the qubit, is analogous to the standard bit (zero or one), but it is in a quantum superposition between two computational quantum states: it can be a zero and a one at the same time. That property, along with another uniquely quantum feature known as entanglement, can enable quantum computers to resolve certain classes of problems more efficiently than any conventional computer can. This technology, while exciting, is notoriously finicky. A process called decoherence, for example, can disrupt its function. Investigators have determined that stringently controlled quantum computers that have a few thousand qubits could be made to withstand decoherence through a technique known as quantum error correction. But the largest quantum computers that laboratories have demonstrated so far—the most notable examples are from IBM, Google, Rigetti Computing and IonQ—contain just tens of quantum bits. These versions, which John Preskill of the California Institute of Technology named noisy intermediatescale quantum (NISQ) computers, cannot perform error correction yet. Nevertheless, a burst of research on algorithms written specifically for NISQs might enable these devices to perform certain calculations more efficiently than classic computers.
2018
Top 10 Emerging Technologies of 2018
Scientific American
Algorithms and software to verify large programmes
The development of algorithms and software to verify large programmes for cloud and grid- based applications is one of the key fields of research and development in ICT. In the medium term, progress in software development technologies will set down a path of improving methods to verify industrial hardware and software systems. Theoretical bases for algorithms allowing for effective verification have already been developed and tested. In the foreseeable future, these methods will become part of the technology cycle of companies which create programmes for critical applications. In a number of cases verification technologies are relevant not only for major software systems, but also to reduce the time take to develop various medium-complexity applications where reliability is a particularly high requirement (built-in computer technologies for on-board control systems in space and military equipment, medical equipment, mobile telephones, etc.).
2016
Russia 2030: science and technology foresight
Russia, Ministry of Education and Science of the Russian Federation
Algorithms and software for knowledge engineering
There has been some development of algorithms and software for knowledge engineering at the juncture of learning system and cognitive psychology theories and research on artificial intelligence. Knowledge engineering extends concepts that were previously – in research on artificial intelligence – only applicable to computers (machine learning) to any learning system (where learning is understood to mean the acquisition and transformation of knowledge with a view to its application). New models for working with large amounts of memory (including semantic databases) are becoming increasingly abundant.
2016
Russia 2030: science and technology foresight
Russia, Ministry of Education and Science of the Russian Federation
Algal bio-fuels
Example of Organizationsactive in the area: Synthetic Genomics/ExxonMobil (US), Global Algae Innovations (US), Algenol (US).
2018
Table of disruptive technologies
Imperial College London