Trends Identified
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
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 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 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 motor fuels
Alternative motor fuels are intended to satisfy future demands for liquid fuel and are characterised by acceptable costs, minimal environmental and health impact, and increased reliability of supply to domestic markets. In relation to the expected growth in demand for motor fuel, which in Russia now accounts for at least 80-85% of petroleum product output, this alternative product could replace an increasing share of fuels derived from crude oil. According to experts, the likelihood of such fuels competing with traditional fuels after 2020 is high.
2016
Russia 2030: science and technology foresight
Russia, Ministry of Education and Science of the Russian Federation
Amazon and Facebook Lead OTT Bids for Major Sporting Rights
Delivering attractive premium content is critical to the success of any video service. Acquiring exclusive rights to popular sporting events is a well- trodden path to increased viewing figures.
2018
Top Tech trends 2018
Juniper Research
Ambient computing - Putting the Internet of Things to work
Possibilities abound from the tremendous growth of embedded sensors and connected devices—in the home, the enterprise, and the world at large. Translating these possibilities into business impact requires focus—purposefully bringing smarter “things” together with analytics, security, data, and integration platforms to make the disparate parts work seamlessly with each other. Ambient computing is the backdrop of sensors, devices, intelligence, and agents that can put the Internet of Things to work.
2015
Tech trends 2015 - The fusion of business and IT
Deloitte
Ambient Voice In New Places
Bernard, who invests Amazon’s own money in startups that leverage the Alexa and Echo ecosystem, says that “while voice services started in the home and will continue to grow there, we’re beginning to see this technology move beyond the home and into new on-the-go environments–in the car, the enterprise, in the gym or on a run, and numerous other mobile scenarios. We see this is a key factor that will make interacting with voice services a truly pervasive daily habit, and we expect to see different device concepts emerge that address the unique requirements of each usage scenario.”
2018
The Most Important Tech Trends Of 2018, According To Top VCs
Fast Company
America First meets One Belt, One Road
Everyone will be a China watcher.
2018
Top Policy Trends of 2018
PWC
Americans are somewhat apprehensive about trying some potential new inventions themselves; driverless cars garner the most widespread interest
Most new inventions appeal at first to a relatively small group of adventuresome early adopters, with the bulk of consumers following along only after they have had a chance to see for themselves what the fuss is about. And indeed, many Americans have a pronounced skepticism toward some new inventions that they might be able to use or purchase in the relatively near future.
2014
US views of technology and the future - science in the next 50 years
Pew Research Center