Trends Identified
Airships
Modern airships have the potential to transport fully assembled goods, supplies, and even large structures from the point of manufacture directly to their point of use without the need to build any of the usual transportation infrastructure such as roads, railways, runways or airports.
2016
Ten Frontier Technologies for International Development
Institute of Development Studies (IDS)
Airborne wind turbines
Example of Organizationsactive in the area: Google/Alphabet (US), Joby Energy (US), Altaeros (US), Kitegen (Italy), Enerkite (Germany).
2018
Table of disruptive technologies
Imperial College London
Aid flows are likely to diminish
By 2060, aid will have decreased in importance as a driver of Africa’s development. There will be new players in the aid industry (international NGOs, private businesses, non-DAC donors) bringing new approaches. However, the total volume of aid to Africa is likely to diminish.
2011
Africa in 50 Years’ Time
African Development Bank
AI's dominance in our lives
Futurist Ray Kurzweil has made a host of predictions – some inspirational, others downright alarming. One of them is the sci-fi-sounding notion that suggests artificial intelligence will one day become more powerful than human intelligence and improve itself at an exponential rate, otherwise known as ‘the singularity’.It’s far from the majority view, but few would deny that AI is only going to get more powerful. So, like in the case of gene editing, the tech and AI community will need to consider the ethical and societal implications of their work as AI comes to shape more realms of our life, from healthcare to financial markets. As for end-of-the-world extinction scenarios, it’s frankly not likely – but that shouldn’t obscure the fact that AI is poised to change how we live and work in profound ways. It is also not impossible that specific AIs could malfunction or run out of their creators’ control, leading to very human disasters, where lives are lost or millions of dollars are wiped out.
2017
10 grand challenges we’ll face by 2050
The BBC
AI-Led Automation
The breakout technology of 2019 is definitely going to be AI-led automation. It’s expected that data mining and management, business processes, information technology (IT) services, customer support, and many other sectors will witness automation via neural networks and machine-learning-based solutions.
2018
2019 Tech Forecast: 11 Experts Predict The Next Wave Of Breakout Technologies
Forbes
AI-fueled organizations
For some organizations, harnessing artificial intelligence´s full potential begins tentatively with explorations of select enterprise opportunities and a few potential use cases. While testing the waters this way may deliver valuable insights, it likely won’t be enough to make your company a market maker (rather than a fast follower). To become a true AI-fueled organization, a company may need to fundamentally rethink the way humans and machines interact within working environments. Executives should also consider deploying machine learning and other cognitive tools systematically across every core business process and enterprise operation to support datadriven decision-making. Likewise, AI could drive new offerings and business models. These are not minor steps, but as AI technologies standardize rapidly across industries, becoming an AI-fueled organization will likely be more than a strategy for success—it could be table stakes for survival.
2019
Tech trends 2019 - Beyond the digital frontier
Deloitte
AI-driven development
AI-driven development looks at tools, technologies and best practices for embedding AI into applications and using AI to create AI-powered tools for the development process. This trend is evolving along three dimensions: The tools used to build AI-powered solutions are expanding from tools targeting data scientists (AI infrastructure, AI frameworks and AI platforms) to tools targeting the professional developer community (AI platforms, AI services). With these tools the professional developer can infuse AI powered capabilities and models into an application without involvement of a professional data scientist. The tools used to build AI-powered solutions are being empowered with AI-driven capabilities that assist professional developers and automate tasks related to the development of AI-enhanced solutions. Augmented analytics, automated testing, automated code generation and automated solution development will speed the development process and empower a wider range of users to develop applications. AI-enabled tools are evolving from assisting and automating functions related to application development (AD) to being enhanced with business domain expertise and automating activities higher on the AD process stack (from general development to business solution design). The market will shift from a focus on data scientists partnered with developers to developers operating independently using predefined models delivered as a service. This enables more developers to utilize the services, and increases efficiency. These trends are also leading to more mainstream usage of virtual software developers and nonprofessional “citizen application developers.” Read more: How to Build a Business Case for Artificial Intelligence
2018
Gartner Top 10 Strategic Technology Trends for 2019
Gartner
AI will be in every industry and every job.
We asked 200 LinkedIn Top Voices about their Big Idea for 2019; one in four mentioned some application of AI, from parsing evidence in medical research to… helping surfers spot the best wave. Six of the 15 hot emerging jobs of the past year — which LinkedIn will unveil on Thursday — relate to AI, while AI skills are the fastest-growing on our platform, up 190% globally from 2015 to 2017. “While 2018 was the year of AI hype, it feels like we're at an inflection point where these technologies are being incorporated into more of the tools we use everyday,” says Sharon O’Dea, co-founder of communications consultancy Lithos Partners. “It's when technology trends start to become invisible that they really make a major impact.”
2018
50 Big Ideas for 2019: What to watch in the year ahead
LinkedIn
AI to Enhance EDGE Computing Power in IoT Systems
Over the past 12 to 18 months, the concept of EDGE computing to power the Internet of Things (IoT) applications, devices and systems surface has become a significant trend in the digital industry. The following factors have led to the a combination of EDGE Computing Power and IoT: · IT and technology providers, given their limitations, have had to decide how much processing power and computing resources to allocate from the cloud layer to the EDGE layer, particularly for applications that are highly Central Processing Unit (CPU) concentrated. · These providers aim to work alongside many sectors, industries, organisations to attain insightful analysis of specific, filtered data and nformation, via the use of machine learning and EDGE computing within IoT. · The collation of these significant amounts and types of intelligent data via smart sensors, actuators, servers, etc, for further analysis by EDGE and Cloud Analytics engines – instills confidence in decision makers to make the right moves. The aviation industry, for example, realises the power of the EDGE element and IoT together. By measuring and monitoring an aircraft’s performance, significant reductions in fuel and operational expenses and customer churn can be achieved. In 2017, SAS and Cisco announced the birth of their IoT Analytics platform, developed to enable analytics on devices at the edge of the network. Many industries see value in capturing and analysing data on the go, or in motion, rather than analyse data that was stored. Meanwhile, Huawei and Google have made efforts, in the last couple of years, to establish specific products to strengthen and enhance their IoT computing EDGE capabilities. In summary, the combination of AI/machine learning and EDGE within IoT systems allows IT and technology providers to: · Increase the running efficiency of their IoT operations via the gathering of intelligence from local data, particularly in locations where cloud connectivity is inconsistent. · As highlighted earlier, deliver real-time, fast predictions for critical IoT applications through machine learning processes that gather and process this data from devices and sensors. · Increase security of all types of sensor collected data via EDGE, with all privacy, security and compliance risks of these data fully eliminated. Juniper forecasts that the total number of connected IoT sensors and devices will exceed 50 billion by 2022, up from an estimated 21 billion in 2018. This growth, equivalent to 140% over the next 4 years, will be driven by EDGE computing services; increasing both deployment scalability and security. Incorporating powerful AI at the EDGE will enable faster processing, and analysis of IoT applications, and deliver improved data filtering, automation and workload distribution. We expect cloud corporates to potentially lead this space strongly, given their experience and background in AI. Related Research: The Internet of Things: Consumer, Industrial & Public Services 2018-2023
2019
Top Tech trends 2019
Juniper Research
AI That Can Argue and Instruct - New algorithms will enable personal devices to learn any topic well enough to debate it
Today’s digital assistants can sometimes fool you into believing they are human, but vastly more capable digital helpers are on their way. Behind the scenes, Siri, Alexa and their ilk use sophisticated speech-recognition software to figure out what you are requesting and how to provide it, and they generate natural-sounding speech to deliver scripted answers matched to your questions. Such systems must first be “trained”—exposed to many, many examples of the kinds of requests humans are likely to make—and the appropriate responses must be written by humans and organized into highly structured data formats.
2018
Top 10 Emerging Technologies of 2018
Scientific American