Trends Identified
Machine Learning – The Algorithms to Make Everything More Intelligent
The success of Google AlphaGo in 2016 marks the rise of machine learning. It is based on the idea that machines can learn for themselves if they get access to large volumes of data and comprises deep learning, neural networks and natural-language processing algorithms. The technology has very strong connections to big data and real-time analytics but needs high quality data and a clear process to be trained. Machine learning and IT vendors will in build intelligent capabilities into business intelligence systems, analytics and into many devices, robots and machines. This is rising a number of ethical questions such as the future of our work, how machine learning will affect our behavior, how can we guard us against mistakes and unintended consequences, and how do we stay in control. Extracting the qualitative data needed for machine learning training is a challenge, as well as finding experts. Machine learning can be used to solve a tremendous variety of problems and automate tasks that had to be handled by humans before, such as translations, face, speech and pattern recognition, text analytics, analyzing large data sets and more. The technology promises to save costs and improve the quality of work by automating 80% of the roughly 50% work activities that are suitable for automation. Most of todays’ knowledge work contains the following activities: pattern recognition (99%), generating and understanding natural language (75%), optimizing and planning (30%). Furthermore, machine learning may generate faster insights and speed up decision making based on large data sets and accelerate innovation by faster prototyping. While machine learning will affect all industries, expectations are the highest for media, telecom, technology, consumer and fi nancial services. The fi rst wave of machine learning will focus on automating repetitive tasks and analyzing large data sets such as invoicing, text analysis, image recognition, and fraud detection but will be used for autonomous vehicles, virtual assistants, product intelligence and advanced robotics as well.
2018
Trend Report 2018 - Emerging Technology Trends
SAP
Machine Learning
AI and machine learning (ML) were born in the ’80s, but the hardware was never fast enough to deliver the expected promise. Now, ML libraries are readily available, and the cloud provides all the computing you need. Thanks to AI and ML, marketers can improve revenue growth, support reps can deliver better answers, service professionals can deliver insights and customers can connect all their data.
2018
2019 Tech Forecast: 11 Experts Predict The Next Wave Of Breakout Technologies
Forbes
Machine learning
“Machine learning has the potential to be one of the biggest disruptors over the next decade,” says DeLaney.
2017
5 big disruptive trends investors should watch
Morgan Stanley
Machine intelligence - Technology mimics human cognition to create value
Artificial intelligence´s rapid evolution has given rise to myriad distinct— yet often misunderstood—AI capabilities such as machine learning, deep learning, cognitive analytics, robotics process automation (RPA), and bots, among others. Collectively, these and other tools constitute machine intelligence: algorithmic capabilities that can augment employee performance, automate increasingly complex workloads, and develop “cognitive agents” that simulate both human thinking and engagement. Machine intelligence represents the next chapter in the advanced analytics journey.
2017
Tech trends 2017 - the kinetic enterprise
Deloitte
Machine / robotics Automating common tasks
Machines and robotics are endowed with AI (programmed algorithms) to ful l set tasks and goals. These generally fall into two key categories: ‘speci c task-based AI’ (e.g. a web search engine or an autonomous vehicle) and ‘general AI’ that aims to replicate aspects of human intelligence (e.g. IBM’s Watson or humanoid robots like Honda’s ASIMO).
2017
Surfing the digital tsunami
Australia, Commonwealth Scientific and Industrial Research Organisation (CSIRO)
Loyalty will beat novelty.
Gen Z kids saw their parents lose homes and pensions to the financial crisis. As a result their perspective on work and money most closely resembles that of their great grandparents, who grew up in the Great Depression and prized security above fulfillment. “Millennials want a dream job,” says Pranam Lipinski, CEO of Door of Clubs, who surveyed thousands of Gen Z students about their values and preferences. “Generation Z wants success and financial stability over that dream job.” That means they’re far more likely to remain loyal to an employer that provides a stable environment and benefits — in Door of Clubs’ survey, 61% said they’d stay with an employer 10 years or longer. But watch out, warns Jill Schlesinger: It’s changing jobs that gets you significant raises. Too much loyalty will hurt your lifetime earning power.
2018
50 Big Ideas for 2019: What to watch in the year ahead
LinkedIn
Low-cost space travel
Example of Organizationsactive in the area: Space X/Elon Musk (US), Blue Origin (US), Virgin Galactic (UK), Rocket Lab (US), Axiom Space (US), SpaceIL (Israel), Firefly Aerospace (US).
2018
Table of disruptive technologies
Imperial College London
Low-cost robots may level the playing field
Sensors, artificial intelligence and robots will reshape heavy manufacturing and are likely to have a leveling impact across both developed and developing economies. While developing countries may lose their low-cost labour advantage as advanced economies deploy an affordable AI-enabled robotic workforce, both economies will be able to deploy AI and increase the productivity of their low-skilled workers.
2013
Metascan 3 emerging technologies
Canada, Policy Horizons Canada
Lost cities
You don’t need to look very hard in a place like Miami to see how cities are changing in the 21st Century – rising sea levels are gradually making some of them disappear. Fuelled by climate change, not only are floods becoming more common in the streets, but the changing weather patterns have also influenced building design. Aside from more seawalls, the city is requiring all new buildings be built with their first floor built higher. But that’s all a sticking plaster – if current trends continue, we may have to come to terms with losing whole swathes of cities, islands and low-lying regions such as Bangladesh. The economic impact to regions will be profound, and climate refugees could become the norm.
2017
10 grand challenges we’ll face by 2050
The BBC