Trends Identified
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 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 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 and AI
2017
2017 technology trends - Increasing stratification and changing competitive dynamics
PWC
Machine Learning Coming to Verify Your Identity
Machine learning will come into its own as a technology underpinning digital identity. Identity verification still largely relies on manual processes, bringing documents into the bank. Machine learning maturing as a technology which can carry out suitable verification checks.
2018
Top Tech trends 2018
Juniper Research
Machine Vision
From detecting corruption to diagnosing cancer, there are a multitude of uses for this AI technology.
2018
Most contagious report 2018
Contagious
Machine-readable world
In recent years, governments have started to discover the power of machine readability, with energy devoted to building open government data programmes that help to fuel innovations both within government and in the broader economy. They are now setting their aims even higher by developing innovative new projects that have the potential to completely reconceive one of the most foundational roles of government – creating laws and other rules that impact the daily lives of citizens and businesses. Governments are also seeking to digitise human characteristics, senses and surroundings to deliver innovative services and interventions. This growing wealth of machine-readable content serves as fuel for a new generation of innovations that use emerging technologies such as artificial intelligence and blockchain. While these advances show tremendous potential, they can also pose major risks and raise significant ethical questions. Governments should seek to understand and experiment with these technologies, but should do so in an informed and ethical way.
2019
EMBRACING INNOVATION IN GOVERNMENT-Global Trends 2019
OECD
Machine-to-machine interaction technologies
The development of machine-to-machine interaction technologies (machine-to-machine, M2M) will lead to the emergence of more flexible opportunities for collaboration and distributed control of infrastructure objects and will become an important stage on the route to implementing the global concept of the “Internet of Things”.
2016
Russia 2030: science and technology foresight
Russia, Ministry of Education and Science of the Russian Federation
Mainstreamed IoT
While IoT is not a new concept, it will move from pre-adoption to a mainstream solution that retail, manufacturing, health care and other industries will integrate as an everyday business operation. It will change the way consumers and businesses get real-time data, engage with their users and interact with AI and machine learning.
2018
2019 Tech Forecast: 11 Experts Predict The Next Wave Of Breakout Technologies
Forbes