Trends Identified
Robot dexterity
Robots are teaching themselves to handle the physical world.For all the talk about machines taking jobs, industrial robots are still clumsy and inflexible. A robot can repeatedly pick up a component on an assembly line with amazing precision and without ever getting bored—but move the object half an inch, or replace it with something slightly different, and the machine will fumble ineptly or paw at thin air. But while a robot can’t yet be programmed to figure out how to grasp any object just by looking at it, as people do, it can now learn to manipulate the object on its own through virtual trial and error. One such project is Dactyl, a robot that taught itself to flip a toy building block in its fingers. Dactyl, which comes from the San Francisco nonprofit OpenAI, consists of an off-the-shelf robot hand surrounded by an array of lights and cameras. Using what’s known as reinforcement learning, neural-network software learns how to grasp and turn the block within a simulated environment before the hand tries it out for real. The software experiments, randomly at first, strengthening connections within the network over time as it gets closer to its goal. It usually isn’t possible to transfer that type of virtual practice to the real world, because things like friction or the varied properties of different materials are so difficult to simulate. The OpenAI team got around this by adding randomness to the virtual training, giving the robot a proxy for the messiness of reality. We’ll need further breakthroughs for robots to master the advanced dexterity needed in a real warehouse or factory. But if researchers can reliably employ this kind of learning, robots might eventually assemble our gadgets, load our dishwashers, and even help Grandma out of bed. —Will Knight
2019
10 Breakthrough Technologies 2019 - How we’ll invent the future, by Bill Gates
MIT Technology Review
Robotic care companions
Example of Organizationsactive in the area: Softbank (Japan), AIST (Japan), Blue Frog Robotics (France), Care-o-bot (Germany), Riken/Sumitomo Riko (Japan), Mayfield Robotics (US).
2018
Table of disruptive technologies
Imperial College London
Robotic Process Automation – Rule-Based Bots
Robotic Process Automation (RPA) refers to rule-based and easily programmed software, that promises to eliminate repetitive, easily automated tasks. RPAs are fully programmed, cannot learn and have to be updated when IT systems change. RPA is seen as a next step towards automation where machine learning is not needed. It can be tied together with machine learning to automate more complex tasks to create intelligent enterprises. Most RPA today uses text analytics, image processing, text search, or optical character recognition. Analytics will become critical as RPA will soon be developed towards more smarter versions. While we are heading towards an automated world, the process seems to take longer than anticipated and is more complex than anticipated, so RPAs could be a fast forward solution for those processes that yet do not need sophisticated algorithms. For now, a central control of bots is not fully established and changes of IT systems could lead to expensive updates. Besides that, RPA can boost productivity with minimal process change, it offers easy-to-calculate ROIs and it is an in-route to more complex automation with machine learning.
2018
Trend Report 2018 - Emerging Technology Trends
SAP
Robotic Process Automation Ramps Up
RPA has, for many years, been used to automate very simple, repetitive business tasks. However, owing to advances in machine learning algorithm modelling, RPA software systems can be trained to automate a wider set of tasks than ever before. This effectively enables a workforce of software agents to manage dynamic data inputs. Previous processes to automate a task involved creating APIs for third parties that can enable the creation of physical actions to execute. In contrast, RPA systems leverage the application’s Graphics User Interface to observe and then mimic the process through robotics. This level of automation can deliver a new degree of efficiency as tasks that were typically time consuming and repetitive, which could thus be automated. Introducing it will also reduce costs and minimise operational errors in business practices. However, its biggest strength lies in its ability to leverage existing systems, rather than requiring a complete overhaul of existing infrastructure. Juniper expects that the public sector will find the greatest benefits from RPA – providing time and cost saving efficiencies that will enable public bodies to offer citizen-centric services. With industries such as manufacturing and financial services investing in RPA solutions, key development focus will be towards more effective machine learning algorithms to increase automation levels. This is in addition to machine learning as a mechanism for defending against new security vulnerabilities introduced by RPA as a result of agents’ ability to access and process across multiple systems. SAP announced their intention to push AI and cloud-based RPA services in late 2018; joining incumbent players including Automation Anywhere, OpenSpan and Blue Prism. Juniper anticipates that in 2019, we will see a number of service providers continuing to invest in AI-based RPA services; releasing solutions that will further drive down cost of adoption. . Related Research: Banking Automation & Roboadvisors: Cost Analyses, Impacts & Opportunities 2018-2022
2019
Top Tech trends 2019
Juniper Research
Robotics
Robotics, under which we include both advanced robotics increasingly able to augment humans in the workplace and traditional robotics, in which machines reproduce repetitive human actions, as well as autonomous and near-autonomous vehicles
2019
Tech for good
McKinsey
Robotics
Physical systems of automation, including driverless cars
2016
Disruptive technologies barometer
KPMG
Robotics
Robotics is the branch of technology that deals with the design, construction, opera on and application
of robots and related computer and control systems. Robots help with or take the place of humans
in dangerous environments or manufacturing processes, and/or resemble humans in appearance, behaviour or cognition. Increasingly, robots are designed to act in roles complementary to humans.
Today, experimental robots can inventory stock, move loads, pick berries, do housework, perform elder care, sense remotely and create a virtual presence. As their AI improves, they will get smarter and more capable. Robot hardware is improving quickly; the challenge is the so ware – the intelligence behind the machine that allows it to function in a specific manner. Task-specific robots could do tasks as diverse as surgery, cooking and driving. Businesses will continue to be early adopters of robot technology, with home use following as prices decline and features become more competitive.
2013
Metascan 3 emerging technologies
Canada, Policy Horizons Canada
Robotics
Robots are machines with enhanced sensing, control, and intelligence used to automate, augment, or assist human activities. The robot market, which has grown for industrial applications, is poised for growth in a broad range of services applications. These applications are transforming manufacturing and non-manufacturing operations with new capabilities that address the challenges of working in changing, uncertain, and uncontrolled environments, such as alongside humans without being a danger to them.
2017
The Essential Eight - Your guide to the emerging technologies revolutionizing business now
PWC
Robots
Electro-mechanical machines or virtual agents that automate, augment or assist human activities, autonomously or according to set instructions — often a computer program.
2016
Tech breaktroughs megatrend
PWC