- Jul 10, 2020 Mozilla/5.0 (iPhone; CPU iPhone OS 1341 like Mac OS X) AppleWebKit/605.1.15Z (KHTML, like Gecko) Version/13.1 Mobile/15E148 Safari/604.1 (Applebot/0.1) Customizing robot.txt rules Applebot respects standard robots.txt directives that are targeted at Applebot.
- RPA is a software robot that mimics human actions, whereas AI is the simulation of human intelligence by machines. Many people often asked about the difference between Robotic Process Automation (RPA) and Artificial Intelligence (AI). Some even confused the two to be the same. To make matters worse, many vendors are now brandying about terms like Intelligent Automation (IA) or Intelligence.
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Non-intrusive, and a no-code low code approach. Our RPA uses the same scripts, to automate any environment, meaning that automation can occur on Windows, Mac and Linux using the same automation development. T-Plan Robot is the only RPA tool on the market which supports Mac and Linux and Windows in the same application. Learn more about T-Plan.
Did you know that…
- You could reduce process costs by up to 80% for certain processes through robotics?
- According to some case studies, 47% of jobs in the U.S. economy could be replaced by robots?
- Removing the mundane tasks in your employees work actually makes them happier?
- Implementing an effective robot in your organization could take less than 3 months?
- Robotic process automation is not only a tool to reduce costs?
Robots process automation (RPA) and artificial intelligence (AI) have transitioned from Hollywood to Wall street thanks to increase availability of data and reduced cost of computing power. Furthermore, the opportunity has become abundantly clear due to an exponential growth of siloed IT systems and fragmented processes.
Terms like robotics (RPA), machine learning (ML), deep learning (DL) and artificial intelligence (AI) are often used synonymously, even though they are worlds apart. What’s the difference between these seemingly interconnected concepts? It’s important to see the field as having two very distinct capabilities, namely robotic process automation (RPA) and cognitive computing.
Robotic Process Automation (RPA) or just robotics for short involves automating repetitive tasks normally conducted by humans. This is done by encoding a small program or computer to conduct a specific task set if a certain condition is fulfilled such as e.g. receiving a pre-filled order form and then automatically placing the order in the system.
Cognitive computing is a much more advanced form of robotics whereby a computer can recognize patterns in data. This allows it to self-sufficiently learn how to respond to different types of problems or situations understanding speech, text or how to improve predictive models. This is called machine learning i.e. which 'gives computers the ability to learn without being explicitly programmed' (Arthur Samuel, 1959). Deep learning is a form of machine learning which uses artificial neural networks which mimic the human brain to find patterns in data presented. Deep learning allows for a more accurate prediction and a higher chance of achieving the ‘expected’ result than traditional models. A machine which is able to perform tasks which were traditionally only able to be performed by humans (i.e. speech recognition, complex decision making, visual perception etc.) is considered to exhibit artificial intelligence.
Robotics or robotic process automation replaces mundane tasks with simple robots. Artificial intelligence replaces more complex and detail oriented tasks & analysis with intelligent, self-learning instances of AI
Between robotics and cognitive computing, there is an even wider spectrum ranging from simplistic desktop automation through to virtual assistants. Below is a comprehensive overview provided to me by Casper Stevenaar (Junior consultant at Accenture) which highlights the use cases, benefits and vendors of the different maturity levels of the Robotics and AI spectrum:
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‘Robots’ are already integrating themselves into all levels of the organization. If the concept of having a computer learn through doing still sounds a bit futuristic to you, just look at what companies such as RBS and Tesla are already doing. RBS has implemented an AI which understands and helps resolve client issues and questions and even shows empathy; Tesla cars have learned to drive.
Similarly, companies such as Blue Prism, IPSoft and Accenture already provide RPA and AI solutions to the market. Blue Prism has devised a tool set that “follows rule-based business processes and interacts with the systems in the same way that existing users currently do.” The tool set is compatible with all programs and platforms, meaning that no new investments in system/architecture are required. Accenture, for example, has created Collete, a mortgage advisor which can give personalized advice to customers within the comfort of their own home 24/7.
The number of companies already investing in technologies such as RPA and AI is growing fast. Companies who fail to recognize the importance of adopting this new technology will fail to remain competitive in a dynamic environment. What can you be doing to prepare your organization for the rise of robotics and cognitive computing? Each company should be asking themselves:
- Is RPA & AI a discussion point at board level?
- What are our strategic objectives for 2017 and do we know how RPA & AI may impact these?
- Have we started any initiatives and do we have relevant expertise in-house?
- Do we have a roadmap for the implementation of RPA & AI initiatives?
Ai Vs Robot Mac Os Update
Robotics process automation and artificial intelligence are already being embedded into organizations large and small at rapid pace. These organizations enjoy benefits such as reduced operating costs and increased service availability. In order to not fall behind, each financial institution should already be thinking about this sooner rather than later.
Look forward to me blogging more about RPA & AI in the coming months. In the upcoming post, I will talk a bit more about the strategic objectives of financial institutions and how RPA & AI may help you achieve a majority of these. If you have any questions about the above, don’t hesitate to contact me. Furthermore, note that this post in no way reflects the views and opinions of my employer or colleagues.