If you have considered adopting robotic process automation (RPA) and artificial intelligence (AI) solutions into your workflow, you have probably encountered a wide range of similar-sounding terms. If you are just beginning your integration, these terms can be a barrier because they are often technical or specific to a single provider.
We’ve pulled together a list of a few of these terms to help out. We feel like the list below is some of the most important and cutting edge technologies that you can leverage for your digital transformation.
RPA Terms
One of the essential steps to using RPA bots is understanding the differences between the different forms of RPA platforms across the industry. Most of the newest offerings are a type of smart RPA. Meaning they combine RPA with AI models, which results in a more effective bot. We’ve provided three examples of the different types of RPA solutions you’re likely to encounter.
• Robotic Process Automation:
RPA is an application of technology, governed by business logic and structured inputs, to automate business processes. Using RPA tools, a company can configure software or a “robot” to capture and interpret applications for processing a transaction, manipulating data, triggering responses, and communicating with other digital systems. RPA bot without AI components are simpler, but they can automate highly repetitive and rules-driven tasks.
• Intelligent Automation (IA):
An advanced form of RPA. Intelligent Automation combines RPA with other technologies such as structured data interaction (SDI), machine learning (ML), natural language processing (NLP), natural language generation (NLG), AI-Decision systems, Chatbots, and more. This helps businesses to automate more processes efficiently and effectively than standard RPA bots. An intelligent Automation bot can efficiently process unstructured data, better exception handling, make decisions, work without human input, and learn continuously.
• Hyperautomation:
The top strategic trend of 2020 from Gartner, Hyperautomation combines RPA, artificial intelligence, machine learning (ML), advanced analytics, and process mining to automate processes in ways that are significantly more impactful than traditional automation capabilities. It is an end to end automation solution that helps with everything from discovering opportunities for automating processes to easily integrating machine learning models to giving managers top view understanding of how well the bots are performing. You can learn more about Hyperautomation on UiPath’s Website as they are at the forefront of its development.
AI Terms
Artificial intelligence is rapidly developing and often described in hard to access technical ways. AI solutions are a powerful tool for any business process, so understanding the differences and benefits they can bring is vital to their usage.
• Machine Learning (ML):
Machine learning is computer algorithms that learn and improve at a specific task over time. Machine learning is a field experiencing rapid development because of its accessibility and positive use cases. ML comes in the form of models. These models learn how to provide the desired output through processing data. ML is experiencing a boom of adoption because the greater availability of higher processing power for fewer resources means that models can process data faster.
• Deep Learning:
Deep learning is a cutting edge type of artificial intelligence. It’s very complicated, but the basic understanding of it is that it’s trying to emulate the human brain through neural networks. Deep learning is a type of artificial intelligence that is used by the most advanced researchers and companies. Deep learning is likely not going to see widespread adoption for some time, but it’s worth paying attention to the newest developments.
• Natural Language Processing (NLP):
NLP is the process of computers understanding human language. Natural language processing has broad applications, but one of the most common uses is text and speech processing. With NLP, extracting text from emails, pdfs, and even handwritten text is possible. A common type of natural language processing is optical character recognition (OCR).
• Natural-Language Generation (NGL):
NGL is the process of software generating language. There have been many recent developments in NGL, and one of the most exciting is GPT-3. GPT-3 is capable of writing whole articles based on prompts given to it by humans. You can read an article that it wrote for the Guardian by following this link.
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