The emergence of ChatGPT in recent months has prompted an unprecedented explosion of public hype and interest in Artificial Intelligence and its potential future uses.
Following industry luminaries such as Bill Gates describing AI as the most important technological advance in decades, there has been a torrent of predictions on how it will change the world of work.
Here at Altilia we have been building an AI-based platform, Altilia Intelligent Automation, that is at the forefront of a new revolution based around Intelligent Document Processing (IDP).
It is clear, however, that industry leaders anxious to understand this new phenomenon, are overwhelmed by the language, acronyms and blizzard of nascent technologies which leave them baffled and unsure on how to get started.
Our aim over a series of blogs is to unpack the lexicon of AI and explain what it all means, a useful, insightful and simplified guide for organizations interested in how AI will affect them.
What is Artificial Intelligence?
The term artificial intelligence (AI) is used loosely to refer to applications that perform complex tasks that previously required human intervention, such as communicating with customers online or playing chess.
The term is often used interchangeably with the terms machine learning (ML) and deep learning, although they (as we will discover) have different meanings.
Many companies are investing significantly in data science teams to take full advantage of AI, combining statistics, computer science and business knowledge to extract value from various data sources and enable problem-solving. Algorithms seek to create expert systems which make predictions or classifications based on input data.
Advanced functions can include the ability to see, understand and translate spoken and written language, analyze data, make recommendations and classify both structured and unstructured data.
Computers and machines are developed with the ability to reason, learn and act in a way that would normally require human intelligence, often at a scale that exceeds or speeds up what humans can deal with.
Benefits of AI:
- Automation. AI can automate workflows and processes or work independently and autonomously from a human team.
- Reduce human error. AI can eliminate manual errors in data processing, analytics, assembly in manufacturing, and other tasks through automation and algorithms that follow the same processes every single time.
- Eliminate repetitive tasks. AI can be used to perform repetitive tasks, freeing human capital to work on higher impact problems.
- Fast and accurate. AI can process more information more quickly than a human, finding patterns and discovering relationships in data that a human may miss.
- Accelerated research and development. The ability to analyze vast amounts of data quickly can lead to accelerated breakthroughs in research and development.
Altilia are world experts in Intelligent Document Processing (IDP), so let’s have a look at how it builds on AI capabilities and developments to enhance organizational efficiency and accuracy.
What is Intelligent Document Processing?
At its most simplistic level, Intelligent Document Processing (IDP) converts unstructured and semi-structured data into structured usable information, thus enabling layers of automation to document-centric business processes.
As an example, many mortgage forms may be filled in with (unstructured) hand-written answers by an applicant, which would need human intervention to input that information into a financial services company’s systems.
IDP uses AI (and other technologies) to extract that information in a usable form, thus reducing time and manual labor.
Which AI fields are relevant for IDP?
A human reading and understanding a document needs to:
- Have visual perception to recognize images, symbols and writing
- Have a comprehensive understanding of the document’s language
- Be able to understand new information and learn concepts
- Be able to memorize concepts and the relations between them.
AI, therefore, needs to emulate these abilities to be capable of reading like a human – and for IDP, these are the most relevant application fields:
- Computer Vision is the AI field that emulates human visual perception
- Natural Language Processing (NLP) focuses on developing algorithms for general understanding of a language
- Machine Learning (ML) is focused on training a machine to learn and conceptualise information as models
- Knowledge Representation is focused on representing information in a way that is functional, not just to memorize the content, but relations between them.
We will continue this series explaining the lexicon of AI in the coming weeks. For more information on how Altilia can support your business, schedule a demo here .