An Introduction to AI

When people hear the term 'Artificial Intelligence', they may imagine an autonomous, automated or conscious computer which feels, thinks and understands the world like a human.

This not the case. Instead, AI is a type of software which uses multiple sets of instructions, also known as 'Algorithms', to access, process and analyse large amounts of data to perform a task.

This process commonly referred to as 'Machine Learning', saves the data and information which is gathered from completing any tasks, to learn and improve.

Instead of being rigidly programmed with every possible answer, a machine learning system is 'Trained', to analyse and save large amounts of data to identify patterns.

For example, if we want an AI system to recognise images of a dog, it will be 'Trained', by being shown a large number of labelled images, to determine and save the patterns which are associated with dogs.

By analysing the data, the machine learning model can learn patterns associated with dogs so that when it is presented with a new image, it can then estimate whether it contains a dog.

This process is very different from human understanding as the AI is not necessarily thinking in the same way as a person. Instead, it is processing information according to mathematical models, patterns and probabilities.

There are foundational methods and software systems that allow AI to learn from data, recognise patterns and solve complex problems.

These core technologies allow computers and machine learning models to perform tasks that normally need human thinking, powering everything from simple search tools to advanced smart assistants.

Machine Learning

Algorithms that train computers to learn from data and improve automatically.

Deep Learning

A subset of Machine Learning, it uses multi layered artificial neural networks modelled after the human brain.

Natural Language Processing

Technology that allows machines to read, understand, and generate human language.

Computer Vision

Software that enables computers to identify and process visual information from images or videos.

The applications for AI in the practical, real world is increasingly helping to solve problems, automates tasks and identify efficiencies across various industries and sectors.

Continuing to grow and increase in use, AI is changing how we live, work and manage businesses.

Generative AI

Involves the use of tools that can create new content, instantly writing code, drafting essays, generating images, audio and video, even composing music, based on patterns and analysis it has saved from it's data sources.

Voice Assistants

AI and machine learning models are used in voice controlled or activated technology, to recognise spoken language and interpret requests.

Search Engines

AI can assist in helping search engines to understand queries, identify and present relevant information to users and generally improve search results.

Navigation

AI is used within navigation systems that can analyse traffic information and related data, to estimate journey times and suggest alternative routes.

Cyber Security

When it comes to the security and IT systems and infrastructure, AI is used to identify unusual activity, detect potential threats and analyse large volumes of security data.

Healthcare & Science

AI is currently being used to support medical research and analyse complex, scientific data, replacing manual, repetitive tasks with automated pattern recognition. This allows researchers and doctors to solve complex problems in days instead of decades, although its use in certain scenarios still requires careful testing, validation and human oversight.

Data Analysis

Algorithms are used to analyse data that will provide market insights and predict financial trends, while also providing information that helps with the management and efficiencies of general business operations, such as logistics and supply chains.

Autonomous Systems & Automation

A range of technologies have been developed across multiple industries to provide autonomous and automated products, services or support for self-driving cars, warehouse robotics and smart drones.

Despite the potential of AI and machine learning, it also raises issues and concerns in various areas of how we work and live.

Accuracy

AI systems can produce incorrect information while presenting it in a convincing way, so as a user, you should not automatically assume that an answer to a question, which is generated by AI, or a machine learning tool is correct.

Bias

AI systems can reflect and build on biases which are present in their training data, logic or design, creating unfair or inaccurate outcomes.

Privacy

AI systems process significant quantities of information and data from the general internet and private or third-party sources, creating questions about how data is collected, stored and used.

Employment

While AI could create new opportunities, areas of AI such as automation, may change the nature or even transform the types of work which are available and their roles in the workplace.

Security

Being used to improve cyber security, AI can also be misused to create more convincing scams, generate malicious content or automate cyber attacks.

Misinformation

Generative AI can create realistic text, images, audio and video, making it increasingly difficult for users to determine whether any digital content is authentic.