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Featured resources

About AI@Socitm

Explore the latest AI research, insights, and guidance. 

Whether you’re a leader, manager, practitioner, or enthusiast, this resource will keep you current in a rapidly-changing technological landscape.

It’s a place to learn, collaborate, and stay informed about breakthroughs. Keep the culture of continuous learning alive!

A structured pathway for individuals seeking to enhance their AI skills and competences.

Whether you’re a beginner or an experienced professional, our training courses, webinars, and real-world examples cover topics like machine learning, neural networks, and other AI concepts.

Our goal is to help you gain practical skills and a deeper understanding of how AI can be applied in public services.

Glossary

Artificial Intelligence (AI)

Artificial Intelligence (AI) is a transformative field of computer science that seeks to create intelligent systems capable of performing tasks that typically require human intelligence, machines that can independently perform tasks, learn from experience, and adapt. It encompasses technologies like machine learning, natural language processing, and robotic process automation.

Below is a list of different types of AI along with brief examples of how they are used, each type of AI has been designed to address specific challenges and applications ranging from dealing with repetitive specialized tasks, to the ability to understand natural language and natural language generation.

Autonomous Systems

Autonomous Systems refer to AI-driven systems capable of performing tasks or making decisions without human intervention.

Examples: Self-driving cars and unmanned planes & drones.

Computer Vision

Computer Vision is about teaching machines to interpret and understand visual information from images or videos.

Examples: Object recognition, facial recognition, autonomous vehicles, and medical imaging.

Deep Learning

Deep Learning is a specialized branch of Machine Learning that involves neural networks with multiple layers (deep neural networks).

Examples: Image and speech recognition, natural language processing, and playing strategic games.

Expert Systems

Expert Systems are AI systems designed to mimic the decision-making abilities of human experts in specific domains. They use knowledge representations and rule-based reasoning to provide expert-level advice and solutions.

Examples: Knowledge representations and rule-based reasoning to provide expert-level advice and solutions such as automated diagnosis

Machine Learning (ML)

Machine Learning uses algorithms that enable computers to learn from data and improve their performance on a specific task without being explicitly programmed. It encompasses several types of learning, such as supervised learning, unsupervised learning, and reinforcement learning.

Examples: Learning and identifying plants, recognition of handwriting to convert it to text.

Narrow AI

Narrow AI refers to AI systems designed to perform specific tasks or solve problems with high competence but limited scope. These systems excel at a narrow set of functions and lack general intelligence.

Examples: Virtual assistants like Siri and Alexa, image recognition systems, and recommendation algorithms used in online shopping.

Natural Language Processing (NLP)

NLP enables computers to understand, interpret, and generate human language. It plays a crucial role in applications like language translation, sentiment analysis, text summarization, and chatbots.

Examples: ChatGPT, Microsoft CoPilot and Chatbots

Reinforcement Learning

Reinforcement Learning involves training AI agents to make decisions by interacting with an environment. The agent learns through a system of rewards and punishments, aiming to maximize cumulative rewards over time.

Examples: Teaching cars to drive around a predetermined track, Non player characters in computer games.

Robotic Process Automation (RPA)

RPA is a technology that uses software robots or “bots” to automate repetitive, rule-based tasks and processes in business operations. These bots are not physical robots; instead, they are software applications that mimic human interactions with computer systems.

Examples: Processing large volumes of invoices following a set of rules