Skip to content
The AI education hub: easy to follow resources explaining AI
Early talent & AI

The AI education hub: easy to follow resources explaining AI

This collection of multimedia resources demystifies AI through beginner-friendly videos, articles and podcasts. Gain a working understanding of core AI concepts like machine learning, neural networks and natural language processing.

Created for both tech and non-tech learners, these curated materials use clear explanations and real-world examples to make AI accessible. Learn how AI systems function, train on data and make decisions, as well as their current and future applications in daily life. It is an ideal starting point for anyone looking to get up to speed on the basics of AI and its transformative potential across industries.

What's AI?(Council of Europe)

This article provides perspective on defining artificial intelligence, arguing it is best understood through the specific technologies used rather than broad speculation.

History of Artificial Intelligence (Council of Europe)

This overview traces key milestones between 1940 and 2010 in the history of artificial intelligence. Early pioneers established foundations like neural networks and questions of machine intelligence.

Introduction to Generative AI (Google Cloud Tech)

This video provides an overview of GenAI, explaining what it is and how it works. It covers common applications of GenAI, different model types, and fundamentals for utilising this technology.

Introduction to large language models (Google Cloud Tech)

This video explores the intersection of large language models and GenAI, both of which fall under the umbrella of deep learning. It explains use cases for large language models, prompt tuning methods, and AI development tools.

Generative AI exists because of the transformer: This is how it works (The FT, September 2023)

This interactive article explains how generative AI works, using foundation models that learn from large amounts of data and generate outputs based on natural language prompts. It also explores the potential and challenges of generative AI and showcases some examples of generative AI applications, such as writing headlines, creating logos, composing music, and designing clothes.

What is Generative AI? (McKinsey and Co 2023)

This article examines what GenAI is, how it functions, its applications, and implications. GenAI uses machine learning algorithms trained on massive datasets to create novel content like text, images, and audio. While holding great promise to transform digital creation, GenAI also poses challenges to address.

The rise of generative AI and what it means for business (IBM)

The AI academy from IBM explores the history of artificial intelligence, generative AI and why it's important to business and how to put AI to work.

AI Campus - The learning platform for artificial intelligence

This platform offers free online courses, videos, and podcasts about AI and data literacy. It is funded by the German Federal Ministry of Education and Research and supported by academic and industry partners.

The road to AGI (Google DeepMind 2022)

In this podcast episode, Hannah Fry meets Google DeepMind co-founder Shane Legg, who coined the term "artificial general intelligence (AGI)," where they discuss how AGI could be achieved. It explores his perspectives on feasibility, timelines, and potential manifestations of AGI.

What Is Artificial General Intelligence, and How Does It Differ From Generative AI? (MUO 2023)

This article contrasts artificial general intelligence (AGI) with generative AI (GenAI). AGI refers to hypothetical AI matching human intellectual abilities. GenAI (or GAI) generates novel content from existing data. It explains distinctions in how they are developed and limitations of current AI versus theorised AGI.

Robots Learn, Chatbots Visualize: How 2024 Will Be A.I.’s ‘Leap Forward’ (The New York Times Jan 2024)

The article discusses the rapid advancement of AI in 2024, highlighting significant improvements in chatbots and generative AI. Key developments include AI-powered image generators producing videos, and the integration of chatbots with various media types for more human-like reasoning and complex problem-solving. Additionally, AI technology is expected to enhance the capabilities of robots in the physical world. The field's rapid progress is attributed to neural networks and the vast data they analyse, pointing towards a future where AI plays a more integral role in both digital and physical realms.

Level the playing field for your students