Quick Tip — Demystifying Generative AI, a Guide to Text and Image Generation
In this Quick Tip, we’ll tackle the challenge of understanding Artificial Intelligence and Generative AI terminology to help you better understand these terms in the context of their widespread use.
Let’s simplify and clarify the distinctions between these concepts and explore two popular Generative AI models for text and image generation.
🔹 Artificial Intelligence (AI) is a broad term encompassing a range of technologies that enable machines to simulate human intelligence. From simple rule-based systems and machine learning to complex deep-learning algorithms, various forms of AI powers everyday experiences like recommendation systems, self-driving cars, and voice assistants like Siri.
🔹 Generative AI is a specialised form of AI that generates new content such as text, images, music, or voices. Generative AI learns from training data to produce new content. For example, models trained to create visual content can generate AI-generated artwork.
🔹 Text Generation, represented by models like ChatGPT, Bard, and Meta, falls under the Large Language Models (LLMs) category within Generative AI. These models are trained on a wide array of text data, enabling them to generate human-like text in response to prompts. What is the “Large” in LLM? There is no set measurement. Large refers to the massive scale of data and parameters used to train the model.
🔹 Image Generation, illustrated by models like Midjourney, DALL-E 2 and Stable Diffusion, is another subset of Generative AI. These models employ diffusion techniques, starting with a random noise image and progressively refining it to match a text prompt. With these models, your creativity can take you anywhere, from imagining a cat astronaut skiing in the desert to other visually stunning concepts.
To summarise, AI encompasses a wide range of technologies simulating human intelligence. Generative AI focuses on creating original content; within it, Large Language Models and Image Generation are specialised subsets with specific applications.
Understanding AI, including Generative AI and Large Language Models, quips you to make strategic decisions, maintain competitiveness through innovation, and address essential considerations like data privacy and ethics.
Have you come across any cool applications of Generative AI recently? Share your experiences below! 💡👇
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