Generative Artificial Intelligence (AI) has exploded in popularity, but with its growth comes a new vocabulary. This article unpacks key terms to boost your understanding of this complex technology.
Reasoning and Planning: Forget chess-playing machines – AI is now tackling real-world challenges. By analyzing past data, AI can solve problems and even plan out steps to achieve goals.
Training and Inference: Creating an AI is a two-step process. First, training feeds the AI data to learn tasks or make predictions. Then, inference uses this learned knowledge to make real-world decisions, like appraising a house.
Small vs. Large Language Models: Think of large language models (LLMs) as information powerhouses. Small language models (SLMs) are their compact cousins, using less data and working offline on devices like phones.
Grounding AI in Reality: Generative AI can be creative, but it can also struggle with truth. Grounding connects the AI to real-world data to improve accuracy and provide relevant responses.
Retrieval Augmented Generation (RAG): Need an AI up-to-date? RAG provides a shortcut. It injects fresh information from a source like a product catalog to enhance the AI’s responses.
Orchestration : Imagine an AI juggling multiple tasks. Orchestration ensures the AI tackles these tasks in the right order for the best outcome. It can even use RAG to find relevant online information.
AI Memory : While AI doesn’t have true memory, it can simulate it. Orchestration allows the AI to “remember” past interactions within a conversation or use RAG for the latest info. Developers are exploring ways to expand this short-term memory for more complex tasks.
Transformer Models and Diffusion Models: Transformer models are the rockstars of language AI, understanding context and generating realistic text. Diffusion models, used for image creation, take a more methodical approach, gradually building an image from scratch.
Frontier Models : These are the cutting-edge AI systems with a vast range of capabilities. So advanced, they can sometimes surprise us with their abilities. Tech companies are working together to ensure their safe and responsible development.
GPUs – The Power Behind the AI Throne: GPUs, originally designed for smooth video game graphics, are the workhorses of AI. These powerful chips are built for parallel processing, making them ideal for the massive calculations needed for AI tasks.
Understanding these terms will equip you to better grasp the capabilities and future of AI.