Key Points
- Defines foundational AI concepts like machine learning, deep learning, and neural networks.
- Explains large language models and how they generate human‑like text.
- Covers generative AI methods such as diffusion, GANs, and text‑to‑image creation.
- Describes multimodal AI that handles text, images, audio, and video together.
- Details autonomous agents and their role in self‑driving and robotics.
- Addresses ethical issues including bias, hallucination, and alignment.
- Highlights AI safety concerns and the importance of guardrails.
- Provides context for AI‑powered products like chatbots and search assistants.
Overview
This glossary assembles a wide range of artificial intelligence (AI) terms that are increasingly relevant across industries. It serves as a reference for readers seeking to grasp the language used in AI research, product development, and public discourse.
Core Concepts
Fundamental ideas such as machine learning, deep learning, neural networks, and large language models are explained, highlighting how computers learn patterns from data and generate human‑like responses. Definitions also cover common processes like inference, training data, and model parameters.
Generative Technologies
The guide details generative AI techniques, including text‑to‑image generation, diffusion models, generative adversarial networks, and video synthesis. It clarifies how these systems create new content by learning from vast datasets.
Multimodal and Autonomous Systems
Terms related to multimodal AI, which processes text, images, audio, and video simultaneously, are included. Autonomous agents and self‑driving technologies are described, emphasizing their ability to operate with minimal human supervision.
Ethics, Safety, and Governance
Ethical and safety considerations are addressed through definitions of AI ethics, alignment, bias, hallucination, and guardrails. The glossary also touches on broader concerns such as AI safety, existential risk, and responsible deployment.
Practical Applications
Real‑world implementations are illustrated with references to AI‑powered chatbots, search engines, and productivity assistants. The terms help readers understand how AI is embedded in everyday tools and services.
Conclusion
By providing concise, accessible definitions, this glossary equips audiences with the vocabulary needed to navigate the rapidly evolving AI landscape and engage in informed discussions about its impact.
Source: cnet.com