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AI's Evolving Language: Your Essential Glossary
8 Sep
Summary
- AI vocabulary expands rapidly with new terms like LLMs and RLHF.
- The glossary provides plain-English definitions for AI concepts.
- It is a living document, regularly updated as the field evolves.
The rapid advancement of Artificial Intelligence has led to a proliferation of specialized terminology, including LLMs and RLHF, making it challenging to keep pace. This comprehensive glossary aims to provide clear, accessible definitions for the most common AI terms.
It serves as an essential resource for professionals in the field, investors, and anyone seeking to understand AI's transformative capabilities. The glossary is designed to be a dynamic, living document, regularly updated to capture the latest developments.
Key terms like Artificial General Intelligence (AGI), AI agents, and Chain of Thought reasoning are explained. The glossary also covers technical aspects such as API endpoints, Compute, Deep Learning, and Diffusion models. Emerging concepts like Mixture of Experts (MoE) and the potential risks of Neuralese are also detailed.
Practical applications and related concepts such as Fine-tuning, GANs, Hallucination, Inference, and Large Language Models (LLMs) are elaborated upon. The glossary provides context on operational aspects like Memory Cache, Model Context Protocol (MCP), and Tokenization, as well as development processes like Training and Transfer Learning.
Finally, it addresses challenges and ongoing research areas including RAMageddon, Recursive Self-Improvement, Reinforcement Learning, Token Throughput, and Validation Loss, offering a holistic view of the current AI landscape.
