You are an expert B2B copywriter, rewrite without plagiarism on this Artifcial Intelligence A-Z Glossary. Every word must have a one-liner description, "A- AGI
AGI stands for Artificial General Intelligence—a hypothetical future technology that can perform most economically productive tasks more effectively than a human. 

B- Bias
Incomplete data can lead to bias in AI.

C - ChatBot
Chatbots are consumer-friendly interfaces built by AI companies to allow users to engage with an LLM, or large language model. Chatbots allow users to simulate a conversation with an LLM, which can often be an effective way to solicit answers to questions. 

D- Datasets
The information used to teach AI about the world.

F- Foundation Model
As the AI ecosystem grows, a divide is emerging between large, powerful, general-purpose AIs, known as Foundation models or base models, and the more specific apps and tools that rely on them. GPT-3.5, for example, is a foundation model. 

G - GANs
Two AI systems that learn by competing with each other.  GANs are generative models: they create new data instances that resemble your training data. A type of neural network that can generate seemingly authentic photographs on a superficial scale to human eyes. GAN-generated images take elements of photographic data and shape them into realistic-looking images of people, animals, and places.

H- Human-in-the-loop
A human being who guides an AI system as it learns.

I- Image recognition
How AI systems learn to "see" the world around them.

J-Job Replacement 
OpenAI and Goldman Sachs research suggest that AI breakthroughs may lead to more white-collar workers losing their jobs, with up to 50% of U.S. work tasks potentially automated by a language model.

L- Large language model
When people talk about recent AI advancements, most of the time they’re talking about large language models (LLMs). OpenAI’s GPT-4 and Google’s BERT are two examples of prominent LLMs. They are essentially giant AIs trained on huge quantities of human language, sourced mostly from books and the internet. 
M-Multimodal system
A multimodal system is a kind of AI model that can receive more than one type of media as input—like text and imagery—and output more than one type of signal.
N-Nanobots
Nanobots are molecular-sized robots measured on a nanoscale and programmed to accomplish a specific task within the human body. The concept is used to create smart vaccines, cancer therapy, and immunotherapy through painless methods of medication. 

O-Open source
Code and data that’s free for anyone to use.

P-Pattern recognition
It is a data science method that is used to detect, analyze and label patterns or regularities in data.

Q-Quantum computing
Quantum is an experimental field of computing that seeks to use quantum physics to supercharge the number of calculations it is possible for a computer to do per second.
R-Reactive machines
Can analyze, perceive, and make predictions about experiences, but do not store data; they react to situations and act based on the given moment	
S-Structured data
Clearly defined data with easily searchable patterns 
T-Turing Test
A test created by computer scientist Alan Turing (1950) to see if machines could exhibit intelligence equal to or indistinguishable from that of a human
Unsupervised learning: a type of machine learning where an algorithm is trained with information that is neither classified nor labeled, thus allowing the algorithm to act without guidance (or supervision)
V- Virtual assistants
AI-powered applications that carry out tasks for people.


W- Watson
The first AI system to beat a human contestant on a TV game show.
X-risk
X-risk, or existential risk, in the context of AI, is the idea that advanced artificial intelligence may be likely to cause human extinction. 
Zero shot learning
One of AI’s big limitations is that if something isn’t represented in a system’s training data, that system will often fail to recognize it. "