AI Terms Explained

Ambiguity is a situation or a statement that can be realized in more than one meaning.

Annotation means adding comments, explanatory notes, or labels to any information.

In the realm of Artificial Intelligence, Agentic AI is a leap into greater autonomy and decision-making.

A chatbot is a program designed to simulate human conversations. It’s an AI assistant that could answer questions based on user requests.

Computer Vision is a branch of Artificial Intelligence (AI) technology that teaches computers to perceive and interpret visual data, just like humans. Computer Vision AI can recognize objects, identify faces, read written text , and track motion.

Data monetization is the process of transforming data into valuable assets that generate economic benefit.

Deterministic systems come in handy while working with AI because they add both reliability and transparency to any process.

Deep Learning is a type of Artificial Intelligence technology that enables machines to learn themselves and make decisions.

A Discriminative model is one type of AI model that strives to discriminate various classes or categories of data. Unlike Generative AI, Discriminative AI acquires skills for classifying instances by finding the patterns and dependencies within existing datasets.

Data augmentation is the process of artificially inflating the limited size of data through many variations that retain most of the essential elements necessary to remain realistic.

Extensibility is the capability of a system, software, or framework to expand, evolve, or be extended easily without major changes.

In the AI development context, interpretability is the extent to which a human can understand and explain AI model decisions.

A multi-modal AI language model is a type of Artificial Intelligence (AI) that processes and understands different types of data at the same time, such as text, images, audio, and video. A traditional language model, which reacts to text alone, is unlike multi-modal AI.

Natural Language Generation (NLG) is one of the aspects of Artificial Intelligence technology that has an express objective: the production of text that appears to have been written by a human.

If we put it in the simplest of words, a Neural Network is a computer system’s simulation of the human brain.

A probabilistic model, also called a probability model, is a mathematical model used to predict future outcomes while accounting for impact from random events…

In the field of AI, prompting is the art of providing specific and clear instructions to an AI tool or model in order to get the desired output.

Stacking is a generalization term used in various contexts.

Structured data is information that is neatly organized into a standardized format.

Summarization involves condensing a lot of text into a smaller version but retaining the key points and the general meaning.

Technical due diligence is a complex investigation into the quality, risks, and scalability of a target company’s technology assets, processes, and infrastructure.

Unsupervised learning refers to a method of how Machine Learning algorithms learn patterns in data without interference by any human expert.

While some of the data is in tabular or database format, most of the data exists freely in an unorganized manner. Data of this nature is referred to as unstructured data.