Innovatia Guru

Data Labeling for AI

Data labeling for AI is essentially tagging data. This operation is intended to create a labeled dataset that can be used to train, test, and improve machine learning models. A labeled dataset provides an AI system with the required information to learn and make predictions accurately. Machine learning algorithms rely on labeled examples to recognize patterns and relationships within the data. The desired result may be jeopardized if data labeling is not executed to a high standard of quality.

Data Pre-Processing

Data and content are the foundation of generative artificial intelligence (AI) systems. However,...

Retrieval-Augmented Generation (RAG)

Retrieval-augmented generation (RAG) is an AI approach that optimizes the content generated by...

AI Hallucinations

AI hallucinations may occur for text, audio, and image outputs generated by Large Language Models...

AI Entities in the context of Chatbots

When users interact with chatbots, they may send messages in text or audio form. To formulate...

How Chatbots are related to AI Intent

Chatbots are designed to interact with users. Users submit messages (text/voice) and depending upon...

What is Intelligent Content?

Intelligent content is content that is much more than the dense “wall of words” approach that older...

What is Content Strategy?

Content strategy is the methodology of planning, developing, and managing your content to achieve...

What is Intent?

Intent content is created to help users by educating, informing, teaching, and even possibly...

What is Structured Content?

Structured content is content that is broken down into smaller pieces or chunks. The size of the...