Bio
Rohit Kundu is a Ph.D. student in the Electrical and Computer Engineering department of the University of California, Riverside. He is a researcher in the Vision-Language domain of AI and published several papers in top-tier conferences and notable peer-reviewed journals.
Writing for V7 since
Articles
LLMs
Mar 20, 2025
What Is RAG in AI and How to Use It? [LLM + RAG Tutorial]
Discover how Retrieval Augmented Generation (RAG) improves AI outputs for accuracy and reliability. Learn key use cases and RAG implementation strategies for companies.
LLMs
Mar 20, 2025
What Is RAG in AI and How to Use It? [LLM + RAG Tutorial]
Discover how Retrieval Augmented Generation (RAG) improves AI outputs for accuracy and reliability. Learn key use cases and RAG implementation strategies for companies.
AI implementation
Aug 31, 2023
Foundation Models: The Benefits, Risks, and Applications
Looking to dive deeper into foundation models? In this article, we’ll cover all the basics and throw in theoverview of their applications, benefits, and current landscape.
AI implementation
Aug 31, 2023
Foundation Models: The Benefits, Risks, and Applications
Looking to dive deeper into foundation models? In this article, we’ll cover all the basics and throw in theoverview of their applications, benefits, and current landscape.
LLMs
Jun 26, 2023
Large Language Models (LLMs): Challenges, Predictions, Tutorial
In this blog post, we will explain why LLMs are the future of AI as we know it—and take a look at the challenges they’re facing.
LLMs
Jun 26, 2023
Large Language Models (LLMs): Challenges, Predictions, Tutorial
In this blog post, we will explain why LLMs are the future of AI as we know it—and take a look at the challenges they’re facing.
LLMs
Aug 31, 2022
Active Learning in Machine Learning [Guide & Examples]
Active learning is a type of machine learning where the model is trained on only the most relevant data. Explore the benefits and limitations of the framework.
LLMs
Aug 31, 2022
Active Learning in Machine Learning [Guide & Examples]
Active learning is a type of machine learning where the model is trained on only the most relevant data. Explore the benefits and limitations of the framework.
AI-Generated Art: From Text to Images & Beyond [Examples]
Computer vision
AI-Generated Art: From Text to Images & Beyond [Examples]
Computer vision
Active Learning in Machine Learning [Guide & Examples]
LLMs
Active Learning in Machine Learning [Guide & Examples]
LLMs
Large Language Models (LLMs): Challenges, Predictions, Tutorial
LLMs
Large Language Models (LLMs): Challenges, Predictions, Tutorial
LLMs
Foundation Models: The Benefits, Risks, and Applications
AI implementation
Foundation Models: The Benefits, Risks, and Applications
AI implementation
What Is RAG in AI and How to Use It? [LLM + RAG Tutorial]
LLMs
What Is RAG in AI and How to Use It? [LLM + RAG Tutorial]
LLMs
Changelog Updates
Feature improvement
May 13, 2026
Chat with Your Knowledge Hubs
Feature improvement
May 13, 2026
Chat with Your Knowledge Hubs
Feature improvement
May 13, 2026
Chat with Your Knowledge Hubs
Feature improvement
May 12, 2026
Updated Granular Usage Reports
Feature improvement
May 12, 2026
Updated Granular Usage Reports
Feature improvement
May 12, 2026
Updated Granular Usage Reports
