AI Creators
Krish Naik
Where AI Is Heading In 2026- Generative AI, Agentic AI, LLM Gateways,Guardrails,Evals, LLM Caching
Jun 15, 2026
Key Points
- 1.AI is evolving with generative AI and large language models (LLMs) leading the way.
- 2.From 2022 onward, companies increasingly implement retrieval-augmented generation (RAG) for tailored chatbot solutions.
- 3.Vector databases are crucial for storing data as numerical representations enhancing AI chatbot accuracy.
- 4.Integration of AI applications with third-party tools is becoming standard practice.
Summary
Types of Individuals Interested in AI
The video outlines three types of people looking to enter the AI field, particularly freshers who are either studying or have recently graduated. Understanding these demographics is essential for tailoring AI education and resources.
Rise of Generative AI and LLMs
Post-2021, generative AI took off, largely driven by advancements in large language models like OpenAI's ChatGPT. This evolution represents a major shift in how AI applications can generate responses and solve problems for users.
Importance of Retrieval-Augmented Generation (RAG)
RAG emerged as a method to refine chatbots using company-specific data, moving away from traditional, costly fine-tuning processes. By using vector databases, organizations can produce more relevant and accurate outputs.
Integrating Third-Party Tools
Companies are increasingly incorporating third-party tools and protocols, such as the model context protocol, to improve AI application functionality. This integration allows chatbots to enhance capabilities and provide more comprehensive solutions.
Worth watching for
This video is aimed at individuals interested in entering the AI field, particularly those new to the concepts of generative AI and LLMs.