Hello everyone! I am Krish Naik, and today I will delve into a fascinating topic that is gaining momentum in the AI world. As we inch closer to 2025, there's a new player entering the field of AI - Agentic AI. Join me as we explore this cutting-edge concept and its importance in the coming years.
Reflecting on the year 2024, we witnessed significant developments in generative AI. Numerous LLM (Large Language Model) models were introduced, with tech giants fiercely competing to create superior models for content generation, applications, and more. As developers, we eagerly embraced different frameworks to integrate LLM models, leading to the creation of remarkable custom chat bots.
Amidst these advancements, a new term emerged around the middle of the year - agentic AI. Companies started discussing multi-agent AI systems, emphasizing their potential in diverse applications. So, what exactly is agentic AI, and how does it differ from generative AI?
In generative AI, the focus lies in creating content. The user inputs a query, accompanied by prompts instructing the LLM on how to behave. For instance, if a user asks an LLM to generate a poem, the output is generated based on the prompt.
On the other hand, agentic AI represents autonomous AI systems with specific goals. These systems operate independently without human intervention to achieve their goals. For example, while generative AI applications might rely on tools like LangChain to integrate external sources like Wikipedia or DuckDuckGo Search, agentic AI systems automatically integrate necessary tools to fulfill a particular task autonomously.
Let's consider a custom bot designed to provide financial advice. If you ask this bot to compare Tesla and NVIDIA stocks, it initiates autonomous workflows. Using tools like YT Finance for stock analysis and news APIs for recent developments, the bot processes information independently. This showcases the potential of agentic AI systems to create complex, intelligent workflows!
As interest in agentic AI grows, several frameworks have emerged to support development:
In this blog, I shared insights into building agentic AI applications using F Data. By integrating models and tools like OpenAI, YT Finance, and DuckDuckGo, it's possible to create a custom chatbot. This bot not only processes information but autonomously interacts with external sources, showcasing the intelligence and complexity of agentic AI.
As we look to the future, these frameworks will be pivotal in developing powerful agentic AI solutions, transforming the landscape of AI applications.
Agentic AI is revolutionizing the world of AI, opening doors to intelligent, autonomous systems capable of achieving business-driven goals. As we approach 2025, mastering agentic AI skills will be essential for developers and companies alike.
To explore more about agentic AI and witness a live demonstration, watch my video here: Agentic AI: Important For GEN AI In 2025.