Brief Summary
This video introduces the AI Learning Community and discusses fundamental AI concepts: LLMs, AI workflows, and AI agents. It explains each concept with real-time examples, emphasizing the importance of understanding these building blocks for anyone looking to in AI. The video encourages viewers to take notes, engage with the content, and share their thoughts on LinkedIn to foster community growth and learning.
- LLMs (Large Language Models) understand and generate human-like language.
- AI workflows integrate LLMs with other tools and data sources.
- AI agents automate tasks and make decisions based on prompts.
Introduction to the AI Learning Community
The creator is starting an AI Learning Community to guide individuals in learning AI basics and improving their skills. The goal is to design a complete system to help community members learn AI in a structured way. The video serves as the first in a series, focusing on AI LLMs, AI agents, and AI workflows. Viewers are encouraged to watch the entire video, take notes, and share their insights on LinkedIn. The best LinkedIn posts will be rewarded.
Understanding LLMs (Large Language Models)
LLMs, or Large Language Models, are AI systems that understand and generate human-like language. Examples include Chart GPT, Gemini, and Cloud Graph. LLMs work by analyzing vast amounts of text data to predict the next word in a sequence, similar to how someone might guess what happens next in a movie scene. LLMs respond based on what they have learned from their training data. They provide answers based on the data they have been trained on and only respond when prompted with a question.
Exploring AI Workflows
AI workflows involve integrating LLMs with other tools and data sources to automate tasks. For example, connecting an LLM to LinkedIn or a calendar allows it to access and process information from those sources. Control logic refers to the process of integrating and training data from various tools within a workflow. Unlike LLMs, which rely on past data, AI workflows can be trained with specific data to provide more tailored outputs.
Demystifying AI Agents
AI agents automate tasks and make decisions based on prompts. They can analyze responses and determine the next course of action. AI agents can reissue prompts and refine outputs without human intervention, thinking like a human to correct and improve results. The future of AI is heading towards artificial general intelligence (AGI), which will be like interacting with another human.
Conclusion and Community Engagement
The video recaps the three main topics: LLMs, AI workflows, and AI agents, with definitions provided for each. Viewers are asked to consider which of these technologies will be most impactful in the future and to share their thoughts in the comments. The creator encourages viewers to subscribe, like, and share the video to support the AI Learning Community. He expresses happiness that many people are upskilling and learning together.
