Chatvolt

The speaker introduces the topic of setting up various llms for multiple agents using Open AI's GPT models. They discuss the process of web scraping news pages to create Instagram posts based on artificial intelligence news.

Explanation of the theory behind intelligent agents, including how sensors provide input to the brain (agent) to form behaviors and actions. The discussion delves into the concept of brains as llms in agent systems.

Exploration of behaviorism theory in psychology, focusing on how agents react to their environment based on inputs from sensors. The speaker relates behaviorism to the creation and function of agents in artificial intelligence.

Detailed explanation of the roles and responsibilities of different types of agents, including reactive agents and intelligent systems. The speaker discusses the interaction of agents with their environment and the use of sensors and actuators.

Demonstration of setting up llms as the brains of agents for different tasks, such as writing text, web scraping, and managing tasks. The speaker explains the configuration process for each type of agent and demonstrates the usage of Open AI's GPT models.

Practical demonstration of web scraping news websites to gather information for agent tasks. The speaker discusses the utilization of Python coding for web scraping and news analysis within the agent system.

The speaker discusses setting up tools for multiple sites such as Forbes Beleza, Tech Tudo, and others, explaining the process and options available.

The speaker introduces the concept of an agent planner and explains its role in organizing tasks and content planning, using examples related to book writing.

Details about the agent planner's objectives, focusing on content planning, post scheduling, and the role of intelligence topics.

Explanation on creating a backstory for the agent planner, defining its role in content preparation and information dissemination.

The speaker integrates AI (GPT) into the agent planner, emphasizing the importance of defining objectives and actions for effective content planning.

Discussion on creating an agent researcher responsible for exploring trends, assisting in content development, and aligning with the planner's objectives.

Details about setting up the agent writer, focusing on writing engaging posts, specifying language preferences, and interaction with an AI for content creation.

The speaker assigns tasks to the agent writer, outlining the requirements for writing captivating posts in specific languages and generating image prompts.

Introduction to the agent photographer tasked with creating image prompts, specifying language preferences, and limiting word count for effective image descriptions.

Explanation of the manager agent's supervision role, ensuring task completion and the use of AI for overseeing team activities.

The process of scraping data automatically from websites and creating posts in Portuguese is explained. The researcher collects information to write posts, sets up pre-configured websites, and automates the posting process for Instagram.

The concept of automating posting on Instagram and generating passive income is discussed. By setting up themes and pre-configured websites, the system can create posts automatically, reducing the need for manual intervention.

Challenges related to web scraping, including issues with specific sites and solutions using tools like Beautiful Soup and Ajax, are addressed. The importance of delegating tasks and storing information in databases is highlighted.

The process of generating text and images for Instagram posts using AI models like OpenAI's GPT-3 is demonstrated. The combination of text prompts and image generation for seamless posting is explained.

Cost analysis of post creation and execution using AI models is discussed. The cost per post is calculated, highlighting the affordability and efficiency of automated posting processes.

Discussions on agent training, book recommendations, and the potential for creating teams of agents for specific tasks are explored. The importance of continuous learning and training in AI is emphasized.

The limitations of software tools, such as API usage restrictions and processing capabilities, are addressed. Strategies for overcoming limitations and optimizing agent performance are discussed.