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If you missed todays live event watch here TLDW Nelson welcomed the group and asked participants to turn on their cameras. He noted that the session was being recorded and would be shared afterwards. There was some initial technical setup as participants joined and got their cameras working. Nelson provided an overview of AI foundations, explaining the key concepts of data, training, models, and outputs. He emphasized that AI models learn from data, not explicit rules, and that the quality and diversity of the training data is crucial. He also discussed the differences between open-source and closed-source AI models. Nelson explained the importance of prompting and context when interacting with AI models. He discussed the different types of prompts (instructional, question, few-shot, and system) and how they guide the model's responses. He also covered the concept of context, noting that models have a limited "memory" and providing too much context at once can overwhelm them. Nelson introduced the concept of AI agents - systems that can autonomously perform tasks on behalf of the user. He explained how agents have access to tools and APIs that allow them to take actions in the real world, beyond just generating text. He demonstrated how an AI agent can be configured with a chat model, memory, and various tools to execute commands. Nelson discussed how AI agents can be used for automation, with the ability to trigger actions on schedules or events. He explained the Model Context Protocol (MCP) which allows AI models to integrate with external tools and APIs. He provided examples of how an agent could be used to perform tasks like sending emails or checking internet traffic. Nelson summarized the key topics covered and noted that he would be publishing the recording for the community. He also mentioned plans to invite guest speakers, like Java expert Josh Long, for future sessions in the Amigos Code community.

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