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- [Instructor] Agent AI automates AI
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using the reasoning power of large language models
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to run complex tasks by breaking them into simple tasks.
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Agent AI has some special characteristics
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that makes it different from intelligent chatbots.
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First, agent AI uses the reasoning power of LLM
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to make decisions.
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These are decisions the AI will make on our behalf
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in our absence,
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and so reasoning is very important for our safety.
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We will talk more about this throughout the course.
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This will be helpful for us to design
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and build agent AI products and systems in this course.
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Second, agent AI has memory.
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Why does a chatbot need memory?
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Well, intelligent chatbots,
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like Gemini or ChatGPT,
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can remember the context of a chat
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and continue conversations.
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But it is not an agent AI,
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and it does not have memory.
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So if we ask for something
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and the chatbot gives an incorrect answer,
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it'll forget its mistake.
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An agent AI has memory.
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So if it gives an unsatisfactory answer,
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it can remember and improve it.
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How does it know its answer is unsatisfactory?
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The agent AI has the ability to ponder its own decisions
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and adjust its approach.
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Third, the best part of agent AI is that it can communicate.
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Who do you think it communicates with?
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Well, it can communicate with its environment.
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Think of automation in a factory.
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And it can communicate with other agents.
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Think of multiple agents doing a task each
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to execute on a complex task that you want to automate.
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So an agent AI automates AI
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by breaking complex tasks into simple tasks,
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and uses reasoning to run tools,
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uses memory to remember and improve itself,
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and communicates with the environment
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and other agents to achieve its goals.
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Join me on this journey to learn more about how agents work,
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the many different kinds of agents we can design.
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And I'll teach you how to build agents
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with live exercises using absolutely zero code.
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