Large Language Models (LLMs) AI (Captioned)

Explained by Common Craft
Artificial intelligence tools, like ChatGPT, can generate original responses to human questions and commands. Behind the scenes, these tools depend on a Large Language Model or LLM. This video explains how LLMs help AI generate responses with human-like qualities.
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Video Transcript:

When you ask artificial intelligence, like ChatGPT, a question, like: “What is the best way to slice bread?” It provides an answer that seems like a human expert. The AI appears to know about types of knives and that bread is heated when cooked.

Does AI really know these things? How can it know about so many topics? Can we trust the answers? To answer those questions, let’s look at the source of the information used by tools like ChatGPT: Large Language Models.

Imagine the task of scanning every word on the internet. That’s every blog, website, research paper, book, newspaper, computer program, and more. That’s the goal of massive computers that power tools like ChatGPT: to capture everything it can on the web. This snapshot of over a trillion words creates the foundation for Large Language Models.

By analyzing the words in the model, ChatGPT can answer our questions and requests with human-like quality. What sounds like expertise is really a math problem for artificial intelligence. It works because powerful computers are trained to look for common patterns between words and phrases, like tomorrow morning, cup of coffee, and suppose that you.

Large language models can also detect context. It can tell, based on words that appear together, if you mean… bat or bat. Every word becomes a math problem that uses artificial intelligence to find what word should come next in a sentence. So, when we ask AI how to slice bread… …it doesn’t know about bread or knives like you and me. It only knows the words in the large language model.

Because it was trained on a trillion words and their context…It can assemble the words that most often answer that question.

Keep in mind that AI responses are based on what is published on the internet, and like the internet, they can be biased, misleading, and inaccurate. Evaluate and use them with skepticism and care.

With experimentation and practice, you can use these tools to easily access the world’s knowledge and find the answers you need, quickly.

 

 

What it teaches:

Artificial intelligence tools, like ChatGPT, can generate original responses to human questions and commands. Behind the scenes, these tools depend on a Large Language Model or LLM. This video explains how LLMs help AI generate responses with human-like qualities.

When a human asks AI how to slice bread, the response sounds human, as if the AI knows about bread and knives. But does AI actually know anything? This video explores how AI uses a large language model to generate original responses that sound human. This video teaches:

    •    How AI gathers the data it needs to generate accurate responses
    •    What kinds of media snapshots are collected by AI
    •    How AI can assemble human-sounding responses
    •    Why humans should be diligent about evaluating and editing AI responses

 

Video Info:

  • Duration:  02m 34s
  • Captions Available:  YES
  • Lesson Plan:  YES
  • Category:  Technology
  • ISTE Standard:  Empowered Learner, Indicator 1d
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