Generative AI: Input & Pre-training

Summary

In this video, Ba’Carri, a Senior Technical Product Manager at AWS, introduces the process behind generative AI chatbots, using simple language to break down its functions. She explains how AI models go through pre-training by studying vast amounts of online data, enabling them to understand words, meanings, and language rules. Ba’Carri emphasizes the four key steps in AI processing: input, storage, processing, and output. She also highlights how generative AI enhances productivity by filling knowledge gaps, making it an invaluable tool for personal and professional use, such as planning trips or even improving recipes.

Takeaways

• 😀 Ba'Carri is a Senior Technical Product Manager at AWS and uses generative AI as a personal trip planner.
• 😀 Generative AI can be an excellent tool for planning itineraries when traveling to new cities or countries.
• 😀 Chatbots work through four key steps: input, storage, processing, and output.
• 😀 The steps of input, storage, processing, and output are the same ones used by computers to handle information.
• 😀 Language models undergo a pre-training phase where they learn from vast amounts of data, similar to attending school.
• 😀 Pre-training helps the model recognize words, understand meanings, and grasp some language rules.
• 😀 Once the pre-training phase is complete, the model is ready to respond to user prompts or questions.
• 😀 When a user provides input, the chatbot breaks down the text into tokens, which are smaller pieces representing words or parts of words.
• 😀 These tokens help the chatbot identify relevant information and ignore irrelevant symbols that weren’t in its training data.
• 😀 Generative AI is a powerful tool for enhancing productivity and can fill in knowledge gaps by providing information we may not know.
• 😀 Learning about generative AI is important because it can enhance efficiency and support decision-making in various areas of life.

Q & A

What is the role of Ba'Carri in AWS?

Ba'Carri is a Senior Technical Product Manager at AWS.

How does Ba'Carri personally use generative AI?

Ba'Carri uses generative AI as a personal trip planner, especially when traveling to new cities or countries, helping to create itineraries.

What happens inside a chatbot after you hit enter?

Inside a chatbot, there are four key steps: input, storage, processing, and output. These are the same steps that computers use to handle any information.

What is the first phase a language model undergoes before being used?

The first phase is pre-training, where the model is exposed to vast amounts of data, essentially 'studying' the information, to recognize words, grasp meanings, and understand language rules.

How is pre-training different from traditional schooling?

In pre-training, the model doesn't attend classes or study in the traditional sense. Instead, it processes data from the internet, like every webpage a user visits, to learn about language.

What happens after the language model graduates from pre-training?

After graduating from pre-training, the model is ready to process questions and provide responses based on the knowledge it has learned.

What is the first step in using a language model once it’s ready?

The first step is input, where a user gives the chatbot a prompt or question. For example, asking for an ingredient to make chili spicier.

How does the chatbot break down the input it receives?

The chatbot breaks the input into smaller parts called tokens, which represent each word or part of a word. This helps the model process and understand the question.

What happens when the chatbot breaks down the input into tokens?

The chatbot focuses on meaningful parts of the input, like words, and ignores symbols or unrecognized characters that were not part of the model's training data.

Why is generative AI considered an enhancer in productivity?

Generative AI is an enhancer because it can provide efficiencies in productivity, helping fill gaps in knowledge and offering solutions that individuals might not have considered.