Categories Beauty Health Wellness

AI Model Optimization Methods: Balancing Customization and Training Data Requirements

In the realm of AI, model optimization is a crucial step to tailor AI systems for specific use cases. However, the level of customization needed often correlates with the amount of training data required. Hereโ€™s a brief overview of four key model optimization methods, illustrated with a graph: ๐Ÿ“Šโœจ

๐Ÿญ. ๐—ฃ๐—ฟ๐—ผ๐—บ๐—ฝ๐˜ ๐—˜๐—ป๐—ด๐—ถ๐—ป๐—ฒ๐—ฒ๐—ฟ๐—ถ๐—ป๐—ด โœ๏ธ

๐——๐—ฒ๐˜€๐—ฐ๐—ฟ๐—ถ๐—ฝ๐˜๐—ถ๐—ผ๐—ป: This method leverages zero-shot or few-shot learning to guide the AI model’s responses using well-crafted prompts.
๐—˜๐˜…๐—ฎ๐—บ๐—ฝ๐—น๐—ฒ: Asking a language model to write a poem with a prompt like “Write a poem about autumn leaves.”
๐— ๐—ผ๐—ฑ๐—ฒ๐—น๐˜€: Both proprietary models like Gpt-4o & open source models like Llama 3.1
๐—ง๐—ฟ๐—ฎ๐—ถ๐—ป๐—ถ๐—ป๐—ด ๐——๐—ฎ๐˜๐—ฎ ๐—ฅ๐—ฒ๐—พ๐˜‚๐—ถ๐—ฟ๐—ฒ๐—บ๐—ฒ๐—ป๐˜: Low
๐—–๐˜‚๐˜€๐˜๐—ผ๐—บ๐—ถ๐˜‡๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—Ÿ๐—ฒ๐˜ƒ๐—ฒ๐—น: Low to Medium

๐Ÿฎ. ๐—ฅ๐—ฒ๐˜๐—ฟ๐—ถ๐—ฒ๐˜ƒ๐—ฎ๐—น ๐—”๐˜‚๐—ด๐—บ๐—ฒ๐—ป๐˜๐—ฒ๐—ฑ ๐—š๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป (๐—œ๐—ป-๐—–๐—ผ๐—ป๐˜๐—ฒ๐˜…๐˜ ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ถ๐—ป๐—ด) ๐Ÿ”

๐——๐—ฒ๐˜€๐—ฐ๐—ฟ๐—ถ๐—ฝ๐˜๐—ถ๐—ผ๐—ป: Uses external databases to fetch relevant information, enhancing the model’s responses by providing additional context.
๐—˜๐˜…๐—ฎ๐—บ๐—ฝ๐—น๐—ฒ: A chatbot retrieving real-time data from Wikipedia to answer a user’s query about recent events.
๐— ๐—ผ๐—ฑ๐—ฒ๐—น๐˜€: Both proprietary models like Gpt-4o & open source models like Llama 3.1
๐—ง๐—ฟ๐—ฎ๐—ถ๐—ป๐—ถ๐—ป๐—ด ๐——๐—ฎ๐˜๐—ฎ ๐—ฅ๐—ฒ๐—พ๐˜‚๐—ถ๐—ฟ๐—ฒ๐—บ๐—ฒ๐—ป๐˜: Medium
๐—–๐˜‚๐˜€๐˜๐—ผ๐—บ๐—ถ๐˜‡๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—Ÿ๐—ฒ๐˜ƒ๐—ฒ๐—น: High

๐Ÿฏ. ๐—ฃ๐—ฎ๐—ฟ๐—ฎ๐—บ๐—ฒ๐˜๐—ฒ๐—ฟ ๐—˜๐—ณ๐—ณ๐—ถ๐—ฐ๐—ถ๐—ฒ๐—ป๐˜ ๐—™๐—ถ๐—ป๐—ฒ ๐—ง๐˜‚๐—ป๐—ถ๐—ป๐—ด (๐—ฃ๐—˜๐—™๐—ง) ๐Ÿ› ๏ธ

๐——๐—ฒ๐˜€๐—ฐ๐—ฟ๐—ถ๐—ฝ๐˜๐—ถ๐—ผ๐—ป: Adjusts the prompts given to the model without changing the underlying weights, using soft prompts that act as placeholders for the desired output. Techniques like LoRA, Soft Prompts
๐—˜๐˜…๐—ฎ๐—บ๐—ฝ๐—น๐—ฒ: Customizing a customer service bot to handle specific types of queries without retraining the entire model.
๐— ๐—ผ๐—ฑ๐—ฒ๐—น๐˜€: Both proprietary models like Gpt-4o & open source models like Llama 3.1
๐—ง๐—ฟ๐—ฎ๐—ถ๐—ป๐—ถ๐—ป๐—ด ๐——๐—ฎ๐˜๐—ฎ ๐—ฅ๐—ฒ๐—พ๐˜‚๐—ถ๐—ฟ๐—ฒ๐—บ๐—ฒ๐—ป๐˜: Medium to High
๐—–๐˜‚๐˜€๐˜๐—ผ๐—บ๐—ถ๐˜‡๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—Ÿ๐—ฒ๐˜ƒ๐—ฒ๐—น: Medium to High

๐Ÿฐ. ๐—œ๐—ป๐˜€๐˜๐—ฟ๐˜‚๐—ฐ๐˜๐—ถ๐—ผ๐—ป ๐—™๐—ถ๐—ป๐—ฒ-๐˜๐˜‚๐—ป๐—ถ๐—ป๐—ด โš™๏ธ

๐——๐—ฒ๐˜€๐—ฐ๐—ฟ๐—ถ๐—ฝ๐˜๐—ถ๐—ผ๐—ป: Involves adjusting the weights of the modelโ€™s training parameters to better fit the specific use case.
๐—˜๐˜…๐—ฎ๐—บ๐—ฝ๐—น๐—ฒ: Retraining a language model on a large dataset of medical literature to create a specialized medical assistant.
๐— ๐—ผ๐—ฑ๐—ฒ๐—น๐˜€: Only open source models like Llama 3.1
๐—ง๐—ฟ๐—ฎ๐—ถ๐—ป๐—ถ๐—ป๐—ด ๐——๐—ฎ๐˜๐—ฎ ๐—ฅ๐—ฒ๐—พ๐˜‚๐—ถ๐—ฟ๐—ฒ๐—บ๐—ฒ๐—ป๐˜: High
๐—–๐˜‚๐˜€๐˜๐—ผ๐—บ๐—ถ๐˜‡๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—Ÿ๐—ฒ๐˜ƒ๐—ฒ๐—น: Very High

By understanding these methods, we can make informed decisions on how to optimize AI models effectively based on our specific needs and available training data. ๐Ÿ”ง๐Ÿ’ก

More From Author

Leave a Reply

Your email address will not be published. Required fields are marked *