9/26(Thu) GenAI meetup

9/26(Thu) Saltlux

Gen AI meetup

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ChatGPT

나의 말:

retrieved augumented generation

ChatGPT의 말:

ChatGPT

It seems like you might be referring to a technical or AI-related term, possibly "augmented generation." This could relate to various topics, such as AI-assisted content generation, neural network augmentations, or techniques that enhance generative models.

Could you clarify what you're looking for regarding "retrieved augmented generation"? For example:

Are you asking about a specific method in AI or machine learning?

Do you need information on how retrieval systems can augment generation in AI models?

Let me know so I can provide a more tailored response!

Augmented generation refers to techniques in AI and machine learning that combine generative models with additional resources or inputs to enhance the quality and relevance of the generated output.

This approach is commonly used in tasks such as text generation, image synthesis, and speech generation.

There are two common types of augmented generation:

1. Retrieval-Augmented Generation (RAG)

Definition: Combines retrieval systems (which search for relevant data from a large dataset) with generative models (which create new content).

The model retrieves relevant pieces of information and then uses this data to produce more accurate and coherent output.

Example: OpenAI’s GPT model enhanced by retrieving knowledge from external databases or documents during generation. This is useful for tasks like answering factual questions, summarizing articles, or generating responses grounded in specific contexts.

2. Data-Augmented Generation

Definition: Involves enriching training data or augmenting inputs with additional information, such as metadata, structured data, or contextual cues, to improve model performance.

This can be achieved through techniques like data augmentation, where the model is exposed to variations of the input during training.

Example: Adding context like location or sentiment when generating text, or applying transformations to images when training image generation models to make them more robust.

Both forms of augmented generation are crucial in making AI models more powerful by allowing them to incorporate external knowledge and context, resulting in outputs that are not only creative but also accurate and contextually relevant.

Are you looking for information about a specific application of augmented generation?

#Augumented_generation