Base Foundation Models Flashcards
AWS Bedrock Base foundation models (14 cards)
What factors should you consider when choosing a foundation model?
Model types, performance requirements, capabilities, constraints, compliance, customization levels, inference levels, licensing agreements, context window size, latency, and whether the model is multimodal.
What is Amazon Titan?
A high-performing foundation model from AWS capable of handling text, images, and multimodal tasks via Amazon Bedrock API. It can also be fine-tuned with your own data.
What are the primary use cases for Amazon Titan, Llama-2, Claude, and Stability AI?
Amazon Titan: Content creation, classification, education
Llama-2: Text generation, customer service
Claude: Analysis, forecasting, document comparison
Stability AI: Image creation for advertising, media, and more
Why is the number of input tokens significant for a foundation model?
Models with higher token limits can handle larger context windows, making them better suited for tasks like analyzing large code bases or books.
Which model is most cost-effective for 1,000 tokens, and why is pricing important?
Amazon Titan Text Express is the cheapest, followed by Llama-2 and Claude. Pricing is crucial because more expensive models may provide better answers but might not always justify the cost for your needs.
What are multimodal capabilities in foundation models?
Multimodal models can process multiple types of inputs (e.g., audio, text, video) and generate various outputs (e.g., images, audio, video, text) simultaneously
What is Amazon Bedrock used for?
Amazon Bedrock provides API access to foundation models, including Amazon Titan, enabling easy integration and use of these models in applications.
What makes smaller foundation models more cost-effective?
Smaller models are usually less expensive because they consume fewer resources but may have limited knowledge and capabilities compared to larger models.
What are some considerations when using Claude for large input data?
Claude has a token limit of 200K, allowing it to handle larger context windows. This makes it useful for processing large codebases or entire books.
Why is testing essential when choosing a foundation model?
Testing helps determine how well a model fits specific requirements, such as input handling, accuracy, latency, and cost-effectiveness.
Which foundation model is specialized in image generation?
Stability AI’s Stable Diffusion is specialized in image generation, often used for advertising and media.
How do pricing differences impact the choice of foundation models?
Higher-priced models might provide more accurate or comprehensive answers, but cost-effective models can often meet specific needs without overspending.
What are some use cases for Llama-2?
Llama-2 is suited for tasks like text generation and customer service due to its ability to handle dialogue and large-scale tasks.
Why are context windows important in foundation models?
Context windows determine how much data can be sent to a model at once, impacting the model’s ability to process and respond to complex inputs effectively.
