A communications specialist wants to use generative AI to help draft a summary of developments in the biotechnology industry, but also wants to include recent news stories that would not yet have been added to foundation models such as ChatGPT.Which technology can help capture this more recent information?Large Action ModelMultimodal ModelRetrieval Augmented GenerationEdge AII don't know this yet.
Question
A communications specialist wants to use generative AI to help draft a summary of developments in the biotechnology industry, but also wants to include recent news stories that would not yet have been added to foundation models such as ChatGPT.Which technology can help capture this more recent information?Large Action ModelMultimodal ModelRetrieval Augmented GenerationEdge AII don't know this yet.
Solution
The technology that can help capture this more recent information is Retrieval Augmented Generation. This technology uses an external knowledge source to pull in the most up-to-date information, which would include recent news stories that have not yet been added to foundation models like ChatGPT.
Similar Questions
Generative AI is a type of artificial intelligence that can ____.Generate text, images, or other data using generative models.Make predictions about future events.Generate responses on real-time data.Perform complex calculations and mathematical operations.
What are foundation models in Generative AI?
What is a best practice when using generative AI?keeping humans in the loop on AI-generated content and solutionsusing company information to help train publicly available Gen AI modelswriting prompts using broad, generic language to maximize resultsrelying on Gen AI models to inform users when content is copyrightedI don't know this yet.
What are foundation models in Generative AI?A foundation model is a large AI model both post and pre-trained on a vast quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of downstream tasks, such as sentiment analysis, image captioning, and object recognition.A foundation model is a large AI model pretrained on a vast quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of downstream tasks, such as sentiment analysis, image captioning, and object recognition.A foundation model is a large AI model post-trained on a vast quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of downstream tasks, such as sentiment analysis, image captioning, and object recognition.A foundation model is a small AI model pretrained on a small quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of downstream tasks, such as sentiment analysis, image captioning, and object recognition.A foundation model is a large AI model pretrained on a vast quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of upstream tasks, such as sentiment analysis, image captioning, and object recognition.
What are foundation models in Generative AI?A foundation model is a large AI model both post and pre-trained on a vast quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of downstream tasks, such as sentiment analysis, image captioning, and object recognition.A foundation model is a large AI model pretrained on a vast quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of upstream tasks, such as sentiment analysis, image captioning, and object recognition.A foundation model is a large AI model post-trained on a vast quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of downstream tasks, such as sentiment analysis, image captioning, and object recognition.A foundation model is a large AI model pretrained on a vast quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of downstream tasks, such as sentiment analysis, image captioning, and object recognition.A foundation model is a small AI model pretrained on a small quantity of data that was "designed to be adapted” (or fine-tuned) to a wide range of downstream tasks, such as sentiment analysis, image captioning, and object recognition.
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