AI Accelerators Library

Retrieval Augmented Generation (RAG) has become an industry standard method for interfacing with large language models by making them 'context aware'. However, there are a number of situations where a text generation problem is not solved by interacting with large vector database containing many documents. These problems require context but where the context is not known before query time and is often unrelated to existing vector stores. Usually, they are questions about single documents where desirable behavior is to allow the document to be specified at runtime.

Deep dive into the utilization of zero-shot text classification for error analysis in machine learning models.

This accelerator aims to illustrate how businesses can use DataRobot to effectively and holistically monitor generative AI solutions, using the metrics relevant to them.

This accelerator shows how users can quickly and seamlessly enable LLMOPs or Observability in their existing Generative AI Solutions without the need of code refactoring.

In this accelerator, we will illustrate how to use Generative AI models to cater to Level 1 requests, allowing support teams to focus on more pressing and high visibility requests. Learning from historical communications, Generative AI Agents can maintain the same standard of support communication that the customers are used to. 

This accelerator aims to provide instructions on how to build this type of system using DataRobot's generative AI solution framework. The accelerator shows how you can build a pipeline to create a knowledge base with only trusted research papers, and build a conversational agent that can answer questions from medical professionals.

Use Generative AI and Prompt Engineering to consume cluster insights and create cluster labels for DataRobot clusters.

Use Predictive AI models in tandem with Generative AI models and overcome the limitation of guardrails around automating summarization/segmentation of sentiment text.

Integrate LLM based agents like ChatGPT with DataRobot prediction explanations to quickly implement effective customer communication in AI based workflows.