Generative AI accelerators¶
Topic | Describes... |
---|---|
Anti-money laundering (AML) alert scoring | Develop a machine learning model that utilizes historical data, including customer and transactional information, to identify alerts that resulted in the generation of a Suspicious Activity Report (SAR). |
Smart cluster labeling using generative AI | Use cluster insights provided by DataRobot with ChatGPT to provide business- or domain-specific labels to the clusters using OpenAI and DataRobot APIs. |
Improve customer communication using generative AI | How generative AI models, like GPT-3, can be used to augment predictions and provide customer-friendly subject matter expert responses. |
Hyperparameter optimization workflow | Build on the native DataRobot hyperparameter tuning by integrating the hyperopt module into DataRobot workflows. |
Zero-shot text classification for error analysis | Use zero-shot text classification with large language models (LLMs), focusing on its application in error analysis of supervised text classification models. |
Optimize customer support workflows with generative AI | Use generative AI models to cater to level-one requests, allowing support teams to focus on more pressing and high-visibility requests. |
Monitor generative AI with custom metrics | Monitor LLMs and generative AI solutions to measure alignment and ROI and to provide guardrails. |
Updated November 9, 2023
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