Summary of Presaise, a Prescriptive Ai Solution For Enterprises, by Wei Sun et al.
PresAIse, A Prescriptive AI Solution for Enterprises
by Wei Sun, Scott McFaddin, Linh Ha Tran, Shivaram Subramanian, Kristjan Greenewald, Yeshi Tenzin, Zack Xue, Youssef Drissi, Markus Ettl
First submitted to arxiv on: 3 Feb 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed paper introduces an initiative from IBM Research aimed at addressing challenges in enterprise adoption of prescriptive AI. The main obstacles are the limitations of observational data for causal inference, the need for interpretable recommendations, and communication silos between data scientists and business users. To overcome these issues, the researchers develop a suite of prescriptive AI solutions incorporating scalable causal inference methods, interpretable decision-making approaches, and large language models to bridge communication gaps via a conversation agent. A proof-of-concept, PresAIse, demonstrates the effectiveness of this approach by enabling non-ML experts to interact with prescriptive AI models through a natural language interface, thereby democratizing advanced analytics for strategic decision-making. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps us make better decisions using artificial intelligence. Right now, it’s hard for companies to use AI because they don’t have good data, the recommendations aren’t clear, and different teams don’t talk to each other. To fix these problems, IBM researchers are working on a special package of tools that can help with all three issues. This package includes ways to make accurate predictions from limited data, approaches to explain why AI is making certain decisions, and a chatbot-like system that helps business users and data scientists work together better. The project has a prototype called PresAIse that shows how this can be done in practice. |
Keywords
* Artificial intelligence * Inference
