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AI-Powered Project Management: Insights into Generative AI’s Growing Influence

Data Science Dojo

As we delve deeper into the use cases of Generative AI, we’ll explore how these technologies are not just supporting but also enhancing the project management landscape. Resource Allocation: GenAI analyzes performance data and project requirements to recommend resource distribution, optimizing team deployment and workload management.

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Are Model Explanations Useful in Practice? Rethinking How to Support Human-ML Interactions.

ML @ CMU

XAI methods are typically optimized for diverse but narrow technical objectives disconnected from their claimed use cases. To connect methods to concrete use cases, we argued in our Communications of ACM paper [ 1 ] for researchers to rigorously evaluate how well proposed methods can help real users in their real-world applications.

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Open data using AI for climate action

DrivenData Labs

Managing natural resources ?️ In this post, we recap each area above and pull together applied use cases where partners have made datasets openly available for ongoing practice and learning. Managing natural resources ¶ Recap: The first area is focused on how we monitor and manage natural resources like water, air, and forests.

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Towards Accurate Differential Diagnosis with Large Language Models

Hacker News

In this study, we introduce an LLM optimized for diagnostic reasoning, and evaluate its ability to generate a DDx alone or as an aid to clinicians. 20 clinicians evaluated 302 challenging, real-world medical cases sourced from the New England Journal of Medicine (NEJM) case reports. vs 33.6%, [p = 0.04]).

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New Study: 2018 State of Embedded Analytics Report

Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.

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Angler: Helping Machine Translation Practitioners Prioritize Model Improvements

Machine Learning Research at Apple

With finite time and resources, ML practitioners are forced to prioritize their model debugging and improvement efforts. We built on this insight in a case study with machine translation models, and developed Angler, an interactive visual analytics tool to help practitioners…

ML 130
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Are Model Explanations Useful in Practice? Rethinking How to Support Human-ML Interactions.

ML @ CMU

XAI methods are typically optimized for diverse but narrow technical objectives disconnected from their claimed use cases. To connect methods to concrete use cases, we argued in our Communications of ACM paper [ 1 ] for researchers to rigorously evaluate how well proposed methods can help real users in their real-world applications.

ML 130