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Research#AI in Business📝 BlogAnalyzed: Dec 29, 2025 07:42

AI for Enterprise Decisioning at Scale with Rob Walker - #573

Published:May 16, 2022 15:36
1 min read
Practical AI

Analysis

This podcast episode from Practical AI features Rob Walker, VP of decisioning & analytics at Pegasystems, discussing the application of AI and ML in customer engagement and decision-making. The conversation covers the "next best" problem, differentiating between next best action and recommender systems, the interplay of machine learning and heuristics, scaling model evaluation, responsible AI challenges, and a preview of the PegaWorld conference. The episode provides insights into practical applications of AI in a business context, focusing on real-world problems and solutions.
Reference

“We explore the distinction between the idea of the next best action and determining it from a recommender system...”

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Research#graph machine learning📝 BlogAnalyzed: Dec 29, 2025 07:56

Trends in Graph Machine Learning with Michael Bronstein - #446

Published:Jan 11, 2021 22:35
1 min read
Practical AI

Analysis

This article from Practical AI summarizes a conversation with Michael Bronstein, a leading expert in Graph Machine Learning (Graph ML). The discussion covers Bronstein's perspective on the year in Machine Learning, including GPT-3 and Implicit Neural Representations. The primary focus, however, is on Graph ML, exploring its applications in fields like physics and bioinformatics, and highlighting key tools. The article concludes with Bronstein's predictions for 2021, specifically mentioning the application of Graph ML to molecule discovery and non-human communication translation. The interview format provides insights into the practical applications and future directions of Graph ML.
Reference

“The article doesn't contain a direct quote, but summarizes the conversation.”

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Technology#Machine Learning📝 BlogAnalyzed: Dec 29, 2025 08:35

Accessible Machine Learning for the Enterprise Developer with Ryan Sevey & Jason Montgomery

Published:Nov 20, 2017 21:03
1 min read
Practical AI

Analysis

This article summarizes a podcast episode from Practical AI featuring Ryan Sevey and Jason Montgomery, founders of Nexosis. The discussion centers around their journey applying machine learning (ML), starting with identifying cheaters in video games and progressing to time-series data analysis and the Nexosis Machine Learning API. The episode originates from the Strange Loop conference, a developer-focused event. The article promotes the Nexosis API, encouraging listeners to obtain a free key and explore its capabilities for their projects. The focus is on making ML accessible to enterprise developers.
Reference

“They invite you to get your free Nexosis API key and discover what they can bring to your next project at nexosis.com/twiml.”

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