Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Three Best Practices for Unilever’s Global Analytics Initiatives
    This article from Morgan Vawter, Global Vice...
Getting Machine Learning Projects from Idea to Execution
 Originally published in Harvard Business Review Machine learning might...
Eric Siegel on Bloomberg Businessweek
  Listen to Eric Siegel, former Columbia University Professor,...
Effective Machine Learning Needs Leadership — Not AI Hype
 Originally published in BigThink, Feb 12, 2024.  Excerpted from The...

artificial intelligence

2024 Data Engineering Trends

 Originally published in Kestra, Jan 24, 2024. Doing More with Less The tech industry in 2024 is under pressure to optimize resources. Technology and data leaders are asked to integrate more data to support new AI-driven features while simultaneously being forced to reduce costs and headcount. Judging by the recent layoffs at a.o. Google, Amazon,

The AI Playbook: Providing Important Reminders to Data Professionals

 Originally published in DATAVERSITY. This article reviews the new book, The AI Playbook, by my colleague here at The Machine Learning Times, Executive Editor Eric Siegel.  Free book: Come to Machine Learning Week – June 4-7, 2024 in Phoenix, AZ – to...

Decode the Algorithm: Navigate the World of Machine Learning in Business with ‘The AI ​​Playbook’

  This article reviews the new book, The AI Playbook, by my colleague here at The Machine Learning Times, Executive Editor Eric Siegel.  Free book: Come to Machine Learning Week – June 4-7, 2024 in Phoenix, AZ – to meet author Eric...

Cracking the Business Code of Clusters

 Winning with Data Science is a compelling and comprehensive guide for customers of data science. It teaches readers how to work with data scientists by emphasizing real-world business applications and focusing on how to collaborate productively with...

Fashion Repeats Itself: Generating Tabular Data Via Diffusion and XGBoost

 Originally published by Alexia Jolicoeur-Martineau, Sept 19, 2023. Since AlexNet showed the world the power of deep learning, the field of AI has rapidly switched to almost exclusively focus on deep learning. Some of the main justifications are that...

Google DeepMind Used A Large Language Model to Solve An Unsolved Math Problem

 Originally published in MIT Technology Review, Dec 14, 2023. Google DeepMind has used a large language model to crack a famous unsolved problem in pure mathematics. In a paper published in Nature today, the researchers say it is...

The Key to ML Success: A Book Review of “The AI Playbook”

  This article reviews the new book, The AI Playbook, by my colleague here at The Machine Learning Times, Executive Editor Eric Siegel. Free book: Come to Machine Learning Week – June 4-7, 2024 in Phoenix, AZ...

The Problem with AI Hype and the True Value of ML

  Eric Siegel, was interviewed on the Digital Communicators podcast about his new book, The AI Playbook.  Free book: Come to Machine Learning Week – June 4-7, 2024, in Phoenix, AZ – to meet author Eric Siegel, the...

Vertical AI – Why a Vertical Approach is Key to Building Enduring AI Applications

 Originally published in Greylock, Dec 6, 2023.  The rise of Vertical SaaS in the past decade has demonstrated the power of industry-specific software, producing dozens of winners like Toast, Shopify, Procore, and ServiceTitan. Yet there are still...

The Real Research Behind the Wild Rumors About OpenAI’s Q* Project

 Originally published in Understanding AI, Dec 7, 2023.  On November 22, a few days after OpenAI fired (and then re-hired) CEO Sam Altman, The Information reported that OpenAI had made a technical breakthrough that would allow it to “develop...

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