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

Microsoft Lays Off Team That Taught Employees How to Make AI Tools Responsibly

 Originally published in The Verge, March 13, 2023. As the company accelerates its push into AI products, the ethics and society team is gone. Microsoft laid off its entire ethics and society team within the artificial intelligence organization as part of recent layoffs that affected 10,000 employees across the company, Platformer has learned. The move leaves Microsoft without a

Distributed Machine Learning at Instacart

 Originally published in Tech At Instacart, March 17, 2023. At Instacart, we take pride in offering a diverse range of machine learning (ML) products that empower every aspect of our marketplace, including customers, shoppers, retailers, and brands....

The Tech Behind Artifact, the Newly Launched News Aggregator From Instagram’s Co-Founders

 Originally published in TechCrunch, March 7, 2023.  Late last month, Artifact, a personalized news reader built by Instagram’s co-founders, opened to the public. The launch was a surprise to many consumers, who wondered why the team behind one of the world’s most...

ML in the Spotlight: Trailblazers with Walter Isaacson Covers Predictive Analytics

 Predictive analytics got another public spotlight and Machine Learning Times Executive Editor Eric Siegel made the cut. Listen to his appearances on Walter Isaacson’s (“Steve Jobs” and “The Innovators”) podcast. Podcast: Trailblazers with Walter Isaacson. The program has over...

ChapGPT Doesn’t “Know” But It Can Tell

  Polanyi’s paradox, named in honor of the philosopher and polymath Michael Polanyi, states, “we know more than we can tell.” He means that most of our knowledge is tacit and cannot be easily formalized with...

Users’ Interests are Multi-Faceted: Recommendation Models Should Be Too

 Originally published in Spotify Research, Feb 22, 2023. A new approach to calibrating recommendations to user interests Users’ interests are multi-faceted and representing different aspects of users’ interest in their recommendations is an important factor for recommender...

The Complex Data Models Behind Shopify’s Tax Insights Feature

 Originally published in Shopify Engineering, Feb 8, 2023. A business’s taxes can be difficult to manage, especially in the United States. Tax laws are complicated and vary state-to-state, city-to-city, and product-to-product, further adding to the complexity. When...

Early Thoughts on Regulating Generative AI Like ChatGPT

 Originally published in Brookings, Feb 21, 2023. With OpenAI’s ChatGPT now a constant presence both on social media and in the news, generative artificial intelligence (AI) models have taken hold of the public’s imagination. Policymakers have taken...

Blueprints for Recommender System Architectures: 10th Anniversary Edition

 Originally published in Amatriain, Jan 29, 2023. Ten years ago, we published a post in the Netflix tech blog explaining our three-tier architectural approach to building recommender systems (see below). A lot has happened in the last 10 years...

Unleashing ML Innovation at Spotify with Ray

 Originally published in Spotify R&D Engineering, Feb 1, 2023. Introduction As the field of machine learning (ML) continues to evolve and its impact on society and various aspects of our lives grows, it is becoming increasingly important...

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