Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Elon Musk Predicts Artificial General Intelligence In 2 Years. Here’s Why That’s Hype
 Originally published in Forbes, April 10, 2024 When OpenAI’s...
Survey: Machine Learning Projects Still Routinely Fail to Deploy
 Originally published in KDnuggets. Eric Siegel highlights the chronic...
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...

Deep Learning

Which AI Model Most Infringes on Copyrighted Content?

 Originally published in AI Business, March 7, 2024.  OpenAI’s GPT-4 reproduces the most copyrighted content from prompts among four popular large language models, according to new research from AI startup Patronus AI. The startup, founded by former Meta AI researchers, also found that popular large language models from the likes of Meta, Mistral and Anthropic generated copyrighted content. The

Balancing Training Data and Human Knowledge to Make AI Act More Like a Scientist

 Originally published in Tech Xplore, March 8, 2024.  When you teach a child how to solve puzzles, you can either let them figure it out through trial and error, or you can guide them with some basic...

Researchers Enhance Peripheral Vision in AI Models

 Originally published in MIT News, March 8, 2024. By enabling models to see the world more like humans do, the work could help improve driver safety and shed light on human behavior. Peripheral vision enables humans to...

DeepMind’s New Algorithm Adds ‘Memory’ to AI

 Originally published in WIRED.com, March 14, 2017. When DeepMind burst into prominent view in 2014 it taught its machine learning systems how to play Atari games. The system could learn to defeat the games, and score higher than humans,...

New Theory Suggests Chatbots Can Understand Text

 Originally published in Quanta Magazine, Jan 22, 2024.  Artificial intelligence seems more powerful than ever, with chatbots like Bard and ChatGPT capable of producing uncannily humanlike text. But for all their talents, these bots still leave researchers...

AlphaGeometry: An Olympiad-Level AI System for Geometry

 Originally published in Google DeepMind, Jan 17, 2024.   Our AI system surpasses the state-of-the-art approach for geometry problems, advancing AI reasoning in mathematics Reflecting the Olympic spirit of ancient Greece, the International Mathematical Olympiad is a modern-day arena...

A University Curriculum Supplement to Teach a Business Framework for ML Deployment

    In 2023, as a visiting analytics professor at UVA Darden School of Business, I developed and “field tested” a curriculum supplement designed to augment introductory data science courses so that they cover the business-side execution...

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...

How Google Taught AI To Doubt Itself

 Originally published in The Verge, Sept 20, 2023.   Today let’s talk about an advance in Bard, Google’s answer to ChatGPT, and how it addresses one of the most pressing problems with today’s chatbots: their tendency to make...

Page 1 of 9 1 2 3 4 5 6 9