Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
What Percentage of Your Machine Learning Models Have Been Deployed?
  Do your models usually get deployed? Or are...
Video – Credit Models, Microfinance, and Improving the Lives of Families in the Developing World
 Event: Machine Learning Week 2021 Keynote: Credit Models, Microfinance, and...
Video – Identifying Program Effectiveness for Survivors of Human Trafficking from Muneeb Alam of QuantumBlack
 Event: Machine Learning Week 2021 Keynote: Identifying Program Effectiveness for Survivors...
Video – How to Use AI Ethically from Natalia Modjeska of Omdia
 Event: Machine Learning Week 2021 Keynote: How to Use AI...

Industry News

Sharing Learnings About Our Image Cropping Algorithm

 In October 2020, we heard feedback from people on Twitter that our image cropping algorithm didn’t serve all people equitably. As part of our commitment to address this issue, we also shared that we’d analyze our model again for bias. Over the last several months, our teams have accelerated improvements for how we assess algorithms for potential bias and improve our

The Four Most Common Fallacies About AI

 Originally published in VentureBeat, May 8, 2021. The history of artificial intelligence has been marked by repeated cycles of extreme optimism and promise followed by disillusionment and disappointment. Today’s AI systems can perform complicated tasks in a wide range of areas, such...

How Image Search Works at Dropbox

 Originally posted in Dropbox.tech, May 11, 2021 Photos are among the most common types of files in Dropbox, but searching for them by filename is even less productive than it is for text-based files.  When you’re looking...

Inside Netflix’s Quest to End Scrolling – How the Company is Working to Solve One of its Biggest Threats: Decision Fatigue.

 Originally published in Vulture, April 28, 2021.  Ten years ago, Netflix got the idea that its app should work more like regular TV. This was early on in its transition from DVD delivery to streaming on demand,...

Clustergam: Visualisation of Cluster Analysis

 Originally published in MARTIN FLEISCHMANN, April 27, 2021. When we want to do some cluster analysis to identify groups in our data, we often use algorithms like K-Means, which require the specification of a number of clusters....

Aiming for truth, fairness, and equity in your company’s use of AI

 Originally published in FTC, April 19, 2021: Advances in artificial intelligence (AI) technology promise to revolutionize our approach to medicine, finance, business operations, media, and more. But research has highlighted how apparently “neutral” technology can produce troubling...

Moving Beyond “Algorithmic Bias is a Data Problem”

 Originally published in Patterns, April 9, 2021. A surprisingly sticky belief is that a machine learning model merely reflects existing algorithmic bias in the dataset and does not itself contribute to harm. Why, despite clear evidence to the...

Can Artificial Intelligence Combat Wildfires? Sonoma County Tests New Technology

 Originally published in Los Angeles Times, March 19, 2021. Sonoma County is adding artificial intelligence to its wildfire-fighting arsenal. The county has entered into an agreement with the South Korean firm Alchera to outfit its network of...

Data Science for Marketing Optimization – Case Studies from Airbnb, Lyft, DoorDash

 Originally published in Blogboard Journal, Jan 7, 2021. In this article we’ll look at several case studies of data science being used to optimize marketing efforts at companies like Lyft, Airbnb, Netflix, Doordash, Wolt, Rovio Entertainment. In...

Algorithm Helps Artificial Intelligence Systems Dodge “Adversarial” Inputs

 Originally published in Massachusetts Institute of Technology, March 8, 2021.  Method builds on gaming techniques to help autonomous vehicles navigate in the real world, where signals may be imperfect. In a perfect world, what you see is...

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