Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Climate Tech Needs Machine Learning, Says PAW Climate Conference Chair
  Straight from the horse’s mouth – the founding...
Predictive Policing: Six Ethical Predicaments
  Originally published in KDNuggets. This article is based...
Measuring Invisible Treatment Effects with Uplift Analysis
  Models make predictions by identifying consistent correlations in...
Machine Learning: Business Leaders Must Take an Enlightening Look Under Its Hood (New Training Program)
  In this article, I identify unmet learner needs...

Industry News

AI Can Help Patients—but Only If Doctors Understand It

 Originally published in Wired.com, October 2, 2020. Algorithms can help diagnose a growing range of health problems, but humans need to be trained to listen. Nurse Dina Sarro didn’t know much about artificial intelligence when Duke University Hospital installed machine learning software to raise an alarm when a person was at risk of developing sepsis,

The Computational Limits of Deep Learning Are Closer Than You Think

 Originally posted to DiscoverMagazine, July 24, 2020. Deep learning eats so much power that even small advances will be unfeasible give the massive environmental damage they will wreak, say computer scientists. Deep in the bowels of the...

Inside TikTok’s Killer Algorithm

 TikTok Wednesday revealed some of the elusive workings of the prized algorithm that keeps hundreds of millions of users worldwide hooked on the viral video app. Why it matters: The code TikTok uses to pick your next...

Traffic Prediction With Advanced Graph Neural Networks

  By partnering with Google, DeepMind is able to bring the benefits of AI to billions of people all over the world.  From reuniting a speech-impaired user with his original voice, to helping users discover personalised apps,...

Multi-Armed Bandits and the Stitch Fix Experimentation Platform

 Multi-armed bandits have become a popular alternative to traditional A/B testing for online experimentation at Stitch Fix. We’ve recently decided to extend our experimentation platform to include multi-armed bandits as a first-class feature. This post gives an...

Looking Inside The Blackbox — How To Trick A Neural Network

 Neural networks get a bad reputation for being black boxes. And while it certainly takes creativity to understand their decision making, they are really not as opaque as people would have you believe. In this tutorial, I’ll...

Can GPT-3 Make Analogies?

 Originally published in Medium, Aug 5, 2020. In the early 1980s, Douglas Hofstadter introduced the “Copycat” letter-string domain for analogy-making. Here are some sample analogy problems: If the string abc changes to the string abd, what does...

Dealing with Overconfidence in Neural Networks: Bayesian Approach

 Originally published in Jonathan Ramkissoon Blog, July 29, 2020. I trained a multi-class classifier on images of cats, dogs and wild animals and passed an image of myself, it’s 98% confident I’m a dog. The problem isn’t...

How Not to Know Ourselves

 Originally published in Medium, July 29, 2020. Platform data do not provide a direct window into human behavior. Rather, they are direct records of how we behave under platforms’ influence. Surfing a wave of societal awe and...

Here’s Why Apple Believes It’s An AI Leader—And Why It Says Critics Have It All Wrong

 Originally published in Ars Technica, Aug 6, 2020. Apple AI chief and ex-Googler John Giannandrea dives into the details with Ars. Machine learning (ML) and artificial intelligence (AI) now permeate nearly every feature on the iPhone, but...

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