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Gradient Descent Models Are Kernel Machines (Deep Learning)

 Originally published in infoproc.blogspot.com, Feb 7, 2021. This paper shows that models which result from gradient descent training (e.g., deep neural nets) can be expressed as a weighted sum of similarity functions (kernels) which measure the similarity of a given instance to the examples used in training. The kernels are defined by the inner product

Worried About Your Firm’s AI Ethics? These Startups Are Here to Help.

 Originally published in MIT Technology Review, Jan 15, 2021. A growing ecosystem of “responsible AI” ventures promise to help organizations monitor and fix their AI models. Rumman Chowdhury’s job used to involve a lot of translation. As...

Machine Learning Models are Missing Contracts

 Why pretrained machine learning models are often unusable and irreproducible — and what we can do about it. Introduction A useful approach to designing software is through contracts. For every function in your codebase, you start by writing...

When Are We Going to Start Designing AI With Purpose?

 Originally published in UX Collective, Jan 19, 2021. For an industry that prides itself on moving fast, the tech community has been remarkably slow to adapt to the differences of designing with AI. Machine learning is an...

How Facebook is Using AI to Improve Photo Descriptions for People Who Are Blind or Visually Impaired

 Originally published in [email protected], Jan 19, 2021. When Facebook users scroll through their News Feed, they find all kinds of content — articles, friends’ comments, event invitations, and of course, photos. Most people are able to instantly...

Learning the Language of Viral Evolution and Escape

 Originally published in AAAS, Jan 15, 2021. Natural language predicts viral escape Viral mutations that evade neutralizing antibodies, an occurrence known as viral escape, can occur and may impede the development of vaccines. To predict which mutations...

Machine Learning is Going Real-Time

 Originally published in Chip Huyen, Dec 27, 2020. After talking to machine learning and infrastructure engineers at major Internet companies across the US, Europe, and China, I noticed two groups of companies. One group has made significant...

2020: A Year Full of Amazing AI papers- A Review

 Originally published in GitHub.com. A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and code Even with everything that happened in the world this...

Supporting Content Decision Makers With Machine Learning

 Originally published in The Netflix Tech Blog, Dec 10, 2020. Netflix is pioneering content creation at an unprecedented scale. Our catalog of thousands of films and series caters to 195M+ members in over 190 countries who span...

Hateful Memes Challenge Winners

 Originally published in Facebook AI, Dec 11, 2020. AI has made progress in detecting hate speech, but important and difficult technical challenges remain. Back in May 2020, Facebook AI partnered with Getty Images and DrivenData to launch...

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