About this series

I'm Ethan Weinberger. After a brief stint in the hedge fund world I'm now a Ph.D student in machine learning at the University of Washington.

The world of AI has had some real breakthroughs mixed with massive amounts of cash and wildly speculative claims - a perfect recipe for BS. Kernels of Truth takes a deep dive into recent work in the field to determine whether reality matches up with the hype.

twitter: @efweinberger, email: ethan [at] honestyisbest [dot] com.

July 14, 2020

RoboCop and You: Why Facial Recognition Discriminates

Machine learning research moves fast - fast enough that we’re still very far from having any kind of strict code of ethics or set of regulations as in medicine. As a result, pseudoscience-esque research has a tendency to crop up every now and then, as it did two weeks ago when Harrisburg University issued a now-deleted press release praising one of its research groups for developing an algorithm to predict a person’s “criminality”…

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June 25, 2020

In AI, Money & Attention Are All You Need

The invention of Transformer models has turned out to be one of the most influential developments in recent machine learning history. Transformers are designed to excel at problems involving human language, such as translating between two languages or summarizing long articles into single paragraphs. While previous deep learning models performed far better than classical, non-deep models at such tasks, they still struggled when presented with long sentences with complex structure…

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What is Honesty Is Best?

We find ourselves living in interesting times. This is a moment of great pain, incredible uncertainty, and collapsing realities — fertile soil for new ideas, new paths, and new institutions. Honesty Is Best brings people together to think about how we got here and to explore what we should do next in order to build a fundamentally better world on the uneven foundations upon which we are perched.

We will play host to a number of regular series about technology, policy, and culture spanning writing, podcasts, and video. Each of these series will be written or anchored by one or two people working actively in the specific area the series is about. The distinct style of each series will reflect that of its creators, with the common threads being a focus on concrete ideas and a commitment to telling the unvarnished truth as they see it.

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Today in Indian History, a four-times weekly series about the context and consequences of events in India’s past written by Sahaj Sankaran, winner of Yale’s South Asian Studies Prize and Diane Kaplan Memorial Prize for his work in Indian history

Segfault, a twice-monthly podcast about Computer Science research hosted by Soham Sankaran, the founder of Pashi and a PhD student in Computer Science at Cornell

Kernels of Truth, a weekly series taking a deeper dive into recent hyped-up developments in artificial intelligence by Ethan Weinberger, a PhD student in machine learning at the University of Washington.

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