Artificial Intelligence Weekly – Artificial Intelligence News #90 – Nov 15th 2018

In the News

A.I. hits the barrier of meaning

Machine learning algorithms don’t yet understand things the way humans do — with sometimes disastrous consequences.

Why China can do AI more quickly and effectively than the US

Harvard wants to school Congress about AI

A tech boot camp will teach US politicians and policymakers about the potential, and the risks, of artificial intelligence.

Also in the news…


Scaling Machine Learning at Uber with Michelangelo

Some thoughts on the evolution of ML at Uber over the last three years: why and how they developed their Michelangelo platform along with the way they have been scaling ML to support large numbers of experiments

Slow Learning

The Economist and others have recently described how online programs like can “equip the masses to use AI.” One of the protagonists, Sara Hooker, feels uneasy about this and gives here a firsthand description of what it really takes to be successful in this field.

Stephen Wolfram on AGI (video)

2h lecture by Stephen Wolfram on what he learned from building Wolfram Alpha.

Can we rule out near-term AGI? (video)

Talk by Greg Brockman, founder of OpenAI.

Software tools & code

Open Images Dataset V4

New dataset released by Google. Around 10 million images with bounding boxes, visual relationships, and image-level labels for 20,000 distinct concepts

Generating custom photo-realistic faces using AI

Controlled image synthesis and editing using a novel TL-GAN model

Facebook Horizon

Open Source Applied Reinforcement Learning Platform

Facebook zero-shot learning

Using text to accurately identify images

Some inspiration

Is artificial intelligence set to become art’s next medium?

Who’s going to profit most from the A.I. wave?


This newsletter is a collection of AI news and resources curated by @dlissmyr. If you find it worthwhile, please forward to your friends and colleagues, or share on your favorite network!

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