Copy
Machine Learnings

Awesome, not awesome.

#Awesome
"The world’s first autonomous tram was launched in unspectacular style in the city of Potsdam, west of Berlin, on Friday...Fitted with multiple radar, lidar (light from a laser), and camera sensors, forming digital eyes that film the tram and its surroundings during every journey, the tram reacts to trackside signals and can respond to hazards faster than a human. Its makers say it is some way from being commercially viable but they do expect it to contribute to the wider field of driverless technology, and have called it an important milestone on the way to autonomous driving.” - Kate Connolly, Correspondent Learn More from The Guardian >

#Not Awesome
"Algorithms do not provide divine insight into people’s objective moral good. Rather, they predict patterns from the data they are fed — data that depend on which information is available and on which information the programmers deem relevant. This means that the people who design predictive child-welfare algorithms, however well-intentioned, insert personal, historical, and systematic biases into equations that, by definition, perpetuate those biases. Thousands of unwitting families are affected in the process. Families like mine. One-hundred and sixty days ago, my three- and four-year-old daughters were removed from my custody, on a temporary but indeterminate basis, because authorities in Broward County, Florida, deemed them unsafe in my care..." - Elizabeth Brico, Writer Learn More from UNDARK >

What we're reading.

1/ The Boston Public School System learns the hard way that even when an algorithm can can be used to solve a major problem, conflicts between humans can stop progress from being made. Learn More from The Boston Globe > 

2/ To build fair criminal justice algorithms that hand out sentences to all populations equally, “we would need to live in a society of perfect surveillance so that there is absolute police knowledge about every single crime so that nothing is excluded." Learn More from TechCrunch >

3/ A House subcommittee within the government thinks neither Congress nor the Executive Branch are doing enough to support artificial intelligence research - and believe the US will struggle to maintain it's lead in the field over China. Learn More from Axios >

4/ The future of transportation will be one in which human engineers and self-driving vehicles work together to get people to their destinations - "engineers [will] monitor routes that present the least amount of danger for riders and select optimal autonomous routes for passengers." Learn More from TechCrunch >

5/ Teams of top scientists around the world compete to create an autonomous "non-humanoid" robot to explore an underwater cave in DARPA's Subterranean Challenge. Learn More from MIT Technology Review >

6/ Alphabet's DeepMind partners with the Unity game development platform to create new virtual environments so they can test AI-behaviors in situations that more closely resemble the physical world. Learn More from Engadget >

7/ Since you won't have to focus on the road when you're sitting inside of a fully-autonomous car, research labs are thinking up new experiences to make your "driving" experience enjoyable. Learn More from MIT Technology Review >

What we're building.

We're building a product called Journal that is, well, a new kind of journal!

It helps you find and organize information across the web and your apps when you're doing research or starting a new project.

Today we each use dozens of disconnected apps to live our lives and do our jobs. Each time we jump from one to another to find information, we're met with distractions that steal our time away from activities we actually want to focus on. Journal is special because of how easy it makes it to get back to information you care about - and the machine learning algorithms we've built power a search experience that makes it possible.

For example the gif below shows me saving articles and emails with Journal that I want to hang onto, then using search to get back to them so I can write this newsletter faster :).

Add your name to the waitlist for early access >

Links from the community.

"Introduction to Machine Learning for Coders: Launch" submitted by Avi Eisenberger (@aeisenberger) . Learn More from Fast.ai >

"How to Visualize Decision Trees" submitted by Samiur Rahman (@samiur1204). Learn More from Explained.ai >

"I made a machine learning chicken rice classifier in ~4 hours to tell me what type of chicken rice I bought for lunch" by Preston Lim (@prestonlim). Learn More from Noteworthy >

"Machine Learning Day Two" by Paul Okoduwa (@paulokoduwa). Learn More from Noteworthy >

First time? Subscribe to Machine Learnings 🤖
30/09/18 View this email in your browser
Copyright © 2018 Machine Learnings, All rights reserved.


Done learning about AI?
Opt out of emails