This week we learn about the machine learning ninjas at Google, check in with a company retrofitting old cars with new tech, discover Apple’s computer vision capabilities, and anxiously wait for delivery drones taking flight. Plus, what we’re reading and a few things for you to try at home.
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Google’s Machine Learning Ninjas ????
The Machine Learning Ninja Program — no joke – embeds select Googlers with their machine learning team for six months where they work on ML projects, like Smart Reply in Gmail, and RankBrain.
In an earnings call late last year, CEO Sundar Pichai laid out Google’s new vision: “Machine learning is a core, transformative way by which we’re rethinking how we’re doing everything. We are thoughtfully applying it across all our products, be it search, ads, YouTube, or Play. And we’re in early days, but you will see us — in a systematic way — apply machine learning in all these areas.”
If Google’s going to build machine learning into all its products, it needs engineers who have mastery of those techniques.
But Did You Know: Google’s RankBrain machine learning system is now used to process every search query, and is now considered the third most important ranking factor?
A Billion Cars Going Autonomous ???? ???? ????
While mums the word on Apple’s car plans, Pearl Automation has big plans to transform millions of today’s cars into the self-driving vehicles of tomorrow.
Armed with 50 former Apple employees, the team has plans for a slew of devices that can upgrade your car by augmenting it with the latest driving capabilities.
Their first product? A rear-view camera.
While their entry into the auto accessory aftermarket is sort of an anticlimactic entry to the market, the Verge writes. “The differentiator is the attention to quality and detail that Apple is known for. This craftsmanship shines through in Pearl’s offering, as well.”
Apple’s Advanced Computer Vision ????
You might remember that Apple added facial and object recognition to the Photos app for iPhone and iPad to bundle photos according to events and places.
So, what’s so great about this?
Unlike Google Photos, Apple has made sure that Photos only uses machine learning to analyze the photos that are stored locally on your iPhone, eliminating the need to upload your photos to Apple’s servers for processing.
Drones Taking Flight ✈️
The FAA unveiled new rules last week to allow for commercial operation of low-altitude drones weighing less than 55 pounds.
As long as you can pass the skill test, you can operate a drone legally.
However, drones cannot be flown at night, and must always remain within eyeshot of the pilot, making it unlikely that autonomous drone delivery will be flying anytime soon.
The FAA says the rules could “could generate more than $82 billion for the U.S. economy and create more than 100,000 new jobs over the next 10 years.”
What We’re Reading ????
- Society in the Loop Artificial Intelligence. At the heart of human-in-the-loop computation is the idea of building models not just from data, but also from the human perspective of the data. (Joi Ito)
- Meet The New Wave Of Wearables. Stretchable Electronics. Scientists have figured out how to make electronics as pliable as a temporary tattoo—meaning the next big tech platform may be your skin. (Fast Company)
- The Return of the Machinery Question. After many false starts, artificial intelligence has taken off. Will it cause mass unemployment or even destroy mankind? History can provide some helpful clues. (The Economist)
- Internet Archive Is a Beautiful Storage Bin for Our Online Memories. The Wayback Machine is an incredible resource for historians, researchers, journalists looking to see when sites get stealthily edited, people who like gawking at corny web design … really anyone who enjoys puttering around online. And it’s getting a search engine in 2017, which will make digging around even easier. (The Ringer)
- Artificial Intelligence’s White Guy Problem / Artificial Intelligence Has a ‘Sea of Dudes’ Problem. Two articles this week by The New York Times and Bloomberg look at how bias creeps into datasets used to train machine learning algorithms. AI software depends on data sets, and data sets have to be created by computer scientists. What happens when most of those researchers are men?
(New York Times) (Bloomberg)
Try This At Home ????
- Machine Learning Yearning – Andrew Ng’s New Machine Learning Book
- Reverse Engineering The YouTube Algorithm
- The “Python Machine Learning” book code repository and info resource
- How to Start Learning Deep Learning
- A Practical Introduction to Deep Learning with Caffe and Python
- An Overview of Gradient Descent Optimization Algorithms
Emergent Future is a weekly, hand-curated dispatch exploring technology through the lens of artificial intelligence, data science, and the shape of things to come. Subscribe here.