engineer


You Could Become an AI Master Before You Know It. Here's How.

#artificialintelligence

At first blush, Scot Barton might not seem like an AI pioneer. He isn't building self-driving cars or teaching computers to thrash humans at computer games. But within his role at Farmers Insurance, he is blazing a trail for the technology. Barton leads a team that analyzes data to answer questions about customer behavior and the design of different policies. His group is now using all sorts of cutting-edge machine-learning techniques, from deep neural networks to decision trees.


China wants to bring #artificialintelligence to its classrooms to boost its education system: "super teacher" is an AI powered education platform developed by online education start-up Master Learner's 300 engineers • r/Sino

#artificialintelligence

For Peter Cao, who has dedicated 16 years of his career to teaching chemistry in a high school in central China's Anhui province, in every teacher there lives a "doctor". He spends two to three hours a day grading assignments, a process the 38-year-old describes as "diagnosing". "By reviewing the homework of my pupils, I can have an overall picture about their understanding of the lessons I give," Cao said, adding that this "diagnosis" helps him draw up a teaching plan for the following day. But if the Chinese online education start-up Master Learner has its way, Cao and his 14 million fellow teachers in China will be able to hand this time-consuming review process to a "super teacher", a powerful "brain" capable of answering nearly 500 million of the most tested questions in China's middle schools as well as scoring high points in each Gaokao test, China's life-changing college entrance exam, for the past 30 years. If the super teacher sounds too smart to be human, that is because it is not.


video-shows-apple-project-titan-self-driving-lexus-test-2603248

International Business Times

Apple has been low key about it autonomous car tech, dubbed Project Titan, but there is now a short video of the iPhone company's self-driving efforts. Voyage co-founder MacCalister Higgins posted a short video of Project Titan's test Lexus SUV, which he called "The Thing." The video givies the public a glimpse of what Apple is up to. The top of the white vehicle is equipped with a suite sensors and self-driving hardware. Higgins said on Twitter the front and back both have 6 LiDARS and that the "majority of the compute stack is likely located inside the roof unit."


Google uses AI to make email smarter

#artificialintelligence

Google Inc. is applying its artificial intelligence (AI) technology to not only prevent spam emails but also as an email reply tool for users, a company engineer said Wednesday. Google said its machine learning model can ferret out spam and phishing messages with 99.9 percent accuracy, even spam that are carefully crafted to deceive people, "Our goal is to make Gmail the most productive email in the world," said Paul Lambert, Google's product manager. Defining five main threats to Gmail as malware, account hijacking, phishing, web attacks, spam, the engineer said Google aims to keep users safe. The new system uses an AI-based neural network to analyze and flag the suspicious messages, especially those written specifically to subvert simpler filters. Google estimates up to 70 percent of messages in Gmail's inbox are spam, Lambert said.


Google's machine-learning software has learned to replicate itself

#artificialintelligence

Back in May, Google revealed its AutoML project; artificial intelligence (AI) designed to help them create other AIs. Now, Google has announced that AutoML has beaten the human AI engineers at their own game by building machine-learning software that's more efficient and powerful than the best human-designed systems. An AutoML system recently broke a record for categorizing images by their content, scoring 82 percent. While that's a relatively simple task, AutoML also beat the human-built system at a more complex task integral to autonomous robots and augmented reality: marking the location of multiple objects in an image. For that task, AutoML scored 43 percent versus the human-built system's 39 percent.


AI Algorithms Are Starting to Teach AI Algorithms

#artificialintelligence

At first blush, Scot Barton might not seem like an AI pioneer. He isn't building self-driving cars or teaching computers to thrash humans at computer games. But within his role at Farmers Insurance, he is blazing a trail for the technology. Barton leads a team that analyzes data to answer questions about customer behavior and the design of different policies. His group is now using all sorts of cutting-edge machine-learning techniques, from deep neural networks to decision trees.


There's a huge opportunity in robotics for early career computer scientists and serious software engineers

ZDNet

There's a major roadblock to deeper market penetration of enterprise robotics, and a new generation of early career computer scientists and more seasoned software engineers may hold the answer. I recently had a chance to speak with Maya Cakmak, assistant professor at the University of Washington, Computer Science & Engineering Department, where she directs the Human-Centered Robotics Lab. To understand PbD, consider collaborative robots from companies like ABB and Kuka. The units consist of articulated arms that can be programmed to help workers do a variety of things, such as pick and place objects, test devices and components, and perform simple but precise manufacturing tasks. So-called "cobots" are relatively inexpensive and operate alongside humans, and many of the use cases involve small- to mid-sized businesses.


AI Algorithms Are Starting to Teach AI Algorithms

MIT Technology Review

At first blush, Scot Barton might not seem like an AI pioneer. He isn't building self-driving cars or teaching computers to thrash humans at computer games. But within his role at Farmers Insurance, he is blazing a trail for the technology. Barton leads a team that analyzes data to answer questions about customer behavior and the design of different policies. His group is now using all sorts of cutting-edge machine-learning techniques, from deep neural networks to decision trees.


Google's AutoML Project Teaches AI To Write Learning Software

#artificialintelligence

White-collar automation has become a common buzzword in debates about the growing power of computers, as software shows potential to take over some work of accountants and lawyers. Artificial-intelligence researchers at Google are trying to automate the tasks of highly paid workers more likely to wear a hoodie than a coat and tie--themselves. In a project called AutoML, Google's researchers have taught machine-learning software to build machine-learning software. In some instances, what it comes up with is more powerful and efficient than the best systems the researchers themselves can design. Google says the system recently scored a record 82 percent at categorizing images by their content.


Top 6 errors novice machine learning engineers make

@machinelearnbot

In machine learning, there are many ways to build a product or solution and each way assumes something different. Many times, it's not obvious how to navigate and identify which assumptions are reasonable. People new to machine learning make mistakes, which in hindsight will often feel silly. I've created a list of the top mistakes that novice machine learning engineers make. Hopefully, you can learn from these common errors and create more robust solutions that bring real value.