By learning how to pitch his bot idea while driving a robot, Button.ai Organized by VentureBeat, the international botathon took place July 9-10 in New York, Melbourne, Tel Aviv, and San Francisco. A fifth finalist category was made for people participating online elsewhere in the world. Finals for popular vote and judges' categories were held Tuesday in San Francisco at MobileBeat, a two-day gathering of chatbot and AI leaders, held July 12-13 at The Village. Skoolbot won the portion of the competition decided by judges Phil Libin, an investor in bots from General Catalyst; SmarterChild creator Robert Hoffer; and Alfred Lin, an investor at Sequoia Capital.

Andrew Heikkila is a tech enthusiast and writer from Boise, Idaho. A recent Pew report found that a majority of Americans believe that most human jobs could be automated by 2065. With tech giants like Google and Chrysler collaborating to produce autonomous passenger vehicles, as well as new tech firms like Otto positioning themselves to revolutionize the commercial transportation industry, many are already discussing how we'll handle history's first slew of "driverless" experiences. It's no wonder, then, that talk about technological unemployment is becoming increasingly popular, with many commercial drivers beginning to question whether or not they'll still have jobs in the coming years. While the concept of a world filled with autonomous workers is relatively new to us, digital disruption obviously isn't, and we've consistently overcome technological unemployment in the past.

The recent reports of robots taking over jobs are alarming for many employees and job-seekers. What will happen to the teeming graduates coming out of our colleges? According to HfS Research, 640,000 IT workers in India engaged in low-level tasks won't be replaced by machines. But 10 categories of professionals including cashiers, drivers, factory workers and journalists will be wiped out. Teachers will become bots, BPO workers will be replaced by Artificial Intelligence software, cars will be driverless. Would you need a human police force in the future?

DARPA has been mostly focusing on making new things, pushing the boundary of what is possible to build. Case in point: This new challenge it issued to hackers. DARPA has just started the final round of the Cyber Grand Challenge, a competition among seven fully-autonomous computers to defend themselves and point out flaws in a DARPA computer. The challenge aims to solve a persistent problem in computer systems. Flaws in software often go unnoticed for around 312 days, time which can be exploited by hackers.

On a clear morning in early May, Brian Lathrop, a senior engineer for Volkswagen's Electronics Research Laboratory, was in the driver's seat of a Tesla Model S as it travelled along a stretch of road near Blacksburg, Virginia, when the car began to drift from its lane. Lathrop had his hands on the wheel but was not in control of the vehicle. The Tesla was in Autopilot mode, a highly evolved version of cruise control that, via an array of sensors, allows the car to change lanes, steer through corners, and match the lurching of traffic unaided. As the vehicle--one of a fleet belonging to Virginia Tech's Transportation Institute, which Lathrop was visiting that day--lost track of the road markings, he shook the wheel to disengage Autopilot. "If I hadn't been aware of what was happening, it could have been a completely different outcome," Lathrop told me recently.

IBM TrueNorth chip uses digital spikes to perform neuromorphic computing and achieves ultrahigh execution parallelism and power efficiency. However, in TrueNorth chip, low quantization resolution of the synaptic weights and spikes significantly limits the inference (e.g., classification) accuracy of the deployed neural network model. Existing workaround, i.e., averaging the results over multiple copies instantiated in spatial and temporal domains, rapidly exhausts the hardware resources and slows down the computation. In this work, we propose a novel learning method on TrueNorth platform that constrains the random variance of each computation copy and reduces the number of needed copies. Compared to the existing learning method, our method can achieve up to 68.8% reduction of the required neuro-synaptic cores or 6.5X speedup, with even slightly improved inference accuracy.

In this talk, I will introduce the audience to the emerging area of computational social science, focusing on how machine learning for social science differs from machine learning in other contexts. I will present two related models -- both based on Bayesian Poisson tensor decomposition -- for uncovering latent structure from count data. The first is for uncovering topics in previously classified government documents, while the second is for uncovering multilateral relations from country-to-country interaction data. Finally, I will talk briefly about the broader ethical implications of analyzing social data. Hanna Wallach is a Senior Researcher at Microsoft Research New York City and an Adjunct Associate Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst.

One of the millennium development goals of the United Nations is to eradicate extreme poverty by 2030. That's a complex task, since poverty has many contributing factors. But one of the more significant is the 750 million people around the world who are unable to read and write, two-thirds of which are women. There are plenty of organizations that can help, provided they know where to place their resources. So identifying areas where literacy rates are low is an important challenge.

Machine Learning is one of the most exciting fields in the world. Every week we discover something new, something amazing, something revolutionary. It's incredible, but it can also be overwhelming. That's why we created This Week in Machine Learning! Each week we publish a curated list of Machine Learning stories as a resource to help you keep pace with all these exciting developments.

Gowild Intelligent Technology held the press conference, entitled "When it comes to AI, we are different", for the launch of its new product in Beijing, China on July 8. The event received widespread attention from thousands of people in academia as well as in the technology, gaming, media and entertainment sectors across China and around the world. Gowild released its first generation AI-based 3D holographic product, holoera, that integrates the latest AI engine and VR technology. Transforming the artificial intelligence sector, holoera is the survival carrier on earth of the two dimensional beauty Amber. Amber not only comes equipped with training programs for daily living and learning, but can also receive instructions from its exclusive master, and be instructed based a customized training program. Furthermore, with her superior artificial intelligence, she can engage in barrier-free interaction with humans.