On Friday, one of China's leading tech companies, Cheetah Mobile, announced the 57 million acquisition of New Republic--a move that signals its "journey of a transformation," according to CTO Charles Fan, highlighting its investment in AI and transition into a mobile content company. Founded in 2010, Cheetah Mobile began as a mobile tools provider. Over the last six years, it has become a major player in China's tech scene--and made a big impact, globally. Fan told TechRepublic that the company has over 650,000,000 monthly active users, internationally, in Q1. Fan said he sees the company as a "bridge between China and the world." What makes Cheetah Mobile different, he said, is that 80% of their mobile users are outside of China.

China's next generation missiles to adapt to war situation according to Artificial Intelligence

China's next generation missiles to adapt to war situation according to Artificial Intelligence

Silicon Valley is full of chatter about artificial intelligence, deep learning neural networks, and machine learning. And Intel, the world's biggest chip maker, is becoming a lot more conversant in that chatter today. Intel executive Diane Bryant announced today that the company is working on a next-generation version of its high-end server chip, the Xeon Phi, for A.I. applications. Baidu will use the upcoming Xeon Phi chips in the data centers it is building for its Deep Speech platform, where its networks will be able to parse natural language speech as quickly and accurately as possible. By 2020, there will be more servers handling data analytics than any other workload, Bryant said.

China's next generation missiles to adapt to war situation according to Artificial Intelligence

China's next generation missiles to adapt to war situation according to Artificial Intelligence

The method would assist governments and charities trying to fight poverty but lacking precise and reliable information on where poor people are living and what they need, the researchers based at Stanford University in California said. Eradicating extreme poverty, measured as people living on less than 1.25 U.S. a day, by 2030 is among the sustainable development goals adopted by United Nations member states last year. A team of computer scientists and satellite experts created a self-updating world map to locate poverty, said Marshall Burke, assistant professor in Stanford's Department of Earth System Science. It uses a computer algorithm that recognizes signs of poverty through a process called machine learning, a type of artificial intelligence, he said. Results of the two-year research effort have been published in the journal Science. The system shows an image to a computer, "and the computer's job is to figure what the image is," Burke said.

I think it's time for a refresher to remind us that automation has made leaps and bounds compared to when it first began. We need to continually keep the new abilities and possibilities that automation offers top-of-mind to ensure we are maximizing its full potential. For instance, when people think of automation they often imagine an employee who never makes a mistake, never gets tired, and works 24/7 to process transactions, manipulate data, trigger responses and communicate with digital systems. We've had sophisticated software on computers with chips that operate at hyper-speed for years (think flash trading). Now imagine this scenario being pushed further -- that you can almost immediately add or subtract resources in real time, exactly as your needs ebb and flow, and that these workers can either be actual machines performing physical tasks or computers programmed to execute core business transactions. Such a workforce combines the flexibility and capability of software with a physical interface, and it's called RPA: RPA software programs are faster and more accurate than humans.

When the only option you have is to talk with a chatbot, you cringe when you have to engage with that awful robot that embarrassingly pretends to be human. While you'd love to be chatting with a human, resources are thin and we would all just rather have a better middle ground. Init.ai, the company that was born out of necessity is taking a different approach with chatbots with a smarter and less robotic way of engaging with customers. With a more advanced understanding of language, slang, and context, Init.ai is a glimpse into the future of chatbots. AlleyWatch chatted with cofounder Will Dawoodi about the startup and what companies really want from their chatbots.

In this paper we propose and investigate a novel end-to-end method for automatically generating short email responses, called Smart Reply. It generates semantically diverse suggestions that can be used as complete email responses with just one tap on mobile. The system is currently used in Inbox by Gmail and is responsible for assisting with 10% of all mobile responses. It is designed to work at very high throughput and process hundreds of millions of messages daily. We describe the architecture of the system as well as the challenges that we faced while building it, like response diversity and scalability. We also introduce a new method for semantic clustering of user-generated content that requires only a modest amount of explicitly labeled data.