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.

This fall, an unusual vessel will begin sea trials off the coast of California. The 51-foot-long Boeing Echo Voyager will have no crew. It will glide underwater for days or weeks, quietly collecting data from the ocean floor to send back to crews on ships or on land. Ever since the start of the war in Afghanistan in 2001, the U.S. military has relied more and more on flying drones to take on dangerous air missions. But increasingly, drones are taking to the sea as well.

In reality, the technology behind that feature is completely innocuous (and can be disabled). However, it is also extremely powerful. The concept, which Logz.io is replicating in the IT space, is that a machine can be taught to read, think, and process very complex information. The AI development that Logz.io announced this week is called Unified Machine Intelligence (UMI), which powers a broader platform called Cognitive Insights . This program is trained to teach itself incredible volumes of information about IT management.

On the first day of "camp," two dozen rising high school sophomores arrive at the Stanford Artificial Intelligence Laboratory's Outreach Summer program (SAILORS) giddy and ready to get started. The rigorous, two-week program is designed to encourage young women from underrepresented populations to get more involved in the field of science. High school students Ishla Zareef-Mustafa and Genaro Pamatz participate in an anatomy lab as part of the Stanford Medical Youth Science Program. On the last day of the summer residential Stanford Medical Youth Science Program (SMYSP), 24 high school students, surrounded by family members, friends and mentors, present the research they have been working on during the five-week summer program.These programs, which fall under the umbrella of Stanford Pre-Collegiate Studies, are designed to provide teenagers from underrepresented populations with an opportunity to explore careers in science, but also to build new relationships, while taking what they've learned back to their home communities. The SAILORS curriculum includes lectures, hands-on research projects and mentoring activities that are intended to educate and excite young women about artificial intelligence.