In the deadliest attack against Indian forces in more than a decade, militants sneaked into an army encampment in the disputed territory of Kashmir early Sunday and opened fire on sleeping soldiers, killing at least 17 and wounding dozens. The four assailants, who also threw grenades that caused tents and temporary shelters to catch fire at the army brigade headquarters at Uri, were killed in a gun battle with security forces that lasted six hours, authorities said. Indian officials blamed the Pakistan-based militant group Jaish-e-Mohammed for the attack, saying it had recovered weapons from the assailants that carried Pakistani markings. Lt. Gen. Ranbir Singh, the director of military operations, said he contacted his Pakistani counterpart to convey "serious concerns." Indian Home Minister Rajnath Singh was more pointed, saying on Twitter: "Pakistan is a terrorist state, and it should be identified and isolated as such."

Over the years, Alphabet and Facebook have invested in everything from walking dog robots to autonomous high altitude wind turbine planes. While not always directly related to their core business, these investments provide an outlet for generous cash flows and could open up future business opportunities. At the very least, crazy science projects generate buzz for the company, which certainly doesn't hurt. However, these two aren't the only tech companies that invest heavily in far-off scientific endeavors in hopes of big payoffs. Microsoft (NASDAQ:MSFT) employs hundreds of scientists through the powerful entity known as Microsoft Research, which has contributed to nearly every product sold by the company in the last several decades.

He Zhigang's eyes pleaded with the elevator dial as he stood waiting on the ground floor. The red numbers wouldn't budge. He glanced at his phone. He pushed back his helmet, lifted the delivery bag of steamed buns and prepared to run up 20 flights of stairs. The hungry office worker probably won't remember who brought him lunch on a Friday afternoon, or that it was 11 minutes and 20 seconds before the allotted time.

'Chatbots are the new apps," said Microsoft's CEO Satya Nadella earlier this year. He was not the first senior tech exec to make this claim. "Threads are the new apps," suggested Facebook's head of messaging products David Marcus in January, referring to the threads of conversation in apps such as Facebook Messenger and WhatsApp. Nadella and Marcus see chatbots – computer programs that you interact with by "chatting", for example in threads in messaging apps – as an important new human/machine interface. Both of their companies have launched tools to help developers create these bots, and between April and September, more than 30,000 were made for Facebook Messenger alone. The shopping and breaking news bots in Messenger's ancestors are chatbots such as AI psychotherapist Eliza from the mid-1960s and Parry, a bot mimicking a human with paranoid schizophrenia, in the early 1970s. Since 1991, the chatbot equivalent of the Olympics has been the annual Loebner prize, which challenges bots ...

When Sebastian Thrun started working on self-driving cars at Google in 2007, few people outside of the company took him seriously. "I can tell you very senior CEOs of major American car companies would shake my hand and turn away because I wasn't worth talking to," said Thrun, now the co-founder and CEO of online higher education startup Udacity, in an interview with Recode earlier this week. A little less than a decade later, dozens of self-driving startups have cropped up while automakers around the world clamor, wallet in hand, to secure their place in the fast-moving world of fully automated transportation. And these companies are hungry for talent and skill sets many don't have. "Uber has just bought a half-a-year-old company [Otto] with 70 employees for almost 700 million," Thrun said.

After decades of stagnation in research and development of artificial intelligence solutions, machine learning has blossomed again – and its seeds are spreading to financial services. Sofia Lotto Persio reports on how AI is improving the field. Almost 20 years later, in March 2016, Google's AlphaGo programme beat South Korean champion Lee Sedol at four matches of Go, a strategy game, in what represents another historic breakthrough for artificial intelligence (AI). In the two-decade span between these achievements, AI has progressed tremendously. Go is a much more complex game than chess, as there are more possible positions on the board than there are atoms in the universe.

"In the time of your life, live -- so that in that wondrous time you shall not add to the misery and sorrow of the world, but shall smile to the infinite delight and mystery of it." "We wanted something that was uplifting and also spoke to a much broader audience," said photographer Levon Parian, one of a team who created the monument. The five-ton piece was sculpted by Glendale architect Vahagn Thomasian from volcanic rock quarried from Armenia's Ararat Valley. The split in the monument represents the disruption of the 1915-18 genocide, which claimed the lives of about 1.2 million Armenians under the Ottoman Empire, which became the modern republic of Turkey. The Turkish government disputes that a genocide took place.

IBM has launched three Power8 Linux servers designed to accelerate artificial intelligence, deep learning, and advanced analytics applications. The new systems tap the Nvidia NVLink technology to move data five times faster than any competing platform, said Stefanie Chiras, an IBM vice president, in an interview with VentureBeat. These systems and their operating systems are part of a larger business group that generates about 2 billion a quarter for IBM. And the A.I. markets they're going after have exploded in the past couple of years. IBM claims that the combination of Power8 processors and Linux software results in systems that deliver 80 percent more performance per dollar than the latest x86-based (Intel or AMD) servers.

Mobileye and Tesla have begun trading barbs illuminating the real reason behind their split. "[Tesla's Autopilot] is not designed to cover all possible crash situations in a safe manner," said Amnon Shashua, Chairman and CTO of Mobileye, the Israel-based maker of collision detection and driver assistance systems. "[Telsa] was pushing the envelope in terms of safety." "When Tesla refused to cancel its own vision development activities and plans for deployment, Mobileye discontinued hardware support for future platforms and released public statements implying that this discontinuance was motivated by safety concerns." Mobileye--the company whose technology underlies the majority of ADAS (Advanced Driver Assistance Systems) and semi-autonomous driving suites on the market, may not be at the cutting edge of the technology on which they've built their reputation.

Analyze internal and external data through advanced analytics uncovering key relationships and trends from relevant information.Recommend solutions to improve the ability for the business to make optimized, real-time, and predictive based business decisions fostering a new level of intelligence and drive quantified business value.• Highly trained statistical / operations research analyst in analytical disciplines (linear, mixed linear, constraint programming, modeling, simulation, time series analysis, pattern recognition, queuing theory, multivariate analysis, and other predictive analytics techniques.Requirements• Candidates with Singapore working experience highly preferred• Master's degree in Statistics or Operations Research• 5 years experience in Natural Language Processing (NLP)• 5 years experience in data mining, statistical modeling or optimization projects using tools such as SPSS, R, SAS, iLog• 5 years experience in working on a variety of advanced analytics projects with good understanding of the different stages of an analytics project• 2 years experience in working with databases, data mapping, data validation and data transformation• Strong experience in Unstructured Information Management Architecture, Computational Linguistics, and Machine Learning.• Strong knowledge and hands-on experience in Big data analytics and related open-source or commercial platforms is preferred.•