One of the modern computer's first killer apps was predicting the weather. John von Neumann, who built the initial ENIAC computer, became fascinated with predicting weather in the 1930s. He called it "the most complex, interactive, and highly nonlinear problem that had ever been conceived of." In 1948, he assembled a team of meteorologists to create a mathematical model that would describe what weather would occur based on conditions in the atmosphere. These first weather predictions took more than 24 hours to compute, but proved the idea was possible--and that we needed faster computers.

We are living in an era where artificial intelligence (A.I.) will play a significant role in our path forward. Entrepreneur Elon Musk warns that A.I. robots should not be turned into war machines. While Russian president Vladimir Putin recently said the nation that leads in A.I. will be "the ruler of the world." So where does that leave us when it comes to working with robots in the business world? As it turns out A.I. and bots and machine learning are the buzz words of the industry and it would be safe to say pretty much every startup going forward will leverage A.I. or machine learning to build their products of the future.

Last spring, Katie Rivera's daughter came home from the St. Francis Parish School in Bakersfield with some unusual paperwork. The school was pushing parents to sign their children up for a "unique pilot program" taught entirely online and run by a public school district in Los Angeles County. Each student who enrolled in the Lennox Virtual Academy would get a free Chromebook computer to use at school, with access to online classes. All parents had to do was fill out the forms, authorizing St. Francis to share information about their finances and their children's health with the Lennox School District a hundred miles away. "This partnership is expected to bring many benefits for St. Francis students," Principal Kelli Gruszka wrote to parents.

The CIA currently has 137 different artificial intelligence pilot projects underway, according to a senior agency official. Dawn Meyerriecks, the CIA's deputy director for science and technology, told an audience at the annual Intelligence and National Security Summit in Washington that the agency has a "punch list" of different artificial intelligence problems that it wants the private sector to work on. The CIA is already coordinating this work with In-Q-Tel, the agency's venture capital firm, she said. The intelligence community has been eyeing artificial intelligence and machine learning to replace some of the tedious tasks its analysts perform for a while now. In June, Robert Cardillo, the director of the National Geospatial-Intelligence Agency, vowed to bring in robots to do 75 percent of the tasks currently being done by employees to analyze and interpret images beamed in from feeds around the globe and in space.

For many Russian students, the academic year started last Friday with tips on planetary domination from President Vladimir Putin. "Artificial intelligence is the future, not only for Russia, but for all humankind," he said, via live video beamed to 16,000 selected schools. "Whoever becomes the leader in this sphere will become the ruler of the world." Putin's advice is the latest sign of an intensifying race among Russia, China, and the US to accumulate military power based on artificial intelligence. All three countries have proclaimed intelligent machines as vital to the future of their national security.

Anthony Falvo, tells The Associated Press that "no civilians were anywhere near the site." He says he does not have the identity of the al-Shabab member killed.

As we head deeper into the 21st century, the prospect of getting robots to do the dirty business of killing gets closer with each passing day. In Max Tegmark's new book, Life 3.0: Being Human in the Age of Artificial Intelligence, the MIT physicist and founder of the Future of Life Institute contemplates this seemingly scifi possibility, weighing the potential benefits of autonomous machines in warfare with the tremendous risks. The ultimate challenge, he says, will be convincing world powers to pass on this game-changing technology. AI has the potential to transform virtually every aspect of our existence, but it's not immediately clear if we be able to fully control this awesome power. Radical advances in AI could conceivably result in a utopian paradise, or a techno-hell worthy of a James Cameron movie script.

The central Chinese government's efforts to build an " intelligent economy " and "intelligent society" by 2030 in China with an aim to build Rmb10 trillion relevant industries will propel the country's GDP growth over the coming two decades, notes Goldman Sachs. In their Aug. 31 research piece titled "China's Rise in Artificial Intelligence," Piyush Mubayi and colleagues dove deep into China's ambitious plans, the factors that make China unique, and the companies that are aiding faster growth. Get the entire 10-part series on Charlie Munger in PDF. Save it to your desktop, read it on your tablet, or email to your colleagues. Mubayi and team traced China's emergence as a global contender in using AI to propel its economic progress.

In October 2013, Lauri Love was drinking coffee in his dressing gown in his bedroom at his parents' house in the village of Stradishall, Suffolk, when his mother called upstairs to say there was a deliveryman at the front door. Love, whose first name is pronounced "Lowry", like the English painter, clomped downstairs. In the front doorway was a man dressed in a UPS uniform. "Are you Lauri Love?" the man asked. In a single motion, the man grabbed Love's arm while presenting, not a package, but a pair of rattling handcuffs. For the next five hours, while dusk turned to evening outside, Love, then 28, and his parents sat in the front room as a dozen or so men from the National Crime Agency, which investigates organised crime and other serious offences, checked the computers in the house. In Love's bedroom, they found two laptops, and a PC tower humming on his desk. Among the bewildering Rolodex of open tabs in Love's internet browsers, the officers found accounts logged into several hacker forums and arcane internet chatrooms. Downstairs, Love, who knew that anything said in these limbo moments of investigation could be later used against him, kept the conversation to small talk about the weather and football. A little before midnight, Love was told that he was being arrested on suspicion of offences under the 1990 Computer Misuse Act, which covers, among other things, criminal hacking. He was not informed of what crimes he had allegedly committed, and was pressed into the back of an unmarked car, and driven to the police investigation centre in Bury St Edmunds. Love's computers, along with USB drives and old computing hardware, much of which belonged to his father, a computing enthusiast, left, too. Love, who was subsequently diagnosed with Asperger syndrome – a form of autism that causes him to fret and obsess – did press-ups in his cell until, in the early hours of the morning, he fell into a brief and fitful sleep.

Artificial intelligence can accurately guess whether people are gay or straight based on photos of their faces, according to new research suggesting that machines can have significantly better "gaydar" than humans. The study from Stanford University – which found that a computer algorithm could correctly distinguish between gay and straight men 81% of the time, and 74% for women – has raised questions about the biological origins of sexual orientation, the ethics of facial-detection technology and the potential for this kind of software to violate people's privacy or be abused for anti-LGBT purposes. The machine intelligence tested in the research, which was published in the Journal of Personality and Social Psychology and first reported in the Economist, was based on a sample of more than 35,000 facial images that men and women publicly posted on a US dating website. The researchers, Michal Kosinski and Yilun Wang, extracted features from the images using "deep neural networks", meaning a sophisticated mathematical system that learns to analyze visuals based on a large dataset. The research found that gay men and women tended to have "gender-atypical" features, expressions and "grooming styles", essentially meaning gay men appeared more feminine and vice versa.