Google acquired Kifi, an app for collecting links from across the Internet, which teams could then collaborate on. No financial terms of the deal were disclosed. The Kifi service and data will not become part of Google. The service will remain fully functional for existing users for a few more weeks, before its shut down. The company is no longer accepting new registrations. The team at Kifi will be joining the Spaces team at Google.

Chinese Premier Li Keqiang called on Saturday for greater global cooperation against terrorism, state media said, as the Asian giant seeks greater international support for its anti-terror fight. Speaking at an Asia-Europe summit, Li said various security challenges - conventional and unconventional - remain prominent even though those regions had remained generally stable and peaceful. "Acts of terrorism are common challenges faced by every nation. Countries should work more closely to fight terrorism, and build societies that are truly open and tolerant so to root out the soil where it grows," said Li. China has sought Western support for its own "war on terror" since the attacks in Paris last November.

I'm Paul Thornton, The Times' letters editor, and it is Saturday, July 16. How much more terrorism can France take? After yet another attack in that country -- this time in Nice, where a driver plowed a truck into a crowd of Bastille Day revelers -- at least 84 people are dead and authorities are busy gathering evidence to determine how it happened. But in the United States, some talking heads seem to possess answers that French investigators have yet to produce. Newt Gingrich, for example, called for government monitoring of mosques, a recommendation that earned him the scorn of The Times' editorial board: In the face of such a threat, people need leaders adept at analyzing data and thinking creatively about intelligence gathering and risk reduction.

Both the bookies and the pollsters predicted the outcome of the European Referendum incorrectly, but do you know who got it right? According to analysis from Pheme, of the 291,000 tweets where a vote was expressed, leave votes outnumbered remain significantly – and that's not even Pheme's main aim. Named after the Greek goddess of fame and rumours, the project, which began in 2014, is designed to assess online rumours, to help journalists determine what's true and what's made up. "Professor Rob Procter (now at Warwick) and I were discussing the manual analysis his team did with the Guardian on analysing rumours circulating during the England riots in 2011 – for example, that the London Eye was on fire," says Kalina Bontcheva, Professor of Text Analytics at the University of Sheffield, who works on Pheme. "My background is in automatic text analysis, so we discussed how rumour analysis and detection can be automated or, at least, support be offered to decision makers to help them with the process."

New technology could lead humans to relinquish control over decisions to use lethal force. As artificial intelligence advances, the possibility that machines could independently select and fire on targets is fast approaching. Fully autonomous weapons, also known as "killer robots," are quickly moving from the realm of science fiction toward reality. The unmanned Sea Hunter gets underway. At present it sails without weapons, but it exemplifies the move toward greater autonomy.

First was the Monte Carlo tree search, an algorithm that rather than attempting to examine all possible future moves instead tests a sparse selection of them, combining their value in a sophisticated way to get a better estimate of a move's quality. The second was the (re)discovery of deep networks, a contemporary incarnation of neural networks that had been experimented with since the 1960s, but which was now cheaper, more powerful, and equipped with huge amounts of data with which to train the learning algorithms. The combination of these techniques saw a drastic improvement in Go-playing programs, and ultimately Google DeepMind's AlphaGo program beat Go world champion Lee Sedol in March 2016. Now that Go has fallen, where do we go from here? Following Kasparov's defeat in 1997, scientists considered that the challenge for AI was not to conquer some cerebral game.

Advancements in AI were recently spotlighted by AlphaGo, a computer program developed by Google's DeepMind team. The program -- which relies on decision-making algorithms and neural networks -- defeated a human European champion at the board game Go in a feat previously believed to be years away. On the investor side, Jim Breyer of Breyer Capital has said AI will deliver massive returns for investors betting on applications for industries including healthcare and entertainment. With this in mind, we used CB Insights' database to look at funding to artificial intelligence startups since 2010. Our artificial intelligence category covers startups primarily focused on developing AI, across areas including image processing, natural language processing, machine learning, deep learning, and predictive APIs, among other core applications.

To find out just how advanced our current AI systems are, researchers have developed a tougher Turing Test - called the Winograd Schema Challenge - which measures how well robotic intelligence matches human intelligence. In the end, the team found that - even though AI is definitely improving every day - our robotic pals are still seriously lacking some common sense, suggesting that it will be some time before AI is fully ready to meld with society. First, before we go any further into the new competition's results, it's important to define what a'Turing Test' actually is. Developed and coined by Alan Turing back in the 1950s, the Turing Test is a way for researchers to challenge computer-based intelligence to see if it can become indistinguishable from human intelligence, which is basically the goal for AI researchers. These tests are mostly language-based because human language is - when you truly think about it - super weird.

Deloitte said that around 3.3 million jobs could be classified as business services roles, and that of those, there was a "high chance" that 800,000 to one million jobs would no longer be performed by humans over the period. Simon Barnes, a Deloitte partner, said that the sector's workforce would "fundamentally change over the next 10 to 20 years". Humans are likely to be liberated from "repetitive and highly structured" roles, while new higher-skilled positions are expected to be created to replace them. Mark Carney, the Bank of England Governor, said last month that many of the jobs and industries we are now familiar with "will be gone tomorrow". The rising speed of technological change threatens to make it difficult to choose a career, and for young people to plan their lives, he said.

The traditional definition of artificial intelligence is the ability of machines to execute tasks and solve problems in ways normally attributed to humans. Some tasks that we consider simple--recognizing an object in a photo, driving a car--are incredibly complex for AI. Machines can surpass us when it comes to things like playing chess, but those machines are limited by the manual nature of their programming; a 30 gadget can beat us at a board game, but it can't do--or learn to do--anything else. This is where machine learning comes in. Show millions of cat photos to a machine, and it will hone its algorithms to improve at recognizing pictures of cats.