One of the most remarkable details of a fatal collision earlier this month involving a tractor trailer and a Tesla electric car operating in self-driving mode was the fact that the car apparently mistook the side of the truck for the sky. As Tesla explained in a public statement following the accidental death, the car's autopilot was unable to see "the white side of the tractor trailer against a brightly lit sky"--which is to say, it was unable to differentiate the two. The truck was not perceived as a discrete object, in other words, but as something indistinguishable from the larger spatial environment. It was more like an elision, a continuation of the sky by deceptive means. Examples like this are tragic, to be sure, but they are also technologically interesting, in that they give momentary glimpses of where robotic perception has failed.

The aim of the hotel, as CEO Hideo Sawada puts it, is a serious one: to be the most efficient hotel in the world. He draws on comparisons with low-cost airlines that "changed how we travel." Two years ago, as hotel prices continued to rise, the CEO (who runs the nearby Huis Ten Bosch theme park) began discussions with robotics and engineering experts with the aim of creating an efficient hotel, one that costs (both fiscally and environmentally) less. If you thought Hen-na Hotel was a kitschy gimmick, well, that's partly true. Still, the bigger picture here is that researchers from Japan's largest, most influential university are involving themselves and testing out cutting-edge green technology, as well as trying to create a space where both robots and humans can move around and do what they want (or need) to do.

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.

NASA plans to send its next rover to Mars in the summer of 2020, so that it arrives on the red planet in February 2021, the space agency said Friday. The "Mars 2020" rover, which borrows a lot of its design features from its wildly successful predecessor Curiosity, has cleared an extensive review process and is now ready to enter the final design and construction phase. "The Mars 2020 rover is the first step in a potential multi-mission campaign to return carefully selected and sealed samples of Martian rocks and soil to Earth," Geoffrey Yoder, acting associate administrator of NASA's Science Mission Directorate in Washington, said in a statement. "This mission marks a significant milestone in NASA's Journey to Mars -- to determine whether life has ever existed on Mars, and to advance our goal of sending humans to the red planet." Mars, despite its inhospitable climate and heavily irradiated surface that would kill humans in a matter of minutes, has been a source of unending fascination for scientists and science fiction writers alike.

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.

Machines could put more than half the world's population out of a job in the next 30 years, according to a computer scientist who said on Saturday that artificial intelligence's threat to the economy should not be understated. Expert Moshe Vardi told the American Association for the Advancement of Science (AAAS): "We are approaching a time when machines will be able to outperform humans at almost any task. "I believe that society needs to confront this question before it is upon us: if machines are capable of doing almost any work humans can do, what will humans do?" Physicist Stephen Hawking and the tech billionaires Bill Gates and Elon Musk issued a similar warning last year. Hawking warned that AI "could spell the end of the human race" and Musk said it represents "our biggest existential threat". Related: 'Mini-brains' could revolutionise drug research and reduce animal use The fear of artificial intelligence has even reached the UN, where a group billing itself the Campaign to ...

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.