If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
An engineer working for Japanese carmaker Nissan has built a robot to help farmers reduce the use of herbicides and pesticides on their rice crops. The compact robot, called Aigamo, is designed to mimic the natural use of ducks that paddle around in flooded paddy fields. Ducks have been used as natural weed repellents for centuries to tear them up and feed on insects, with their manure even acting as an additional fertiliser. As it glides through the water, two mechanisms on the bottom muddy the water to prevent weeds from getting enough sunlight to grow. The technique was used in the late 20th century with live ducks, called'aigamo,' which would paddle the water with the same results and eat any insects they found along the way.
SpaceX CEO Elon Musk has announced that one of the company's most powerful engines will be produced at a rate of about one per every 12 hours by the end of the year in his quest to get a person on Mars. The massive production ramp-up was foreshadowed by a series of tweets posted early Monday morning, which began with a bold photo: an orange-tinted orb, with bold font reading, 'OCCUPY MARS.' But that orb was in fact a picture of an orange-tinted'blood-moon', not of Mars. As Twitter followers rushed to point out the blunder, Musk eventually segued into more substantive - if speculative - news, shedding light on a huge leap in the company's production output. In a recent tweet, SpaceX CEO Elon Musk made bold predictions about the production of the company's Raptor engines which could one day take the first human to the moon.
DUBAI, UNITED ARAB EMIRATES - U.S. Secretary of State Mike Pompeo held talks Monday with the Saudi king and crown prince about countering the military threat from Iran by building a broad, global coalition that includes Asian and European countries. Pompeo is likely to face a tough sell in Europe and Asia, particularly from those nations still committed to the 2015 nuclear deal with Iran that President Donald Trump repudiated last year. With tensions running high in the region after Iran shot down a U.S. surveillance drone on June 20 and Trump said he aborted a retaliatory strike, Iran's naval commander warned that his forces won't hesitate to down more U.S. drones that violate its airspace. The U.S. has been building up its military presence in the Persian Gulf. The U.S. announced additional sanctions Monday on Iran aimed at pressuring the Iranian leadership into talks.
An estimated 7 million drones will be flying in the skies by 2020; Claudia Cowan reports on the new technology being developed to keep airports safe. But some people either don't care or use drones to intentionally disrupt airport operations. Last December, drone sightings at London's Gatwick Airport forced a three-day shutdown, and canceled flights left thousands of stranded passengers scrambling. No one has been arrested in the case, and this past April, investigators said it could have been an inside job. In recent months, suspected or confirmed drone activity has grounded flights in Dubai, New Zealand, Israel, and at Newark Airport in New Jersey.
Facebook once teamed up with scientists at Cornell to conduct a now-infamous experiment on emotional contagion. Researchers randomly assigned 700,000 users to see on their News Feeds, for one week, a slight uptick in either positive or negative language or no change at all, to determine whether exposure to certain emotions could, in turn, cause a user to express certain emotions. The answer, as revealed in a 2014 paper, was yes: The emotions we see expressed online can change the emotions that we express, albeit slightly. Conversations about emotional contagion were quickly shelved, however, as the public disclosure of the study sparked an intense backlash against what many perceived to be an unjust and underhanded manipulation of people's feelings. Facebook would later apologize for fiddling with users' emotions and pledge to revise its internal review practices.
A new app from the former head of video-sharing app Vine hopes to repeat the success of the cult social network by making it easier to shoot and edit short clips. Trash hopes that its secret weapon will be "computational cinematography": the app, which entered closed beta on Monday, uses machine learning "to automate the un-fun parts of video editing", automatically processing video to cut together short clips with a consistent mood and feel. A similar approach, computational photography, has already radically changed smartphone photography, enabling features such as the Pixel's Night Sight and iPhone's Portrait Mode. Trash's co-founder, Hannah Donovan, who was Vine's last general manager before the service was shut down by its owner, Twitter, said she hoped the approach would lower the barrier of entry to video editing. "We're analysing the video for a bunch of different things," Donovan said.
Intratumor heterogeneity in lung cancer may influence outcomes. CT radiomics seeks to assess tumor features to provide detailed imaging features. However, CT radiomic features vary according to the reconstruction kernel used for image generation. To investigate the effect of different reconstruction kernels on radiomic features and assess whether image conversion using a convolutional neural network (CNN) could improve reproducibility of radiomic features between different kernels. In this retrospective analysis, patients underwent non–contrast material–enhanced and contrast material–enhanced axial chest CT with soft kernel (B30f) and sharp kernel (B50f) reconstruction using a single CT scanner from April to June 2017.
Python is a prevalent programming language in machine learning (ML) community. A lot of Python engineers and data scientists feel the lack of engineering practices like versioning large datasets and ML models, and the lack of reproducibility. This lack is particularly acute for engineers who just moved to ML space. We will discuss the current practices of organizing ML projects using traditional open-source toolset like Git and Git-LFS as well as this toolset limitation. Thereby motivation for developing new ML specific version control systems will be explained.
Artificial intelligence (AI) and its many related applications (ie, big data, deep analytics, machine learning) have entered medicine's "magic bullet" phase. Desperate for a solution for the never-ending challenges of cost, quality, equity, and access, a steady stream of books, articles, and corporate pronouncements makes it seem like health care is on the cusp of an "AI revolution," one that will finally result in high-value care. While AI has been responsible for some stunning advances, particularly in the area of visual pattern recognition,1-3 a major challenge will be in converting AI-derived predictions or recommendations into effective action.