Of all the A.I. tools to have emerged in recent years, very few have generated as much concern as deepfakes. A combination of "deep learning" and "fake," deepfake technology allows anyone to create images or videos in which photographic elements are convincingly superimposed onto other pictures. While some of the ways this tech has been showcased have been for entertainment (think superimposing Sylvester Stallone's face onto Arnie's body in Terminator 2), other use-cases have been more alarming. Deepfakes make possible everything from traumatizing and reputation-ruining "revenge porn" to misleading fake news. As a result, while a growing number of researchers have been working to make deepfake technology more realistic, others have been searching for ways to help us better distinguish between images and videos which are real and those that have been algorithmically doctored.

Facial recognition has received widespread application to assist in the identification of criminals in public spaces and crowds. For instance, Chinese officers succeeded in arresting a person from a sea of people inside a stadium, which without AI technology would have been nearly impossible to spot this person. China has installed numerous cameras in public spaces, which helps the police monitor citizens, catch citizens committing petty crimes such as jaywalking and helping identify criminals and arrest them. Some cities like London have experimented with the use of AI in railway stations to help in increasing surveillance, and maybe more nations will come up with the same for better law enforcement.

AI-related startups received record funding in 2019. This year marked the biggest year in funding for artificial intelligence ventures yet. According to a new report by CB Insights, the second quarter of 2019 saw a record of $7.4 billion invested in AI startups, with the majority going to transportation and health care-related companies. The data, which tracks capital received between 2013 and 2019, also shows that seed funding is still going strong. SEE ALSO: Why the AI Apocalypse Isn't the End of the World The number of unicorn-status AI startups has spiked in recent years, jumping from just two in 2016 to 11 in 2017.

Artificial Intelligence enabled automation is sweeping through society. In this century, it will have a species level impact on humanity. What form will that evolution take? This talk explores the nuances of humanity's future. Before attending, please read the Man and Superman: Human History Bifurcates blog series this talk is based on.

Three New Jersey teens brought home two international awards for their artificial intelligence robot, who competed at the International Robocup Junior Championship in Sydney, Australia earlier this month. The team -- made up of high school juniors Julian Lee of Livingston and Jeffrey Cheng from Bridgewater, and senior Alexander Lisenko, also of Bridgewater -- won the third place World Title for Individual Team Tournament, and the Judge's Award for Best Rescue Engineering Strategy in the Rescue Maze League. The trio belongs to Storming Robots, a New Jersey-based Robotics Learning Lab, and competed against teams of 14- to 19-year-olds from around the world in the July 4-9 contest. "The competition went by quick despite the many hours of work. It was an exciting but stressful experience, which was especially fun due to our great team dynamic," Lee said.

DER SPIEGEL: Mr. Schönbohm, the German government has decided not to exclude Huawei from building networks for the next generation of mobile communications. Do you not see any risk in allowing this controversial Chinese company from participating in the construction of the 5G network in Germany? Schönbohm: I think the risk is manageable. There are essentially two fears: First, espionage -- i.e. that data will be siphoned off involuntarily. But we can counter that with improved encryption.

Wine growers have a neat, if unusual, trick for making more flavorful wine--don't water the vines. Let the vines go dry right before harvest, and they will yield smaller grapes with more skin and less juice. Smaller grapes produce wine with a deeper color and more complex flavor. Trinchero Family Estates in Napa Valley, California wanted to make sure it was watering its grapes just the right amount, so they worked with Ceres Imaging to map their fields. Ceres used fixed-wing aircrafts to capture color, thermal, and infrared images of the vineyard, and they used artificial intelligence to analyze those images to see if the wine producer was overwatering its grapes.

The South Australian Government had recently launched a free autonomous vehicle trial that will deliver a first and last mile service between the Playford Alive Township and the Munno Para Train Station. As reported, the autonomous electric bus will run approximately every half hour on weekdays and will carry passengers from the Munno Para Railway Station to the Playford Alive Township, including stops at Mark Oliphant College and the Stretton Centre. The free autonomous shuttle bus service will include a morning and afternoon service window, with passengers collected from designated pick up points on the route. The Munno Para service is phase two of the Playford Connect autonomous bus trial. It follows phase one, which provided a free park and ride service from the Lionsgate Carpark through to the Lyell McEwin Hospital in Elizabeth Vale from October 2018 to June 2019.

Surprisingly, I got a huge response from many top data scientists from different industries who all shared their thoughts and advice -- which I found very interesting and practical. To learn more about the main differentiators between a good data scientist and a rockstar data scientist, I kept searching on the internet… Until I found this article on KDnuggets. So I distilled all the information and listed down the skills to become a rockstar data scientist. Practically speaking, it's impossible for a data scientist to have all the skills listed below. But these skills are what make a rockstar data scientist different from a good data scientist, in my opinion. By the end of this article, I hope you'll find these skills helpful throughout your career path as a data scientist.

Are technology companies running too fast into the future and creating things that could potentially wreak havoc on humankind? That question has been swirling around in my head ever since I saw the enthralling science-fiction film "Ex Machina." The movie offers a clever version of the robots versus humans narrative. But what makes "Ex Machina" different from the usual special-effects blockbuster is the ethical questions it poses. Foremost among them is something that most techies don't seem to want to answer: Who is making sure that all of this innovation does not go drastically wrong?