Recycling facilities use robotic sorting stations and object-recognition technology to identify and put garbage in its proper place. Filled with intricate mazes of high-speed conveyor belts carrying yesterday's garbage, high-tech recycling centers use sophisticated sensors to sort plastic from paper from aluminum. While this technology may streamline sorting, it's not smart or nimble enough to finish the job. Behind the scenes, recycling workers continue to sort the materials, making sure cereal boxes don't mix with soda cans. But the future of smart recycling is looking brighter.

NASA's Frontier Development Lab (FDL), a public-private research institute operated jointly by the space agency's Ames Research Center and the SETI Institute, announced it will use artificial intelligence to study methods of protecting the Earth from potentially hazardous asteroids and comets. The announcement was made on Friday, June 30, designated in 2014 as International Asteroid Day, an annual event that addresses potential threats from Near Earth Objects (NEOs). June 30 was chosen because it is the anniversary of the 1908 Tunguska impact, when an asteroid estimated to have been 120 feet wide exploded over the Stony Tunguska River in Siberia. The annual commemoration is the brainchild of astrophysicist and Queen lead guitarist Brian May and film director Grigorij Richters. Several years ago, Richters directed 51 Degrees North, a film depicting a fictional asteroid strike in London. For this year's event, FDL assembled a research team to discuss the ways artificial intelligence can assist in planetary defense.

The logic around artificial intelligence is fuzzy. Some people might argue that the heuristic algorithms used in antivirus to recognize potential threats are artificial intelligence. Others got a glimmer of hope -- outside of the security field -- with the landmark success of AlphaGo. In 2016, the DeepMind software won four out of five matches of the complex Chinese Go board game when it out-strategized top professional player Lee Sedol. The win astounded viewers and saved Alphabet Group, which acquired the London-based DeepMind in 2014, a million dollars of prize money.

The Department of Defense is consuming more and more chips and lines of code, which translates to more supply-chain vulnerability. Officials and industry leaders argue big data and artificial intelligence will be critical tools to manage that risk going forward. Speaking at an Intelligence and National Security Alliance and Defense One event, panelists described a rapidly expanding network of suppliers for weapons and components. For example, Northrup Grumman alone has some 5,000 suppliers in just one sector of its business. "You've got those 5,000, they in turn have additional suppliers, so you think about all of the potential points of entry ... in terms of hardware, software, design, delivery," said John Jordan, director of compliance for global supply chain for Northrop's Mission Systems Sector.

There have been recriminations about Secretary Clinton's use of a personal email account and server while she was Secretary of State, but there hasn't been enough examination of why Shadow IT is a bad thing. When an employee uses personal IT resources to do their job, that activity and data is out of view of the employer, in the so-called "shadows." An employer provides computer resources to employees and has a responsibility to maintain the systems, keep track of company data, back it up, secure it, and secure the network and devices. When employees use their personal computers and email accounts for work, it creates security risks. The employer can't secure systems or data it doesn't know about, and individuals might have worse cybersecurity practices than the employer.

There is a lot of hype and plenty of fear around artificial intelligence and its impact on the future of healthcare. There are many signs pointing towards the fact that AI will completely move the world of medicine. As deep learning algorithms and narrow AI started to buzz especially around the field of medical imaging, many radiologists went into panic mode. In his presentation at the GPU Tech Conference in San Jose in May 2017, Curtis Langlotz, Professor of Radiology and Biomedical Informatics at Stanford University, mentioned how he received an e-mail from one of his students saying he was thinking about going into radiology but does not know whether it is a viable profession anymore. But the assumption that the radiologist profession is dying, is just plain wrong.

Oddly enough, tattoos are now playing a significant role in modern law enforcement–thanks largely to the advent of computer vision. This month, an investigation by the Electronic Frontier Foundation revealed that the FBI is actually investing in research that can identify and semantically analyze tattoos en masse. To create a tool for the police that can not only recognize tattoos but analyze their meaning to create a network of contextual links between potentially millions of tattoos. One commonly cited scenario for how it might be used: If a surveillance camera didn't record a perpetrator's face, but it did catch a part of his or her tattoo, this technology could theoretically link that tattoo to a list of possible suspects. Or, investigators could use it to search for other examples and context about a particularly inscrutable tattoo. But questions about whether such a database impinges upon freedom of speech–and the rights of the prisoners whose photos populate it–are rife.

In any event, machine learning has already changed the rules of the IoT cybersecurity game, says Thomas Dinsmore, director of product marketing for data science at Cloudera, making it look more like a chess match that pits machine against machine. "For instance, segmenting vulnerable or potentially vulnerable IoT or other devices into a separate network, or limiting their Internet access, thereby creating hurdles for hackers and machines attempting to attack the network." At present, security operations are beginning to make greater use of machine-learning-based software to identify vulnerabilities, says Shaun Cooley, CTO of IoT and Industries at Cisco. "Again, it's the human element that is critical here--whether it is humans being lax when training machine learning cybersecurity algorithms, losing control over powerful cyberweapons, humans corrupting machine learning through malicious inputs undetectable by human eyes, or humans believing that a given technology will make them safe," McCleary says.

The SpaceX Dragon capsule that made history by becoming the first recycled spacecraft to fly two missions was recovered on Tuesday. The capsule took supplies to the International Space Station and splashed down as planned in the Pacific Ocean on Monday. SpaceX announced on Twitter that the Dragon hit the water off the California coast shortly after 5am Monday. After being released by the space station's robotic arm, the capsule completed a 5½-hour journey back to Earth, part of which was captured by NASA astronaut Jack Fischer. NASA astronaut Jack Fischer photographed the SpaceX Dragon capsule as it reentered Earth's atmosphere before splashing down in the Pacific Ocean west of Baja California at 8:12 a.m. EDT, July 3, 2017.

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