A drone is flown during a property inspection following Hurricane Harvey in Houston. The mass destruction brought on by Harvey has been a seminal moment for drone operators, proving that they can effectively map flooding, locate people in need of rescue and verify damage to speed insurance claims. The mass destruction brought on by Harvey has been a seminal moment for drone operators, proving that they can effectively map flooding, locate people in need of rescue and verify damage to speed insurance claims. According to Kate Harris, a spokesperson for Verizon, the company began using drones last October during Hurricane Matthew to inspect cell towers in North Carolina.
Assistants falling for the ploy included Amazon Alexa, Apple's Siri, Google Now, Samsung S Voice, Microsoft Cortana and Huawei HiVoice, as well as some voice control systems used in cars. When a voice assistant hears these sounds, they still recognise them as legitimate commands, even though they are imperceptible to the human ear. The owner's voice had to be surreptitiously recorded for playback as Apple's system recognises the speaker. To secure voice assistants in the future, sounds outside the human voice range could be suppressed or machine learning algorithms could listen out for similar style attacks, Vaidya says.
The bill, called the SELF DRIVE Act, lays out a basic federal framework for autonomous vehicle regulation, signaling that federal lawmakers are finally ready to think seriously about self-driving cars and what they mean for the future of the country. It officially gives the National Highway Traffic Safety Administration power to regulate vehicle design, construction, and performance--the way it does with, well, normal cars. Finally, the legislation makes it a lot easier for self-driving cars to hit the road. Today, Federal Motor Vehicle Safety Standards (FMVSS, for those who are hip with it) govern how vehicles are designed.
Before the devastation throughout southern Texas, lawmakers and trade groups representing drone manufacturers specifically urged the FAA to adopt policies providing swift regulatory exemptions in the event of emergency applications. Since the FAA began clearing the way for unmanned aircraft around Houston, people familiar with the details said at least one company has received the green light to survey coastal damage using drones operating beyond the sight of ground-based pilots. Despite FAA flexibility, drone industry groups have called for further easing of rules. All drone operations were prohibited without specific FAA approval, and the FAA explicitly warned that "flying an unauthorized drone could interfere" with official rescue and recovery efforts.
One response to the call by experts in robotics and artificial intelligence for an ban on "killer robots" ("lethal autonomous weapons systems" or Laws in the language of international treaties) is to say: shouldn't you have thought about that sooner? There are shades of science-fictional preconceptions in a 2012 report on killer robots by Human Rights Watch. Besides, there's a continuum between drone war, soldier enhancement technologies and Laws that can't be broken down into "man versus machine". By all means let's try to curb our worst impulses to beat ploughshares into swords, but telling an international arms trade that they can't make killer robots is like telling soft-drinks manufacturers that they can't make orangeade.
Before autonomous trucks and taxis hit the road, manufacturers will need to solve problems far more complex than collision avoidance and navigation (see "10 Breakthrough Technologies 2017: Self-Driving Trucks"). These vehicles will have to anticipate and defend against a full spectrum of malicious attackers wielding both traditional cyberattacks and a new generation of attacks based on so-called adversarial machine learning (see "AI Fight Club Could Help Save Us from a Future of Super-Smart Cyberattacks"). When hackers demonstrated that vehicles on the roads were vulnerable to several specific security threats, automakers responded by recalling and upgrading the firmware of millions of cars. The computer vision and collision avoidance systems under development for autonomous vehicles rely on complex machine-learning algorithms that are not well understood, even by the companies that rely on them (see "The Dark Secret at the Heart of AI").
Hearing plays an essential role in how you navigate the world, and, so far, most autonomous cars can't hear. It recently spent a day testing the system with emergency vehicles from the Chandler, Arizona, police and fire departments. Police cars, ambulances, fire trucks, and even unmarked cop cars chased, passed, and led the Waymo vans through the day and into the night. Sensors aboard the vans recorded vast quantities of data that will help create a database of all the sounds emergency vehicles make, so in the future, Waymo's driverless cars will know how to respond.
On August 3, sequencing company Veritas Genomics bought one of the most influential: seven-year old Curoverse. In a step forward, the company also hopes to use things like natural language processing and deep learning to help customers query their genetic data on demand. He points to a 2013 study that used polygenic testing to predict heart disease using the Framingham Heart Study data--about as good as you can get, when it comes to health data and heart disease. "They authors showed that yes, given polygenic risk score, and blood levels, and lipid levels, and family history, you can predict within 10 years if someone will develop heart disease," says Butte.
The Darwin Project, an alliance between oceanographers and microbiologists in the MIT Department of Earth, Atmospheric and Planetary Sciences (EAPS) and the Parsons Lab in the MIT Department of Civil and Environmental Engineering, was conceived as an initiative to "advance the development and application of novel models of marine microbes and microbial communities, identifying the relationships of individuals and communities to their environment, connecting cellular-scale processes to global microbial community structure" with the goal of coupling "state of the art physical models of global ocean circulation with biogeochemistry and genome-informed models of microbial processes." The boost in computational infrastructure the award provides for will advance several linked areas of research, including the capacity to model marine microbial systems in more detail, enhanced fidelity of the modeled fluid dynamical environment, support for state of the art data analytics including machine learning techniques, and accelerating and extending genomic data processing capabilities. As an initiative to advance our understanding of the biology, ecology, and biogeochemistry of microbial processes that dominate Earth's largest biome -- the global ocean -- SCOPE seeks to measure, model, and conduct experiments at a model ecosystem site located 100 km north of the Hawaiian island of Oahu that is representative of a large portion of the North Pacific Ocean. Steady growth in available large-scale metagenomic and single-cell genomic data resulting from genetics data activities in the Chisholm Lab are also driving additional computational processing resource needs.