CAPE CANAVERAL, FL––It's been almost three months since SpaceX sent a Falcon 9 roaring on its second flight through the skies off Florida's space coast. On a Thursday in March, the spaceflight company became the first to recover, refurbish, and relaunch an orbital-class rocket. The event marked a watershed moment for an aerospace industry that has been disposing these complex and insanely expensive launch vehicles for over 60 years. Friday, SpaceX will attempt the feat again. SpaceX plans to launch another recovered booster from the history-worn Pad 39A at Kennedy Space Center--what CEO Elon Musk calls the'Times Square' of launch pad, thanks to its service during the Apollo and Space Shuttle era.

Going through airport security is a universally painful experience. And despite being slow and invasive, the TSA doesn't have a great record at catching threats. With the help of the Kaggle data science community, the Department of Homeland Security (DHS) is hosting an online competition to build machine learning-powered tools that can augment agents, ideally making the entire system simultaneously more accurate and efficient. Kaggle, acquired by Google earlier this year, regularly hosts online competitions where data scientists compete for money by developing novel approaches to complex machine learning problems. Today's competition to improve threat recognition algorithms will be Kaggle's third launch this year featuring more than a million dollars in prize money.

During the jungle primary they identified him with unpopular party leader Nancy Pelosi, and portrayed him as just another liberal. The Republicans also used Ossoff's own TV ad against him to highlight the fact that he did not support repealing Obamacare, and remind voters that Ossoff does not live in the district. Also during the jungle primary – Republicans used residents of the district to accuse Ossoff of lying about his credentials, and they again reinforced the branding of him as a Pelosi liberal who'd raise taxes and weaken the military. Straight after the primary, they ran a contrast ad -- framing Ossoff as a carpetbagging Hollywood/Pelosi liberal and Handel as a "proven fighter for Georgia." National security played a surprisingly heavy role in the messaging given Ossoff had never taken a vote that could be used against him.

As with most practical AI, the experiment will use machine learning algorithms to teach the machine to react to situations politely: for instance, saying thank you when it is given something. It will then derive new manners not directly taught to it via deep learning.

Commercial supersonic air travel could return in just half a decade after a Richard Branson-backed company aiming to replace the concord announced it will begin test flights next year. Boom Supersonic has said initial test flights for its 1,451mph (2,330kph) aircraft, nicknamed the'baby boom', will begin by the end of 2018, with both subsonic and supersonic tests taking place in the US. Supersonic flight tests will be conducted near Edwards Air Force Base in Southern California in partnership with Virgin Galactic's The Spaceship Company. If the firm's full-sized, 55-seater aircraft is approved, the first passengers could be making a supersonic journey across the Atlantic by 2023 at a top speed more than 100mph (160km/h) faster than the infamous Concorde. Boom Supersonic has said initial test flights for its 1,451mph (2,330kph) aircraft, nicknamed the'baby boom', will begin by the end of 2018, with both subsonic and supersonic tests taking place in the US.

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With the help of the Kaggle data science community, the Department of Homeland Security (DHS) is hosting an online competition to build machine learning-powered tools that can augment agents, ideally making the entire system simultaneously more accurate and efficient. Kaggle, acquired by Google earlier this year, regularly hosts online competitions where data scientists compete for money by developing novel approaches to complex machine learning problems. The TSA is making its data set of images available to competitors so they can train on images of people carrying weapons. Thankfully, Google, Facebook and others are heavily investing in lighter versions of machine learning frameworks, optimized to run locally, at the edge (without internet).

Like many artificial intelligence companies in Canada, PeopleAnalytics.ai was happy to see the federal government's launch of its Pan-Canadian Artificial lntelligence Strategy for research and talent as part of the federal budget this year. The $125-million that the Liberals are committing to the project, to be administered through the Canadian Institute For Advanced Research (CIFAR), is expected to help to attract and retain top academic talent in this country. With the market for AI-related ideas and products expected to reach $47-billion by 2020, according to CIFAR, the sector has already attracted major investment from Facebook and Google, among others. For PeopleAnalytics.ai, based out of Toronto's MaRS Discovery District, Canada is at a crossroads where it has the ability to define exactly how it wants to mould its focus on AI. Mark Chaikelson, below, vice-president of product for PeopleAnalytics.ai, says the success of the government's plan, particularly in the AI clusters in Montreal, Toronto-Waterloo and Edmonton, will come down to three things: capital, customers and talent.

As a kid, I saw the 1968 version of Planet of the Apes. As a future primatologist, I was mesmerized. Years later I discovered an anecdote about its filming: At lunchtime, the people playing chimps and those playing gorillas ate in separate groups. It's been said, "There are two kinds of people in the world: those who divide the world into two kinds of people and those who don't." And it can be vastly consequential when people are divided into Us and Them, ingroup and outgroup, "the people" (i.e., our kind) and the Others. The core of Us/Them-ing is emotional and automatic. Humans universally make Us/Them dichotomies along lines of race, ethnicity, gender, language group, religion, age, socioeconomic status, and so on. We do so with remarkable speed and neurobiological efficiency; have complex taxonomies and classifications of ways in which we denigrate Thems; do so with a versatility that ranges from the minutest of microaggression to bloodbaths of savagery; and regularly decide what is inferior about Them based on pure emotion, followed by primitive rationalizations that we mistake for rationality. But crucially, there is room for optimism. Much of that is grounded in something definedly human, which is that we all carry multiple Us/Them divisions in our heads. A Them in one case can be an Us in another, and it can only take an instant for that identity to flip.

Federal agencies are a step closer to automating some of their common customer service processes using artificial intelligence. The General Services Administration recently wrapped a pilot that walked federal agencies through the process of building chatbots and other intelligent personal assistants similar to Apple's Siri and Amazon's Alexa. Graduates of that pilot have developed some basic prototypes--a single chatbot that lets users access Small Business Administration licenses, Internal Revenue Service tax credits, Forest Service park permits, and Health and Human Services Department benefits, for one. But prototypes weren't the point of the pilot, GSA's Emerging Citizen Technology Office lead Justin Herman told Nextgov--instead, it was to help agencies understand what they'd need before they can fully deploy intelligent personal assistants. One finding, Herman said, was that agencies need to assess their cloud services, as chatbots and voice-controlled virtual assistants would need to pull information from the internet.