State Archives and Records NSW will pilot machine learning technology to determine whether it can be used to automate some records classification and disposal activities. The records management authority said in a blog post that it plans to run pilots "to assess the technology's capabilities in sentencing unstructured data". Sentencing is a process used to identify and classify documents, usually for the purpose of determining which ones can be safely disposed of. The authority said it would be "seeking partnerships for an agency pilot and will also run an internal pilot using in-house data". The internal pilot will use machine learning "to apply GA28 to a corpus of digital records which have already been sentenced manually" - presumably to determine how accurate the algorithm is compared to a traditional methods.

Today, machine learning has come of age as it seeks to create predictive models and algorithms and gives computers the ability to carry out tasks without being explicitly programmed. Examples of Machine Learning we use on a day-to-day basis are Google search engines, recommendations from Amazon, Netflix and YouTube, and even suggested friends on Facebook. However, machine learning is also being called out as the saviour of cybersecurity, with companies incorporating it into their technologies to predict, prevent and defeat the next major cyber-attack. With internet crime growing at the rate it is, we need all the tools in our armory to stand any chance of keeping pace. According to the Australian Competition & Consumer Commission, security scams have cost Australians over $950 000 to date in 2017, with hacking scams hitting the hardest.

For an example of the transformative role drones -- or unmanned aerial vehicles, as they're known in the industry -- will play across industries, just consider, said Michael Huerta, administrator of the Federal Aviation Administration, what happened after Hurricane Harvey struck Texas last week. Looking to establish accountability across disparate project teams? Trying to automate processes or allow for lean methodology support? Hoping to enable business consequence modeling or real-time reporting? If you answered'yes' to any of these questions, then you need to download this comprehensive, 68-page PDF guide on selecting, managing, and tracking IT projects for superior service delivery. You forgot to provide an Email Address.

Most popular word embedding techniques involve implicit or explicit factorization of a word co-occurrence based matrix into low rank factors. In this paper, we aim to generalize this trend by using numerical methods to factor higher-order word co-occurrence based arrays, or \textit{tensors}. We present four word embeddings using tensor factorization and analyze their advantages and disadvantages. One of our main contributions is a novel joint symmetric tensor factorization technique related to the idea of coupled tensor factorization. We show that embeddings based on tensor factorization can be used to discern the various meanings of polysemous words without being explicitly trained to do so, and motivate the intuition behind why this works in a way that doesn't with existing methods. We also modify an existing word embedding evaluation metric known as Outlier Detection [Camacho-Collados and Navigli, 2016] to evaluate the quality of the order-$N$ relations that a word embedding captures, and show that tensor-based methods outperform existing matrix-based methods at this task. Experimentally, we show that all of our word embeddings either outperform or are competitive with state-of-the-art baselines commonly used today on a variety of recent datasets. Suggested applications of tensor factorization-based word embeddings are given, and all source code and pre-trained vectors are publicly available online.

The era of artificial intelligence is upon us, though there's plenty of debate over how AI should be defined much less whether we should start worrying about an apocalyptic robot uprising. The latter issue recently ignited a highly publicized dispute between Elon Musk and Mark Zuckerberg, who argued that it was irresponsible to "try to drum up these doomsday scenarios". In the near-term however, it seems more than likely that AI will be weaponized by hackers in criminal organizations and governments to enhance now-familiar forms of cyberattacks like identity theft and DDoS attacks. A recent survey has found that a majority of cybersecurity professionals believe that artificial intelligence will be used to power cyberattacks in the coming year. Cybersecurity firm Cylance conducted the survey at this year's Black Hat USA conference and found that 62 percent of respondents believe that "there is high possibility that AI could be used by hackers for offensive purposes."

Big data can mean big business. But as Texas copes with the destruction of Hurricane Harvey, which ravaged the state late last month, and with Irma barreling over the Caribbean toward Florida, and Mexico shaken by the most powerful earthquake in 100 years, can mining vast amounts of data also help save lives from the fury of natural disasters? Find and rescue victims from rubble? Governments are looking to the same sophisticated analytics techniques that are predicting -- with fast-improving accuracy -- the paths and destruction potential of increasingly fearsome storms to better prepare for and tend to their constituents' needs during calamities. But whether such data-driven decision-making is actually making a difference is, in 2017, an open question.

One of the biggest problems we face today is the impact we're having on the natural world. Covering 70% of our planet, we still know so little about our oceans and how we can protect them from further destruction. We can see the devastation around us like deforestation and mass urbanisation etc., but the destruction of the oceans is so easily ignored as it remains largely unseen beneath the waves. It's so vital to keep our oceans healthy; they are home to millions of species of plant and animal, provide food, financial resources, and even produce half of the oxygen we breathe. Climate change and coral bleaching, pollution, and over fishing are just a few issues that need urgent attention in order to save our oceans.

This Tuesday Apple unveiled a new line of phones to much fanfare, but one feature immediately fell under scrutiny: FaceID, a tool that would use facial recognition to identify individuals and unlock their phones. Jake Laperruque (@jakelaperruque) is senior counsel for privacy and security issues at The Constitution Project. He previously served as a fellow for New America's Open Technology Institute and The Center for Democracy and Technology. Unsurprisingly, this raised major anxiety about consumer privacy given its profound ramifications: Retailers already crave facial recognition to monitor consumers, and without legally binding terms, Apple could use FaceID to track consumer patterns at its stores, or develop and sell data to others. It's also possible that police would be able to more easily unlock phones without consent by simply holding an individual's phone up to his or her face. But FaceID should create fear about another form of government surveillance: mass scans to identify individuals based on face profiles.

New drone video out of Florida captured an aerial view of the devastation wrought by Hurricane Irma in the Sunshine State. The video, taken by Travis Long and posted by the Miami Herald Wednesday, showed Irma's path of destruction in Manatee County, south of Tampa on the west coast. The video showed enormous trees ripped out of the ground by their roots, roofs torn clean off homes and overturned and sunken boats. At least one person could be seen in the video working to restore a home amid the wreckage. President Donald Trump headed down to Florida Thursday to determine the extent of the damage left by the record-breaking hurricane.

A lot of people quickly raised concerns about privacy and security the moment Apple revealed iPhone X and its Face ID feature. Edward Snowden, for instance, thinks it normalizes face scanning, "a tech certain to be abused." Now, US Senator Al Franken is pressing the tech titan for answers, penning a letter addressed to Apple chief Tim Cook with a list of questions concerning the technology's "eventual uses that may not be contemplated by" its customers. While Cupertino already said during its keynote that Face ID details will be saved on the phone itself, Franken wants to know whether it's currently possible for Apple or a third party to access (and then save) that data either remotely or through physical access to one's iPhone. He wants to know all the steps Apple has taken to ensure the tech can't be fooled by masks and photographs.