Imagine you live in a smart city that knows your face and follows your every move – the places you go, the people you see, and all of the things you do along the way. Over time, autonomous artificial intelligence (AI) builds a profile that reports on how likely you are to commit a crime. When that risk is high, the police take pre-emptive action. Welcome to hyper-surveillance and the next generation of predictive policing. Both India and China are currently implementing this level of surveillance to bring down crime rates and detect terrorists before they strike.

Advances in brain scanning and intervention technologies are transforming our ability to observe, explain, and influence human thought and behaviour. However, many factors beyond the brain – factors targeted by different emerging technologies – also influence human thought and behaviour. Sequencing the human genome and gene-editing technologies like CRISPR Cas-9 offer novel ways to explain and influence human thought and behaviour. Analysis of data about our offline and online lives (e.g. from fitness trackers, how we interact with our smartphone apps, and our social media posts and profiles) also provide striking insights into our psychology. Such intimate information can be used to predict and influence our behaviour, including through bespoke advertising for goods and services that more effectively exploits our psychology and political campaigns that sway election results.

Deep ocean robotics is not generally an area where we expect to see much in the way of significant innovation. When we do write about submersible robots, they're usually confined to very near-surface operations. This isn't a total surprise: It seems like the only people who really worry about what's going on in the deep ocean (meaning hundreds or thousands of meters beneath the surface) are the military, the occasional scientist, and the oil and gas industry. Robots are important to these folks, even critical in some cases, but the technology has been more or less stagnant for decades, which is why we don't write about it very frequently. To be fair, there are some very good reasons why it's hard to innovate when it comes to submersible robotics.

Sharks and a saltwater crocodile went on a feeding frenzy about a mile off the coast of Western Australia. Sharks and a saltwater crocodile went on a feeding frenzy about a mile off the coast of Western Australia -- and the "rare" event was caught on tape. A drone captured the predators feasting side-by-side on a 16-foot hump-back whale carcass floating near a sandbar off Montgomery Reef. It was the first time sharks and a croc had been documented foraging together. Dr. Austin Gallagher, chief scientist and CEO of Beneath the Waves, a Washington, D.C.-based non-profit organization working to protect the world's oceans, says he's been studying sharks for more than a decade but he'd never seen anything quite like this.

A lot of companies like to claim their offices are personalized to their staff, but at Ansarada they've taken the idea one step further: You'll need your fingerprint at the ready to get through the door. Biometric ID passes are just one of several high-tech features built into the Australian data firm's Sydney headquarters to reflect its innovative approach and inspire its team of 118 technology buffs. "Proxy cards and all that, that's old school," Sam Riley, CEO of Ansarada, told CNBC's "Office Envy" during a tour of its 8,460-square-foot work space. Ansarada is what's known as a virtual data room company, meaning it provides an online platform -- or cloud -- for companies to store information during major transactions like fundraising and mergers and acquisitions.

Kiwi businesses need to get on board with artificial intelligence - despite mass adoption of the technology being years away. AI is expected to increase productivity and skilled workforce, according to a leading national report commissioned by the AI Forum New Zealand, to be released on May 2. New Zealand AI Forum executive director Ben Reid says artificial intelligence could soon become part of our daily working lives in a similar way as the internet or electricity has. Both of those changes were transformational to the way that the economy and businesses operate," Reid said. "If AI adoption follows a similar pattern to those other major technologies, then it will be a similar number of years in terms of business uptake, so between 20 and 40 years for mass adoption of AI throughout all businesses and all society." AI and machine learning will be front and centre at the next PwC Herald Talks event in Auckland and Wellington.

Most people are not very familiar with the concept of artificial intelligence (AI). As an illustration, when 1,500 senior business leaders in the United States in 2017 were asked about AI, only 17 percent said they were familiar with it.1 A number of them were not sure what it was or how it would affect their particular companies. They understood there was considerable potential for altering business processes, but were not clear how AI could be deployed within their own organizations. Despite its widespread lack of familiarity, AI is a technology that is transforming every walk of life. It is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decisionmaking. Our hope through this comprehensive overview is to explain AI to an audience of policymakers, opinion leaders, and interested observers, and demonstrate how AI already is altering the world and raising important questions for society, the economy, and governance. In this paper, we discuss novel applications in finance, national security, health care, criminal justice, transportation, and smart cities, and address issues such as data access problems, algorithmic bias, AI ethics and transparency, and legal liability for AI decisions. We contrast the regulatory approaches of the U.S. and European Union, and close by making a number of recommendations for getting the most out of AI while still protecting important human values.2 Although there is no uniformly agreed upon definition, AI generally is thought to refer to "machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment and intention."3 According to researchers Shubhendu and Vijay, these software systems "make decisions which normally require [a] human level of expertise" and help people anticipate problems or deal with issues as they come up.4 As such, they operate in an intentional, intelligent, and adaptive manner. Artificial intelligence algorithms are designed to make decisions, often using real-time data. They are unlike passive machines that are capable only of mechanical or predetermined responses. Using sensors, digital data, or remote inputs, they combine information from a variety of different sources, analyze the material instantly, and act on the insights derived from those data. With massive improvements in storage systems, processing speeds, and analytic techniques, they are capable of tremendous sophistication in analysis and decisionmaking.

Killer robots, tanks, planes, and ships could theoretically fight wars for states, without any human intervention. They will be "weapons of terror, used by terrorists and rogue states against civilian populations" and will follow any orders however evil," according to Toby Walsh, a professor from the University of New South Wales, Australia. He added: "These will be weapons of mass destruction. One programmer and a 3D printer can do what previously took an army of people. "They will industrialise war, changing the speed and duration of how we can fight. They will be able to kill 24-7 and they will kill faster than humans can act to defend themselves."

Apache Thrift The Thrift stack is a common class hierarchy implemented in each language that abstracts out the tricky details of protocol encoding and network communication 26. Chukwa A data collection system for monitoring large distributed systems; Provides flexible/powerful toolkit to display, monitor, and analyze results; Architecture: Agents - run on each machine and emit data; Collectors - receive data from the agent and write it to stable storage; MapReduce jobs - parsing and archiving the data; Hadoop Infrastructure Care Center - a web-portal style interface.

The term "machine learning" might not mean much to you. You might imagine a computer playing chess, calculating the multitude of moves and the possible countermoves. But, when you hear the term "artificial intelligence" or "AI," however, it's more likely you have visions of Skynet and the rise of our inevitable robot overlords. But, the truth of artificial intelligence -- and particularly machine learning -- is far less sinister, and it's actually not something of the far-off future. It's here today, and it's shaping and simplifying the way we live, work, travel and communicate.