When on the subject of successful leaders, it is evident that the how and why of success help derive inspiration. Forbes has come up with its second list of game changers--those who are not happy with the status quo and are transforming their industries by making a difference to the lives of their consumers. The youngest game changers are two contenders--Evan Spiegel, 26-year-old CEO of Snap, and Stripe cofounders John (26) and Patrick Collison (28). The oldest is 75–year-old Christo Wiese, chairman of South Africa-based retail company Steinhoff. These are the innovative trailblazers who are redefining and reimagining the lives of people, and taking the requisite action to bring that vision to life. Forbes embarked on this initiative to acknowledge not just typical corporate achievements such as profits and growth, which are largely limited to employees and shareholders, but also the flair for making a true difference to the larger society.

Apple recently updated online availability of 15-inch MacBook Pro on its website to June 6-8 to coincide with the Worldwide Developers Conference next week, MacRumors first spotted. The move comes after a Bloomberg report said Apple plans to announce its new laptop lineup at WWDC. Apple will reportedly announce new versions of the 12-inch MacBook and MacBook Pro at the event. The company is also said to be considering updating the MacBook Air, which hasn't been upgraded in years. In-store pickup of the 15-inch MacBook Pro is available for June 8.

WWE's next pay-per-view is set for Sunday night in Baltimore with Extreme Rules 2017. It will exclusively feature wrestlers from the "Monday Night Raw" roster. Six matches are on the Extreme Rules card, and the main event will determine the No.1 contender for Brock Lesnar's WWE Universal Championship. Below are predictions for every match at the event. Reigns is really the only superstar that has no chance in this match. The winner is expected to face Lesnar at the Great Balls of Fire PPV on July 9, and Reigns vs. Lesnar would only happen at SummerSlam or WrestleMania.

PREDICTING HOW artificial intelligence technology will evolve in the following ten or 20 years, or even beyond, is very difficult to say the least. However, certain is the fact that there is much to be gained to go around for everyone. It is estimated that by the year 2018, robots will literally be supervising more than three million of us at work; and by 2020, smart machines will become a major investment priority amongst at least 30% of all CIOs. Right now, many different fields, spanning from customer service to journalism, are already being set aside by increasingly able AI that can replicate human abilities and experience. Already before our eyes is an aspect that we once thought only belonged in future technology.

The recently proposed DeGroot-Friedkin model describes the dynamical evolution of individual social power in a social network that holds opinion discussions on a sequence of different issues. This paper revisits that model, and uses nonlinear contraction analysis, among other tools, to establish several novel results. First, we show that for a social network with constant topology, each individual's social power converges to its equilibrium value exponentially fast, whereas previous results only concluded asymptotic convergence. Second, when the network topology is dynamic (i.e., the relative interaction matrix may change between any two successive issues), we show that each individual exponentially forgets its initial social power. Specifically, individual social power is dependent only on the dynamic network topology, and initial (or perceived) social power is forgotten as a result of sequential opinion discussion. Last, we provide an explicit upper bound on an individual's social power as the number of issues discussed tends to infinity; this bound depends only on the network topology. Simulations are provided to illustrate our results.

Mutants like the X-Men might be much more likely to emerge in a human society living on another planet than here are on Earth, because radiation can really mess with evolution. Space agencies and private companies like Elon Musk's SpaceX are trying to make space travel more sustainable, learn about how the human body responds to long-term microgravity conditions and isolation and figure out how to grow crops in outer space, among other exercises -- all as people set their sights on places like Mars to explore and colonize. But what will happen to us once we get there? It's possible the first settlers will evolve into a new human species entirely, given enough time. On Earth, that amount of time is somewhere between thousands and millions of years, according to anthropologist John Hawks, a professor at the University of Wisconsin-Madison.

As AI algorithms that can impersonate the human voice get better and better, it might not be long before you pick up the phone and genuinely can't tell if you're talking to a human or a machine that's been trained to sound like one. In the far future, you might not be able to tell the difference in person, either. In this vision of a future filled with computers pretending to be people, you might need a device like the Anti-AI AI. Designed as a fun proof-of-concept by Australian firm DT, the device uses essentially the same algorithms that impersonate human voices to detect if you're being spoken to by a computer. If the Anti-AI AI clocks some synthesized vocal patterns, it uses a thermoelectric plate to literally send a chill down your spine.

Modeling causal dependencies often demands cycles at a coarse-grained temporal scale. If Bayesian networks are to be used for modeling uncertainties, cycles are eliminated with dynamic Bayesian networks, spreading indirect dependencies over time and enforcing an infinitesimal resolution of time. Without a ``causal design,'' i.e., without anticipating indirect influences appropriately in time, we argue that such networks return spurious results. By identifying activator random variables, we propose activator dynamic Bayesian networks (ADBNs) which are able to rapidly adapt to contexts under a causal use of time, anticipating indirect influences on a solid mathematical basis using familiar Bayesian network semantics. ADBNs are well-defined dynamic probabilistic graphical models allowing one to model cyclic dependencies from local and causal perspectives while preserving a classical, familiar calculus and classically known algorithms, without introducing any overhead in modeling or inference.

At Soul Machines, a company that uses artificial intelligence to create lifelike avatars that respond to human emotion, a fair amount of their work could be considered unsettling to the average person who fears the coming takeover by our AI-robot overlords. It's a company that pretty much lives in the uncanny valley, that space between fake and real that can creep people out, but that's not usually what happens when people meet BabyX, said Soul Machines founder Mark Sagar. Instead, he says, when the baby begins to whimper or cry, some respond in human ways, demonstrating what appears to be sympathy similar to the kind they may lavish on a human baby. "I'll probably get about 10 or 15 percent of people respond with'that's creepy,' and others it doesn't bother them at all. Ultimately it's about creating an emotional connection and then people jump right into that," he said. To see which of these two camps you fall into, watch the video below.

Business Insider Australia is the Australian edition of the world's fastest-growing business news website, Business Insider. Australia's pioneering bionic ear company, Cochlear, plans to use artificial intelligence to more accurately implant and calibrate its devices. Cochlear today announced an exclusive licensing and development agreement with Otoconsult for its artificial intelligence fitting assistant FOX (Fitting to Outcomes eXpert). The company says the technology is expected to enable a faster and more consistent fitting of cochlear implants. A short time ago, Cochlear shares were trading at $147.09, up 0.2% in a falling market.