Tim Cook has said that the "best" of the iPhone is still yet to come, as Apple celebrates its 10th birthday. The first phone was introduced on 9 January 2007 at a Macworld event in San Francisco, by Steve Jobs. The late Apple co-founder described the pocket computer as three products in one – "a widescreen iPod with touch controls, a revolutionary mobile phone and a breakthrough internet communications device". Now, 10 years later, the company is celebrating the anniversary by promising that the upcoming phones – presumably including the much-rumoured iPhone 8 – will bring updates better than those seen in the phones since 2007. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.

It is supposed to make life easier – but owners of the new Amazon Echo have fallen foul of the high-tech gadget's automatic features. Owners of the device been warned after a number accidentally ordered dollhouses that were being discussed on a TV show. The Amazon Echo, which includes a virtual assistant called Alexa, was a popular Christmas gift this year. Alexa performs tasks at the vocal request of her owner – including internet shopping. But a recent incident in America has revealed the technology could prove costly to unsuspecting users.

Nature has given human beings an amazing ability to learn. We learn complex tasks, like language and image recognition from birth and continue throughout our lives to modify and build upon these first learning experiences. It seems natural then, to use the concept of learning, building up knowledge and being able to model and predict outcomes and apply that to computer related processes and tasks. The terminology used to describe the technologies involved in this paradigm in computing are Artificial Intelligence (AI). In the late 1990s, a defining moment in the world of artificial intelligence happened.

First and foremost, business leaders need to lead from the front in facing up to disruption. "It's a leadership issue," says Anders Ibsen, serial entrepreneur and co-founder of Copenhagen-based artificial intelligence for SEM (search engine marketing) company Cobiro. "A lot of it starts at the leadership level," agrees Uschi Schreiber, EY Global Vice Chair - Markets. "For businesses to reinvent themselves there needs to be an understanding at the leadership level of what disruption means for their organisation." Leaders need to set the pace and be visibly directing their teams to stay a step ahead of changes.

Continuing their push to jointly develop self-driving vehicles, Intel (INTC), Mobileye (MBLY) and BMW (BMWYY) say they will put a fleet of about 40 autonomous vehicles on the road by the second half of 2017. The announcement, made at the CES show in Las Vegas on Wednesday, follows the partnership established by BMW Group, Intel and Mobileye last July. BMW plans to use Mobileye and Intel technology for "highly and fully automated driving" in the BMW iNext, an all-electric vehicle. The 40 autonomous vehicles will demonstrate "the significant advancements made by the three companies toward fully autonomous driving," according to a joint press release. They said the BMW 7 Series will employ cutting-edge Intel and Mobileye technologies during global trials that will start in the U.S. and Europe.

Opinions expressed by Forbes Contributors are their own. The author is a Forbes contributor. The opinions expressed are those of the writer. I've previously written about the Golden Age of Gadgets and how China has propelled it. At this year's Consumer Electronics Show (CES), the annual international show for consumer electronics held in Las Vegas, this only affirmed my position on China.

Professor Einstein rolls his eyes, sticks out his tongue, and can give a simple explanation of the theory of relativity. With his lifelike rubbery "skin" and bushy mustache, he can almost make you forget he's a robot. The Einstein robot is among dozens roaming the Consumer Electronics Show in Las Vegas that can be your companion, educator or babysit your children. While robots have been around for years, advances in technology and artificial intelligence have allowed developers to give them traits that enable the devices to be seen as members of the family. "We make robots that have personality and come to life," said Andy Rifkin, chief technology officer of Hanson Robotics, the Hong Kong-based firm which is bringing the $299 Einstein robot to consumers this year.

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Yiling Chen (yiling@seas.harvard.edu) is Gordon McKay Professor of Computer Science at Harvard University, Cambridge, MA. Arpita Ghosh (arpitaghosh@cornell.edu) is an associate professor of information science at Cornell University, Ithaca, NY. Michael Kearns (mkearns@cis.upenn.edu) is a professor and National Center Chair of Computer and Information Science at the University of Pennsylvania, Philadelphia, PA. Tim Roughgarden (tim@cs.stanford.edu) is an associate professor of CS at Stanford University, Stanford, CA. Jennifer Wortman Vaughan (jenn@microsoft.com) is a senior researcher at Microsoft Research, New York, NY.

Deep neural networks have been developed drawing inspiration from the brain visual pathway, implementing an end-to-end approach: from image data to video object classes. However building an fMRI decoder with the typical structure of Convolutional Neural Network (CNN), i.e. learning multiple level of representations, seems impractical due to lack of brain data. As a possible solution, this work presents the first hybrid fMRI and learnt deep features decoding approach: collected fMRI and deep learnt representations of video object classes are linked together by means of Kernel Canonical Correlation Analysis. In decoding, this allows exploiting the discriminatory power of CNN by relating the fMRI representation to the last layer of CNN (fc7). We show the effectiveness of embedding fMRI data onto a subspace related to deep features in distinguishing two semantic visual categories based solely on brain imaging data.