FRANKFURT (Reuters) - Humanity no longer needs God but may with the help of artificial intelligence develop a new form of collective consciousness that fulfils the role of religion, U.S. author Dan Brown said on Thursday. Brown made the provocative remark at the Frankfurt Book Fair where he was promoting his new novel, "Origin", the fifth outing for Harvard "symbology" professor Robert Langdon, the protagonist of "The Da Vinci Code", a book that questioned the history of Christianity. "Origin" was inspired by the question "Will God survive science?", said Brown, adding that this had never happened in the history of humanity. "Are we naive today to believe that the gods of the present will survive and be here in a hundred years?" Brown, 53, told a packed news conference.

The GPU Technical Conference in Munich is an annual showcase of the best advancements in computer technology, but it seems like it's no place for cars. That is, until autonomous concept cars became the main attraction this year according to NVIDIA, a gaming technology company and now a competitive force in the realm of artificial intelligence. Those who set foot in the International Conference Center this week were greeted with a fleet of autonomous concept vehicles powered by NVIDIA's Artificial Intelligence systems. The theme for this event was the future of mobility, displaying a diverse range of concepts that covered everything from race cars to taxis.

The particle detectors at CERN are like cathedral-sized 3D digital cameras, capable of recording hundreds of millions of collision events per second. The detectors consist of multiple'layers' of detecting equipment, designed to recognise different types of charged particles produced by the collisions at the heart of the detector. As the charged particles fly outwards through the various layers of the detector, they leave traces, or'hits'. Tracking is the art of connecting the hits to recreate trajectories, thus helping researchers to understand more about and identify the particles. The algorithms used to reconstruct the collision events by identifying which dots belong to which charged particles can be very computationally expensive.

Robots in the workplace should be owned and controlled by workers rather than bosses, Jeremy Corbyn will suggest. The Labour leader, who has previously warned of the risk to jobs of automation, will say new technology has led to "a more rapacious and exploitative form of capitalism". He will also suggest "gig economy" firms like Uber could be replaced by co-operatives. Drivers would collectively agree their own pay and conditions, he will say. Earlier this year, a study by accountancy firm PwC said robotics and artificial intelligence could affect almost a third of UK jobs by the 2030s, with "more manual, routine jobs" which "can effectively be programmed" the most at risk.

Real data often contain anomalous cases, also known as outliers. These may spoil the resulting analysis but they may also contain valuable information. In either case, the ability to detect such anomalies is essential. A useful tool for this purpose is robust statistics, which aims to detect the outliers by first fitting the majority of the data and then flagging data points that deviate from it. We present an overview of several robust methods and the resulting graphical outlier detection tools. We discuss robust procedures for univariate, low-dimensional, and high-dimensional data, such as estimating location and scatter, linear regression, principal component analysis, classification, clustering, and functional data analysis. Also the challenging new topic of cellwise outliers is introduced.

A vast majority of computation in the brain is performed by spiking neural networks. Despite the ubiquity of such spiking, we currently lack an understanding of how biological spiking neural circuits learn and compute in-vivo, as well as how we can instantiate such capabilities in artificial spiking circuits in-silico. Here we revisit the problem of supervised learning in temporally coding multi-layer spiking neural networks. First, by using a surrogate gradient approach, we derive SuperSpike, a nonlinear voltage-based three factor learning rule capable of training multi-layer networks of deterministic integrate-and-fire neurons to perform nonlinear computations on spatiotemporal spike patterns. Second, inspired by recent results on feedback alignment, we compare the performance of our learning rule under different credit assignment strategies for propagating output errors to hidden units. Specifically, we test uniform, symmetric and random feedback, finding that simpler tasks can be solved with any type of feedback, while more complex tasks require symmetric feedback. In summary, our results open the door to obtaining a better scientific understanding of learning and computation in spiking neural networks by advancing our ability to train them to solve nonlinear problems involving transformations between different spatiotemporal spike-time patterns.

Would you ride in a car that was prepared to kill you? An "ethical knob" could let the owners of self-driving cars choose their car's ethical setting. You could set the car to sacrifice you for the survival of others, or even to always sacrifice others to save you. The dilemma of how self-driving cars should tackle moral decisions is one of the major problems facing manufacturers. When humans drive cars, instinct governs our reaction to danger.

I was about to plug my new Google Home Mini into the wall outlet this weekend when I froze. What kind of a commitment was I about to make? Google had handed out freebies of its puck-sized, fabric-coated gizmo at a press event last week. It seemed like a good, low-risk opportunity to dip my toes in the home voice-assistant waters. Scott Rosenberg is an editor at Backchannel.

Cambridge Consultants showed off an deep-learning driven application this week at GTC Europe in Munich that lets you pick up a stylus and sketch out a few lines, and watch, in real time, as the application turns your squiggles into art in one of seven styles resembling everything from moody J.M.W Turner oil paintings to neon-hued pop art. It's a demo that stunned the more than 3,000 attendees during NVIDIA CEO Jensen Huang's keynote speech Tuesday at the show. Huang even climbed down from the stage to pick up a stylus and sketch a stylized NVIDIA logo and a profile of a man -- which the application transformed into a Picasso-esque painting as he worked -- grinning as the audience applauded. The story behind the story: a finely tuned generative adversarial network that sampled 8,000 great works of art -- a tiny sample size in the data-intensive world of deep learning -- and in just 14 hours of training on an NVIDIA DGX system created an application that takes human input and turns it into something stunning. Building on thousands of hours of research undertaken by Cambridge Consultants' AI research lab, the Digital Greenhouse, a team of five built the Vincent demo in just two months.

Amazon is to create a further 1,200 new jobs with a warehouse in Bolton as it continues its rapid UK expansion. The warehouse, which will be the third to open in the north-west, will be one of a new generation of Amazon facilities that will see staff work alongside robots. Stefano Perego, an Amazon director, said the warehouse would take the total number of new permanent jobs the company has created in the north-west of England to more than 3,500 since 2016. Amazon, which will have 15 of the warehouses – called fulfilment centres – across the UK by the end of this year, employs a workforce of 24,000 across Britain. Amazon has started recruiting for a range of roles at the fulfilment centre, including operations managers, engineers, human resources staff and IT specialists.