DON'T make fun weekend plans: Researchers say too much planning will kill your enjoyment A researcher from The Ohio State University found that it is common for people to lose excitement over plans they scheduled in advance. Not just for lonely men: Sex robots will let couples have... From a dazzling supermoon to a stunning meteor shower: Here... Are these the legs of Queen Nefertari? Mystery mummified... Britain's ancient multicultural heritage revealed: Roman... Not just for lonely men: Sex robots will let couples have... From a dazzling supermoon to a stunning meteor shower: Here... Are these the legs of Queen Nefertari? Mystery mummified... Britain's ancient multicultural heritage revealed: Roman... Across 13 studies, researchers found that the simple act of scheduling makes otherwise fun tasks feel more like work.

Not just for lonely men: Sex robots will let couples have... You could book a holiday on the MOON by 2026: Private firm... From a dazzling supermoon to a stunning meteor shower: Here... Britain's ancient multicultural heritage revealed: Roman... Not just for lonely men: Sex robots will let couples have... You could book a holiday on the MOON by 2026: Private firm... From a dazzling supermoon to a stunning meteor shower: Here... Britain's ancient multicultural heritage revealed: Roman... The F-35 Joint Strike Fighter has been hailed as the'most expensive weapon in history.'

Analyses performed using Spark of brain activity in a larval zebrafish: embedding dynamics of whole-brain activity into lower-dimensional trajectories. This open source computing framework unifies streaming, batch, and interactive big data workloads to unlock new applications. The growth of data volumes in industry and research poses tremendous opportunities, as well as tremendous computational challenges. As data sizes have outpaced the capabilities of single machines, users have needed new systems to scale out computations to multiple nodes. As a result, there has been an explosion of new cluster programming models targeting diverse computing workloads.1,4,7,10 At first, these models were relatively specialized, with new models developed for new workloads; for example, MapReduce4 supported batch processing, but Google also developed Dremel13 for interactive SQL queries and Pregel11 for iterative graph algorithms. In the open source Apache Hadoop stack, systems like Storm1 and Impala9 are also specialized. Even in the relational database world, the trend has been to move away from "one-size-fits-all" systems.18 Unfortunately, most big data applications need to combine many different processing types. The very nature of "big data" is that it is diverse and messy; a typical pipeline will need MapReduce-like code for data loading, SQL-like queries, and iterative machine learning. Specialized engines can thus create both complexity and inefficiency; users must stitch together disparate systems, and some applications simply cannot be expressed efficiently in any engine. In 2009, our group at the University of California, Berkeley, started the Apache Spark project to design a unified engine for distributed data processing.

A new artificial intelligence tool created by Google and Oxford University researchers could significantly improve the success of lip-reading and understanding for the hearing impaired. In a recently released paper on the work, the pair explained how the Google DeepMind-powered system was able to correctly interpret more words than a trained human expert. The tool is called Watch, Listen, Attend and Spell (WLAS), and the paper describes it as a "network that learns to transcribe videos of mouth motion to characters." Using videos from the BBC, the team trained the system with a dataset of more than 100,000 natural sentences. While similar attempts in the past have focused on a narrow set of words, the report said, Google and Oxford wanted to address lip reading through "unconstrained natural language sentences, and in the wild videos."

In considering current market conditions and near-term growth from a technological standpoint, it is essential to first ask the question: what is happening? The world is moving faster, people are more enabled/connected today than ever, and fear of missing out is as central socially today in society as it is for companies – who do not want to lose customers. If one can agree with all that, then one might also agree with the following: this is the age of the customer, and therefore convergence of technologies in order to serve the customer is still happening. Understanding how the long arc of technological revolutions and financial capital matters as well as where one is in history – the fourth industrial revolution (though Carlota Perez argues this is in the fifth). The fourth industrial revolution is centred around IT. The long wave of financial capital is marked by two phases – an installation period and a deployment period.

Artificial intelligence and increasing automation is going to decimate middle class jobs, worsening inequality and risking significant political upheaval, Stephen Hawking has warned. In a column in The Guardian, the world-famous physicist wrote that "the automation of factories has already decimated jobs in traditional manufacturing, and the rise of artificial intelligence is likely to extend this job destruction deep into the middle classes, with only the most caring, creative or supervisory roles remaining." He adds his voice to a growing chorus of experts concerned about the effects that technology will have on workforce in the coming years and decades. The fear is that while artificial intelligence will bring radical increases in efficiency in industry, for ordinary people this will translate into unemployment and uncertainty, as their human jobs are replaced by machines. Technology has already gutted many traditional manufacturing and working class jobs -- but now it may be poised to wreak similar havoc with the middle classes.

Is this Amazon's top-secret delivery drone? Aircraft is thought to be a prototype of Amazon's delivery drone Amazon has a 500,000 square foot warehouse in Peterborough The Seattle-based company wants to use drones to deliver packages to people's homes in under 30 minutes Aircraft is thought to be a prototype of Amazon's delivery drone The Seattle-based company wants to use drones to deliver packages to people's homes in under 30 minutes Some outlets claim the footage is the first time a prototype Amazon drone has been spotted, but similar pictures were revealed earlier this year. New video footage has surfaced showing a drone flying above a field in Cambridgeshire. The aircraft is thought to be a prototype of Amazon's new delivery drone Apple warns 90% of'official' iPhone cables and chargers... Are you affected? WhatsApp will stop running on MILLIONS of... Meet'Baby Boom': The supersonic passenger airliner that can...

As in the global survey, we are concerned with platform business models and the design choices that allow these business models to grow. We find the term platform, which is well-established in economic and management literature, offers a more useful and accurate term than some of the terms that have been used such as "share economy companies," "internet companies" or, even more broadly, "tech companies." Network effects are a key characteristic that distinguish platforms from other business models. As more users engage with a platform, the more attractive the platform becomes to potential new users. When more users attract more users, a dynamic is created that in turn triggers a self-reinforcing cycle of growth.

WhatsApp is about to stop working on millions of phones. Older devices are going to have their support cut off so that they'll no longer be able to use the free chat app. Phones including the iPhone 3GS and Android handsets are about to stop being supported by WhatsApp's engineers. And when that happens, owners will no longer be able to send or receive messages. WhatsApp first announced the change early this year.

Several years ago, I attended a Buddhist retreat in which I was introduced to the idea of the "retinue," a constellation of influential and supportive people whom one imagines in an enveloping cloud as one meditates. I took the concept one step further and decided to create an actual photo montage that I could hang on the wall above my desk: my childhood piano teacher, my high school English teacher, my rabbi, mentors in science, writers who encouraged me--in all, 20 people who had profoundly influenced me. Some members of my retinue were still living, some not. In some cases I could find the photographs myself. In others, I had to contact the mentors. When I finally tracked down William Gerace, who introduced me to physics nearly 50 years ago, he was puzzled as to why I should desire such a montage. We had not spoken for decades. Reluctantly, he sent me an old, out-of-focus photo of himself, dating back to the days when I knew him. Now, Gerace is a professor of science education at the University of North Carolina at Greensboro, after a 30-year career as a professor of physics at the University of Massachusetts Amherst, during which time he made the transition from theoretical nuclear physicist to leader in science education and co-founder of the Scientific Reasoning Research Institute at the University of Massachusetts, Amherst. When I knew him, in the late 1960s, he was a lowly instructor in physics at Princeton, where he had recently received his Ph.D. I was an undergraduate. The photo shows a man in his late 20s, about 5 feet 6, slight in build, dark hair beginning to thin, dressed in a button-down shirt and blue sweater, and a Mona Lisa smile. Each new mathematical technique Bill taught us was offered with the enthusiasm of a 12-year-old boy showing his friend a strange new butterfly. I first met Bill Gerace during a physics lab my sophomore year.