A dream is successions of images, ideas, emotions, and sensations that usually occurs involuntarily in the mind during certain stages of sleep.[1] The content and purpose of dreams are not definitively understood, though they have been a topic of scientific speculation, as well as a subject of philosophical and religious interest, throughout recorded history. The scientific study of dreams is called oneirology.[2] Dreams mainly occur in the rapid-eye movement (REM) stage of sleep--when brain activity is high and resembles that of being awake. REM sleep is revealed by continuous movements of the eyes during sleep. At times, dreams may occur during other stages of sleep. However, these dreams tend to be much less vivid or memorable.[3] The length of a dream can vary; they may last for a few seconds, or approximately 20–30 minutes.[3] People are more likely to remember the dream if they are awakened during the REM phase. The average person has three to five dreams per night, and some may have up to seven;[4] however, most dreams are immediately or quickly forgotten.[5] Dreams tend to last longer as the night progresses. During a full eight-hour night sleep, most dreams occur in the typical two hours of REM.[6] In modern times, dreams have been seen as a connection to the unconscious mind. They range from normal and ordinary to overly surreal and bizarre. Dreams can have varying natures, such as being frightening, exciting, magical, melancholic, adventurous, or sexual. The events in dreams are generally outside the control of the dreamer, with the exception of lucid dreaming, where the dreamer is self-aware.[7]

Can we use big data and artificial intelligence to foster future financial success in today's African youth? Having started with a series of surveys to understand practical behaviours throughout one's childhood that correlate with financial success, Yassi currently leads this initiative across Africa focusing on the creation of personalised data-led mechanisms to nurture those behaviours. Embedding new solutions amongst African youth in underprivileged communities, she will monitor whether via data and AI-enabled technologies such as chatbots, one can influence and maintain their existing drive and ambitions throughout their critical adolescent years. SXSW reserves the right to restrict access to or availability of comments related to PanelPicker proposals that it considers objectionable.

It has spent a huge A 300,000 on Chip, a humanoid robot that will be used to carry out research into artificial intelligence for the bank. One of only three REEM robots from Spanish firm PAL Robotics, Chip aims to identify the opportunities and limitations of human-robot interaction, in the hope that the technology will one day become an integral part of improving banking services. Kelly Bayer Rosmarin, group executive, institutional banking and markets, CommBank, commented: "The development of robotics and artificial intelligence will affect all of us in the future. This research will help us better understand the impact social robotics will have on the lives of people, customers and industries across Australia." The bank's innovation lab in Sydney will be used as a testing environment for the research, allowing both students and academics from the country's technology universities to experiment with robotics.

Meet Alter, the humanoid robot that controls its own movements.

When Siri was originally released on the iPhone 4S back in 2011, the reviews were somewhat lukewarm. On the positive side, having an intelligent assistant baked into a massively popular smartphone was a huge leap forward. On the other hand, Siri didn't always perform as advertised. Even more problematic was that Siri's feature set was purposefully stunted by Apple. In fact, the Siri Apple released in 2011 wasn't even as capable as the Siri app that Siri's original developers had previously released on the App Store.

Small is beautiful, as the old saying goes, and nowhere is that more true than in media files. Compressed images are considerably easier to transmit and store than uncompressed ones are, and now Google is using neural networks to beat JPEG at the compression game. Google began by taking a random sample of 6 million 1,280 720 images on the web. It then broke those down into nonoverlapping 32 32 tiles and zeroed in on 100 of those with the worst compression ratios. The goal there, essentially, was to focus on improving performance on the "hardest-to-compress" data, because it's bound to be easier to succeed on the rest.

Looking for an artificial intelligence that can write all your email messages so you don't have to? That dream is still years away. But in the meantime, a startup called Boomerang wants to take you at least part of the way there. Boomerang makes a plug-in for Gmail and Outlook that lets you hit the "snooze button" on certain messages. They'll disappear from your inbox but then reappear at later time.

Today's post is from Sean McClure. Sean is the Director of Data Science at Space-Time Insight, a leading provider of advanced analytics software for organizations looking to leverage machine learning for their business applications. Having worked across diverse industries, and alongside many talented professionals, Sean has seen the blend of approaches required to convert raw data successfully into real world value. Sean's passion is working with cross-discipline teams to build the next generation of adaptive, data-driven applications. Organizations are a product of their choices.

As part of our look back over the last 70 years, we created this quiz all about British motoring from 1946 to 2016.But enough about the past – we've always got one eye on the future, with exciting new developments happening in the automotive industry all the time. Right now, electric cars are growing in popularity, in-car infotainment tech is getting more and more impressive, and manufacturers are working with governments to make self-driving cars a reality. Within the next decade, Britain's roads could begin looking very different. In the year 2086, how might the motoring world have changed? There will be some major changes over the next 70 years.

Whether you're blogging, publishing a video, or sharing an image, you are contributing to the 2.5 quintillion bytes of data that is made everyday! The old method of publishing tons of content isn't as effective as it used to be. Many more are publishing great content nowadays to the point that it's becoming increasingly difficult to be heard over all that digital noise. It's time to blow off that dust and apply a shiny new coat of machine learning polish to your content strategy. As a sub-set of artificial intelligence, machine learning occurs when computer algorithms are programmed to learn from the data and information it inputs.