A dream is a succession 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 fully 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]

Last week, Casey Newton wrote about Roman, an AI bot created by Eugenia and her team to memorialize their deceased friend. The piece ignited many thoughts and conversations I've had on this topic… My parents are "digital immigrants", born before the widespread adoption of digital technology. I grew up with computers and the internet, shaping my world view and relationships. Technology often brings us together but it has also spread generations apart. Try calling a millennial on the phone.

With Facebook and Twitter now offering branded chatbots, how can brands get the most out of AI-powered customer service? Matt Wright, Search Engine Optimisation (SEO) freelancer and Venturebeat contributor, looks at the 8 basic conversations your bot should be well-versed in before meeting your consumers. Chatbots are robotic messenger services where audiences can ask a robotic chat simulator basic questions. They may well in the future sit prominently on your brand site, helping to replace and make the most of website chat widgets, WhatsApp conversations, Facebook Messenger chats, Kik or in combination with voice search services such as Siri, Amazon Alexa, Google voice search or Google Home. Chat bots should really be exciting SEOs right now if your ask me https://t.co/crQdzVBYnF

CBR looks at the'Artificial intelligence: an overview for policy-makers' report from the Government Office for Science. The UK government is driving the artificial intelligence agenda, pinpointing it as a future technology driving the fourth revolution and billing its importance on par with the steam engine. The report on Artificial Intelligence by the Government Office for Science follows the recent House of Commons Committee report on Robotics and AI, setting out the opportunities and implications for the future of decision making. In a report which spans government deployment, ethics and the labour market, Digital Minister Matt Hancock provided a foreword which pushed AI as a technology which would benefit the economy and UK citizens. "As one the world's leading digital nations, artificial intelligence presents a huge opportunity for the UK. Get this right, and we can create a more prosperous economy with better and more fulfilling jobs," Mr Hancock wrote in the report.

InfiniBand is set to hit 200Gbps (bits per second) in products that were announced Thursday, potentially accelerating machine-learning platforms as well as HPC (high-performance computing) systems. The massive computing performance of new servers equipped with GPUs calls for high network speeds, and these systems are quickly being deployed to handle machine-learning tasks, Dell'Oro Group analyst Sameh Boujelbene said. So-called HDR InfiniBand, which will be generally available next year in three sets of products from Mellanox Technologies, will double the top speed of InfiniBand. It will also have twice the top speed of Ethernet. But the high-performance crowd that's likely to adopt this new interconnect is a small one, Boujelbene said. Look for the top 10 percent of InfiniBand users, who already use 100Gbps InfiniBand, to jump on the new stuff, she said.

That there's little love lost between Donald Trump and Silicon Valley is hardly a new revelation. But while a Trump Administration's relationship with the tech elite is bound to be more distant and chillier than a Clinton Administration's would have been, its policies may simply be sub-optimal for the tech sector rather than disastrous -- and with some notable silver linings. On one hand, a lack of the close ties prominent tech execs formed with the Obama Administration, and appeared set to maintain with a Clinton Administration, could cause some problems. Obama, who recently guest-edited an issue of Wired magazine and gave the publication a thoughtful interview on various tech topics, has been willing to lend an ear to Silicon Valley's views on issues such as autonomous driving regulations, encryption keys, artificial intelligence research and STEM education funding. Trump, who appears to know much less about tech and briefly called for a boycott of Apple (AAPL) in response to the company's unwillingness to help break the encryption on an iPhone used by one of the San Bernardino shooters, probably won't be holding talks with the likes of Tim Cook and Facebook's (FB) Mark Zuckerberg and Sheryl Sandberg as frequently.

But that is not to say it is perfect by any stretch of the imagination. "Deep learning has led to some big advances in computer vision, natural language processing, and other areas," Tommi Jaakkola, a Massachusetts Institute of Technology professor of electrical engineering and computer science, told Digital Trends. "It's tremendously flexible in terms of learning input/output mappings, but the flexibility and power comes at a cost. That is it that it's very difficult to work out why it is performing a certain prediction in a particular context." This black-boxed lack of transparency would be one thing if deep learning systems were still confined to being lab experiments, but they are not.

Almost every action we do on the Internet or on mobile applications is recorded in files known as web logs. These logs can be very voluminous, providing a classic example of Big Data. Data science and Machine Learning algorithms can provide a way of extricating value from web logs. At the OVH Summit on the 11th of October, I presented a workshop on getting value out of web logs through Machine Learning with Dataiku DSS. In this article, I will run through the aspects of that presentation.

Machine learning is a very hot topic for many key reasons, and because it provides the ability to automatically obtain deep insights, recognize unknown patterns, and create high performing predictive models from data, all without requiring explicit programming instructions. This is a summary (with links) to an article series that's intended to be a comprehensive, in-depth guide to machine learning, and should be useful to everyone from business executives to machine learning practitioners. It covers virtually all aspects of machine learning (and many related fields) at a high level, and should serve as a sufficient introduction or reference to the terminology, concepts, tools, considerations, and techniques in the field. The first chapter of the series starts with both a formal and informal definition of machine learning. This is followed by a discussion of the machine learning process end-to-end, the different types of machine learning, potential goals and outputs, and a categorized overview of the most widely used machine learning algorithms.

Science fiction has, for many years, looked to a future in which robots are intelligent and cyborgs are commonplace. The Terminator, The Matrix, Blade Runner and I, Robot are all good examples of this vision. But until the last decade, consideration of what this might actually mean in the future was unnecessary because it was all science fiction, not scientific reality. Now, however, science has not only done some catching up; it's also introduced practicalities that the original story lines didn't appear to include (and, in some cases, still don't include). What we consider here are several different experiments linking biology and technology together in a cybernetic way--essentially ultimately combining humans and machines in a relatively permanent merger.