Wellness
Workaholics: Let Google's machine learning tool solve your work-life balance problems - TechRepublic
Have trouble achieving a work-life balance? Well, Google Calendar might be able to help. On Wednesday, Google released Goals, a new feature for Google Calendar that uses machine intelligence to help users find time in their busy schedule to accomplish personal goals, such as exercising, reading more, or learning a new skill. Goals is on the Google Calendar mobile app, and can be used to tackle specific, categorized goals, or to create and pursue a custom personal goal. The new feature is now available everywhere that Calendar is. For those of us who live and die by what's on our calendars, stating our goals is a good start to achieving them.
Artificial intelligence project could yield clues about autism Spectrum
Researchers have traced the paths of thousands of neurons in a tiny piece of mouse brain, creating the largest map of neuronal wiring to date. The atlas, published in March in Nature, shows not only how these neurons connect, but also how they function as the brain processes information1. The work is part of a massive effort, backed by more than 70 million in federal funding, to use the brain as a blueprint for intelligent machines. The findings could also offer clues about how the brain becomes wired during development and what happens when this wiring goes awry, says lead researcher R. Clay Reid, senior investigator of neural coding at the Allen Institute for Brain Science in Seattle, Washington. "In some way that no one has thought of yet, this will help [to advance our understanding of] autism," he says.
Microscope uses artificial intelligence to find cancer cells more efficiently
Scientists at the California NanoSystems Institute at UCLA have developed a new technique for identifying cancer cells in blood samples faster and more accurately than the current standard methods. In one common approach to testing for cancer, doctors add biochemicals to blood samples. Those biochemicals attach biological "labels" to the cancer cells, and those labels enable instruments to detect and identify them. However, the biochemicals can damage the cells and render the samples unusable for future analyses. There are other current techniques that don't use labeling but can be inaccurate because they identify cancer cells based only on one physical characteristic.
Taco Bell releases Slack-based TacoBot that takes food orders
Deutsch's senior VP and creative technology director, Martin Legowiecki, told Marketing Land, "We are at a point of switching up how we use computers. It used to be we had to talk like computers." With chatbots marketers can use computers to "talk" with consumers, not just the other way around. Of course in creating a chatbot, marketers must craft elaborate decision trees on how the automated communication responds to various interactions. For example, when the TacoBot takes order, if you tell the you happen to be drunk, it automatically adds water to your order -- and humor into the chatbot ordering process.
Microscope uses artificial intelligence to find cancer cells more efficiently
Scientists at the California NanoSystems Institute at UCLA have developed a new technique for identifying cancer cells in blood samples faster and more accurately than the current standard methods. In one common approach to testing for cancer, doctors add biochemicals to blood samples. Those biochemicals attach biological "labels" to the cancer cells, and those labels enable instruments to detect and identify them. However, the biochemicals can damage the cells and render the samples unusable for future analyses. There are other current techniques that don't use labeling but can be inaccurate because they identify cancer cells based only on one physical characteristic.
Tokyo stocks fall back, hit by selling on rally
Stocks turned lower on the Tokyo Stock Exchange Friday, pressured by selling on a rally after the recent sharp advance. The 225-issue Nikkei average lost 63.02 points, or 0.37 percent, to end at 16,848.03. On Thursday, the key market gauge jumped 529.83 points to a two-week high. The Topix index of all first-section issues finished down 9.95 points, or 0.73 percent, at 1,361.40, after advancing 38.91 points the previous day. Tokyo stocks got off to a weaker start after the Nikkei average shot up more than 1,100 points, or over 7 percent, during the previous three days.
Sleep: Difference between revisions - Wikipedia, the free encyclopedia
Sleep is a naturally recurring state of mind characterized by altered consciousness, relatively inhibited sensory activity, inhibition of nearly all voluntary muscles, and reduced interactions with surroundings.[1] It is distinguished from wakefulness by a decreased ability to react to stimuli, but is more easily reversed than the state of hibernation or of being comatose. Mammalian sleep occurs in repeating periods, in which the body alternates between two highly distinct modes known as non-REM and REM sleep. REM stands for "rapid eye movement" but involves many other aspects including virtual paralysis of the body. During sleep, most systems in an animal are in an anabolic state, building up the immune, nervous, skeletal, and muscular systems. Sleep in non-human animals is observed in mammals, birds, reptiles, amphibians, and fish, and, in some form, in insects and even in simpler animals such as nematodes. The internal circadian clock promotes sleep daily at night in diurnal species (such as humans) and in the day in nocturnal organisms (such as rodents). However, sleep patterns vary widely among animals and among different individual humans. Industrialization and artificial light have substantially altered human sleep habits in the last 100 years.[2] The diverse purposes and mechanisms of sleep are the subject of substantial ongoing research.[3] Sleep seems to assist animals with improvements in the body and mind. A well-known feature of sleep in humans is the dream, an experience typically recounted in narrative form, which resembles waking life while in progress, but which usually can later be distinguished as fantasy. Sleep is sometimes confused with unconsciousness, but is quite different in terms of thought process. Humans may suffer from a number of sleep disorders. These include dyssomnias (such as insomnia, hypersomnia, and sleep apnea), parasomnias (such as sleepwalking and REM behavior disorder), bruxism, and the circadian rhythm sleep disorders. In mammals and birds, sleep is divided into two broad types: rapid eye movement (REM sleep) and non-rapid eye movement (NREM or non-REM sleep). Each type has a distinct set of physiological and neurological features associated with it. REM sleep is associated with dreaming, desynchronized and faster brain waves, loss of muscle tone,[4] and suspension of homeostasis[citation needed]. REM and non-REM sleep are so different that physiologists classify them as distinct behavioral states. In this view, REM, non-REM, and waking represent the three major modes of consciousness, neural activity, and physiological regulation.[5]
Largest-Ever Medical Imaging Study Launches In The UK
MRI images like this one might help researchers learn about organs before disease sets in, which could help them discover new treatments and prevention tactics. Doctors have found lots of ways to see right through you. Now a team of researchers throughout the United Kingdom will be doing a lot of that--they are kicking off the world's largest imaging study. The scientists, who are affiliated with the UK nonprofit Biobank, intend to capture images of the brains, hearts, bones, and arteries of 100,000 patients, with the help of MRIs, X-rays, and ultrasounds. By combining those images with other types of lifestyle and health data that the researchers have spent the past decade collecting, the researchers hope to better understand how to prevent and treat disease.
Association Rules and the Apriori Algorithm: A Tutorial
When we go grocery shopping, we often have a standard list of things to buy. Each shopper has a distinctive list, depending on one's needs and preferences. A housewife might buy healthy ingredients for a family dinner, while a bachelor might buy beer and chips. Understanding these buying patterns can help to increase sales in several ways. While we may know that certain items are frequently bought together, the question is, how do we uncover these associations? Besides increasing sales profits, association rules can also be used in other fields.