I was rehearsing a speech for an AI conference recently when I happened to mention Amazon Alexa. At which point Alexa woke up and announced: "Playing Selena Gomez." I had to yell "Alexa, stop!" a few times before she even heard me. But Alexa was oblivious to my annoyance. Like the majority of virtual assistants and other technology out there, she's clueless about what we're feeling.
What's the secret to success? Some would argue that insanely successful people possess traits like having a vision, showing gratitude, being honest, learning from failure and having a high emotional intelligence. While these traits definitely play a role, the real secret to success comes down to science, particularly advancements in neuroscience, and how you can condition your brain to achieve your dreams and goals. The neuroscience of success can get complicated, but it's really about how your brain functions in three different areas: reticular activating system (RAS), the release of dopamine and your memory. If you're not a science person, I'll try and make this all as painless as possible.
The workings of the brain are the greatest mystery in science. Unlike our models of physics, strong enough to predict gravitational waves and unseen particles, our brain models explain only the most basic forms of perception, cognition, and behavior. We know plenty about the biology of neurons and glia, the cells that make up the brain. And we know enough about how they interact with each other to account for some reflexes and sensory phenomena, such as optical illusions. But even slightly more complex levels of mental experience have evaded our theories.
French scientists say they may have found a potential cause of dyslexia which could be treatable, hidden in tiny cells in the human eye. In a small study they found that most dyslexics had dominant round spots in both eyes - rather than in just one - leading to blurring and confusion. UK experts said the research was "very exciting" and highlighted the link between vision and dyslexia. But they said not all dyslexics were likely to have the same problem. People with dyslexia have difficulties learning to read, spell or write despite normal intelligence.
Intel CEO Brian Krzanich speaks at a 2016 AI event. Intel might be an old-school computing company, but the chipmaker thinks the latest trends in artificial intelligence will keep it an important part of your high-tech life. AI technology called machine learning today is instrumental to taking good photos, translating languages, recognizing your friends on Facebook, delivering search results, screening out spam and many other chores. It usually uses an approach called neural networks that works something like a human brain, not a sequence of if-this-then-that steps as in traditional computing. Lots of companies, including Apple, Google, Qualcomm and Nvidia, are designing chips to accelerate this sort of work.
PARIS – A duo of French scientists said Wednesday they may have found a physiological, and seemingly treatable, cause for dyslexia hidden in tiny light-receptor cells in the human eye. In people with the reading disability, the cells were arranged in matching patterns in both eyes, which may be to blame for confusing the brain by producing "mirror" images, the co-authors wrote in the journal Proceedings of the Royal Society B. In non-dyslexic people, the cells are arranged asymmetrically, allowing signals from the one eye to be overridden by the other to create a single image in the brain. "Our observations lead us to believe that we indeed found a potential cause of dyslexia," study co-author Guy Ropars of the University of Rennes, told AFP. It offers a "relatively simple" method of diagnosis, he added, by simply looking into a subject's eyes. Furthermore, "the discovery of a delay (of about 10 thousandths of a second) between the primary image and the mirror image in the opposing hemispheres of the brain, allowed us to develop a method to erase the mirror image that is so confusing for dyslexic people" -- using an LED lamp.
It is a question that has long stumped researchers. But now light has been shed on why boys are more at risk of autism. University of Iowa scientists believe they have collected the first ever evidence of a'protective effect' in females. Trials on mice showed males who had a known genetic cause of autism showed signs of being on the spectrum. This genetic deletion, or a missing stretch of DNA, plays a role in one in every 200 cases of autism spectrum disorder (ASD), experts claim.
Marijuana is said to cause permanent damage to the brain and can make users dependent on it, a new study suggested. A team of neuroscientists wanted to determine what makes marijuana addictive through long-term exposure to the drug, according to research published Monday in the journal JNeurosci. Scientific research has previously confirmed that frequent marijuana use can lead to addiction, but this study provides further detail into why this outcome is possible. Researchers at Brigham Young University's (BYU) neuroscience department injected teenage male mice test subjects with tetrahydrocannabinol (THC) -- marijuana's active ingredient -- for a weeks time. BYU researchers examined the mice's brain's ventral tegmental area (VTA), a cluster of neurons positioned near the midline in the midbrain.
Princeton University neuroscientists joined forces with Intel computer scientists to map the human mind in real time, developing the next generation in brain imaging analysis. Researchers at Princeton University and Intel Labs have developed software that enables cognitive neuroscientists to map the mind in real time. The Mind's Eye team hopes to apply findings from their studies to machine learning and AI in other industries, including pharmaceutical research and development, Willke said. A better understanding of human cognition, including how the brain solves problems, may lead to improvements in the AI that enables self-driving cars to solve problems and make decisions about the environment in which they operate.
In the video presentation below (courtesy of Yandex) – "Deep Learning: Theory, Algorithms, and Applications" – Naftali Tishby, a computer scientist and neuroscientist from the Hebrew University of Jerusalem, provides evidence in support of a new theory explaining how deep learning works. Tishby argues that deep neural networks learn according to a procedure called the "information bottleneck," which he and two collaborators first described in purely theoretical terms in 1999. Striking new computer experiments by Tishby and his student Ravid Shwartz-Ziv reveal how this squeezing procedure happens during deep learning, at least in the cases they studied. The Berlin workshop aims at bringing together leading scientists in deep learning and related areas within machine learning, artificial intelligence, mathematics, statistics, and neuroscience.