1. Articles in category: Latest News

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    1. Dementia Risk Declines, As Education Increases

      Dementia Risk Declines, As Education Increases

      Dementia is declining according to a study published Monday in JAMA Internal Medicine. One reason for the improved outlook seems likely tied to an increase in education, according to researchers.  How does that translate to numbers?

      "That's well over a million people who don't have dementia, who would have had it if the rates had stayed the same as 2000 rates," says John Haaga, who directs the Division of Behavioral and Social Research at the National Institute on Aging, which funded the study.

      The JAMA Internal Medicine study used data gathered in two samples, one in 2000 and another in 2012, that each looked at more than 10,000 Americans who were 65 years old or older.  In the first sample, approximately 11.6 percent of them had some form of dementia. In the second sample, it had dropped to 8.8 percent.  

      The average amount of education in the study population increased, while the incidence of dementia cases dropped. The average amount of education in 2000 was 11.8 years, which was just shy of the 12 years it usually takes to graduate from high school.  However, in 2012, the average amount of education was 12.7 years.

      The downward trend has emerged despite something else the study shows which was a rise in the following three factors which tend to raise dementia risk by interfering with brain blood flow:

      • Diabetes;
      • High blood pressure; and
      • Obesity.  

      Those with the most years of education had the lowest chances of developing dementia, according to the findings by a team from the University of Michigan. This may help explain the larger trend, because today’s seniors are more likely to have at least a high school diploma than those in the same age range a decade ago.

      “Our results, based on in-depth interviews with seniors and their caregivers, add to a growing body of evidence that this decline in dementia risk is a real phenomenon, and that the expected future growth in the burden of dementia may not be as extensive as once thought,” says lead author Kenneth Langa, M.D., Ph.D., a professor in the U-M Medical School.

      For the complete study, go to:



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    2. Is Our Fear of Artificial Intelligence Based on Reality - Part 1

      Is Our Fear of Artificial Intelligence Based on Reality - Part 1

      Don’t laugh, but I was counting on seeing singularity happening in my lifetime.  If you’re like me, I kind of like having a device in my pocket that can figure out a lot of things for me without my having to stress over the mental gymnastics required to solve these things on my own.  For instance, in the morning when I’m on a business trip, I find it quite helpful to ask my Google Assistant where the nearest Starbucks is located.  Then I get my second stress relieving session by getting in my car in a strange city, and ask Google to navigate me to my business appointment.  Seriously.  Bring on the self-driving Uber cars.

      My friends say, “Aren’t you afraid of getting ‘stupid’ and giving up all of your mental processes to a device?”  Internally I say “NO!” But externally I usually lie and say, “Yeah.  I’m trying to memorize all my friends’ phone numbers again in the evening…”  They simply shake their heads.

      For sure, there is a pervasive underlying fear from generations raised on dystopian science fiction that artificial intelligence and robots will be the undoing of humankind.  Eventually, as the conventional thinking goes, artificial intelligence will become smarter than the human version and terrible things will happen as machines take over the planet.  Even Gates, Hawking and Musk are on board with this thinking. 

      In reality, however, those of us that follow AI feel it’s much more likely it isn’t going to destroy us — or even take our jobs.  In fact, it’s more likely that AI is going to help us do our jobs better.  That’s worth thinking about for a moment or two.  Although the idea that AI could help us work smarter is not nearly as sexy as the notion of robot overlords taking over Earth, in actuality, it is a much more realistic view of the artificial intelligence technology that’s evolving today.   It’s also worthy of note, that this is as true for the line worker at a factory as it is for a salesperson or knowledge worker.

      While it seems like every software engineer in Silicon Valley is trying to create the perfect algorithm to replace human workers, in most cases, they are simply trying to find ways to make you a better employee by combining the power of the computer with your creative working brains.  You’ll see that in Part 2 of this report.

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    3. All the Feels: Digitizing Human Feelings

      A few years ago, companies such as FitBit popularized physical health wearables and now a number of companies are looking to collect and analyze data through phone use and mental health wearables. Vinaya, creator of Zenta, says the wrist-wearable monitors physical health, such as your heart rate, but also perspiration, respiration and temperature and cross-references this data against other data from your smartphone in order to understand cause and effect. In doing so, it creates a pattern of indicators measuring stress levels.

      Spire is another option for wearable technology that can detect breathing patterns and other signs that translates them into emotions without requiring the user to input information into an app. When an emotion is detected, it will send a signal to the user’s phone and tell him or her how to relax. Users clip it to their belt or bra so the device is discrete.

      Pala-linq is a mobile app with wearable and web components that provide support to those recovering from alcohol and/or drug addiction. Pala-linq’s technology tracks mind, body and spiritual activity levels, helping the more than 23 million Americans enrolled in substance abuse programs each year stay on track with their recovery goals. Pala-linq leverages technology to keep users connected to their support system, remember their goals and stay on track with their overall recovery plan through promoting holistic recovery principles with complementary technology. The device is currently in beta-testing.

      The Fisher Wallace Simulator, an FDA-approved neurostimulation device helps treat depression, anxiety and insomnia. The headband-like device is placed over the patient’s temples and gently stimulates the brain to release serotonin and dopamine reducing stress and increasing happiness. Doctors believe it can treat Bipolar Disorder and Depression. It can be used on its own or paired with medication and a provider must approve the treatment in order for it to be used. 

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    4. Artificial Intelligence and Sports

      Artificial Intelligence is making life easier for fans across the country. ReplyBuy sends texts to all fans and whomever replies “Buy Now” the most quickly, get the tickets. Now, they’re introducing ReplyBuy.ai, an artificial intelligence program that acts as a concierge service to tickets into the hands of fans even faster. The chat bot asks follow up questions whenever customers send a text telling it that they want tickets. After finding out how many tickets are needed and the price range, the chat bot buys the tickets and instantly texts them to the recipient. Several NFL, NBA, NHL and MLS teams are using the service, as well as some major universities such as UCLA and the University of Arizona. The company has future plans to be integrated into apps with chat capability and messaging based services such as iMessage and Facebook Messenger, along with Internet of Things devices such as Amazon Echo and others. Founded in 2011, the company has raised $2.65 million to date.

      Another product that aids sports fans is MLB Advanced Media. The product helps reinvent the customer experience with the help of Amazon Web Services’ Kinesis which processes real-time streaming data. It works to measure every pitched ball’s movements more than 2,000 times per second, stores the data on Amazon S3 and then performs pitching analytics and so many others on Amazon EC2. Collectively, the suite of services generates nearly 7TB of raw statistical data per season shedding quantitative light on baseball myths and pearls of wisdom. 

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    5. Tesla Sues Western Michigan District Court and Teases New Sunroof Product

      Tesla has filed suit with the Western District Court of Michigan over its ability to sell its cars directly to consumers and service vehicles owned by state residents. The lawsuit was filed in response to an application for a dealership license earlier in September that lines up with Tesla’s goal of selling vehicles directly to U.S. consumers.

      Currently, vehicle sales in the United States depend on dealerships to be set up as franchises, where third parties handle the sales of cars in model showrooms, rather than consumers being sold cars directly from manufacturers. a franchise dealership model, wherein licensed third-parties handle the actual sales of cars from auto manufacturers. Tesla has been trying to eliminate the third-party middle man and sell directly to consumers.

      Tesla operates showrooms in many states, but because of legal reasons, isn’t allowed to sell cars directly from them, consumers must buy the vehicles online. The state of Michigan, also America’s automotive capital, won’t allow Tesla to open a show room or a service center.

      Despite the Michigan setback, it’s business as usual for the electric car company. Elon Musk, Tesla CEO and founder plans to unveil Tesla and SolarCity’s new solar roof product on October. The product will be directly integrated with version 2.0 of the Tesla’s PowerWall solar storage battery for the home and feature a Tesla car charger. The event will also be consumers’ first full-scale look at the new version of Powerball. 

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    6. Discrimination in the Workplace

      Although obviously illegal, discrimination is still prevalent in hiring practices and the workplace. A study from Plos One found slight weight gain often hurts a woman’s chances of being hired. Researchers studied 60 men and 60 women and asked them to imagine they made the hiring decisions and look at a series of photographs and determine the likability of the people in them. The photographs showed four men and four women, all white and expressionless, at various, digitally enhanced weights. Each face reflected what doctors consider healthy body weights. A human resources manager might warn that deciding on the basis of a photo could invite a lawsuit. But the respondents made snap judgments. Both genders preferred thinner faces and identified them as more hirable than the heavier ones, though the effect was stronger for roles that involved customer interaction. The results showed that subjects were the least likely to hire larger women.

      Another group facing hiring discrimination are those Americans over the age of 50. Even with years of experience, two-thirds of job seekers report encountering age discrimination. According to the National Bureau of Economic Research, age discrimination starts earlier with females and doesn’t improve. In a report from the Sloan Center on Aging & Work, hiring managers at state agencies listed numerous stereotypes about why they felt hiring older employees was a poor choice: claiming applicants were more likely to be burned-out, resistant to new technologies, absent due to illness, poor at working with younger supervisors and reluctant to travel. In reality, data shows that older workers are reliable, handle stress, can master new skills and are engaged when offered the opportunity to grow and advance within a company.

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    7. Machine Learning to Solve Social Media Trolling and the Spread of Misinformation

      Although social media trolling has been a problem since it was first introduced, until recently, many social media giants were doing their best to manage it, but that wasn’t quite enough.

      Twitter has been struggling with negative publicity regarding bullying and tolling since July when Milo Yiannopoulos and others began harassing Saturday Night Live star Leslie Jones. In August, American gymnast Gabby Douglas was targeted with several racist tweets.

      But Twitter’s problems with its free speech policy extend beyond trolling, a number of times misinformation has been spread throughout the platform. Although it’s users’ responsibility to stay informed and decipher what may or may not be true, Twitter is starting to utilize machine learning for its new quality filter, which was introduced to stop trolling and the spread of misinformation. The filter also hides notifications from bots and spam tweets.

      KnowMore is a third-party alternative to negative tweets. The Brooklyn-based app provides users with the ability to share and mute block lists among subscribers and creates a blacklist that anyone can subscribe to. It also uses machine learning to function properly.

      Block Together is another third-party alternative used to reduce the burden of blocking when many accounts are attacking your organization or when a few accounts are attacking a number of accounts in a community. Users can also share their blocked lists with others as well. The service also allows users auto-block accounts that are less than seven days old or have 15 or fewer followers, which helps combat the spread of misinformation.

      Facebook Inc.-owned Instagram is another social media giant that’s struggled to block negative comments in the past. The company introduced a new tool to the public and allows any account manager to filter comments with negative words from being posted on their photos. Certain celebrities and organizations have had this option for a while, but the machine learning-based feature is rolling out publicly this week. 

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    8. Machine Learning and Agriculture

      One of the major uses of machine learning has been in the agricultural sector. Applications converge with drones determining weather, if water and machinery is accessible in certain locations and if pests or nutrient deficiencies in the soil will make it difficult to grow crops. All of these pieces are put into an adaptive algorithm which self-corrects and “learns” where farming will be most successful.

      Almonds are a tricky crop to grow, they require a lot of water and can only thrive in a very specific climate. Central California’s climate it ideal for them, and the region grows most of the almonds that are consumed in the United States. However, the area relies on sophisticated and expensive irrigation since most of the state’s water is located in the northern region. It’s difficult for farmers to get the right range of soil moisture for growth and operators can’t simply turn on irrigation systems like a faucet, they must plan ahead to ensure availability and compliance with governmental regulations. It’s difficult to predict the amount of water needed at a given time due to temperature variations, historical data and data from sensors at a current time. Too often, almond farmers have produced sub-optimal results or lost crops due to human error.

      Machine learning can be used to solve this problem. Z-Farm, an almond cooperative, partnered with ThingWorx Machine Learning to run on top of the Internet of Things (IoT) databases detecting patterns, abnormalities and to predict the need for water and automating the solution from start to finish. Within the first day, ThingWorx discovered that farmers were over-watering their crops on the hottest days due to solar radiation penetrating the soil rather than the soil moisture itself. This alone is saving the company water and money while yielding higher-quality crops.

      Beyond planning and growing, machine learning can be used for sorting crops too, saving farmers time. Japan doesn’t have a standardized classification model for cucumbers and Makoto Koike, a former embedded systems designer in the automotive industry, has helped his parents come up with an automated way to sort their harvest into nine categories — something that can take up to nine hours per day when done manually. Koike uses Raspberry Pi 3 as the main controller to take photos of the cucumber and then sends the data to Google’s TensorFlow to determine whether or not the image is a cucumber. The image is the forwarded to a larger TensorFlow network running on a Linux server for further classification. The system works well, but can still be improved. Koike reported a 95 percent success rate with image recognition but only a 70 percent success rate with real use cases. 

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    9. Disrupt SF: Part 2 of 3

      Disrupt SF: Part 2 of 3

      TechCrunch’s Disrupt SF takes place September 12-14 and a number of new technologies are being introduced for the first time. This is the second part of Elearning! Magazine’s special three-part series covering product introductions at the event in San Francisco.  Read Part 1 here.

      ProductBoard is introducing a service for digital product managers that helps them better organize user research and determine which features deserve priority. The product management platform is already being used by more than 100 paying customers during its beta period to establish their product plans and collaborate with engineering teams on their upcoming feature releases. It was introduced publicly at Disrupt SF.

      Product managers often gather information from a variety of channels when determining what to build next, but they often don’t have a cohesive way to organize it. ProductBoard was created to tackle this problem specifically and offers users tools to organize and aggregate data and prioritize the list of features that need to be built.

      The service works with third-party systems where product feedback is initially collected, such as Zendesk, Intercom and others. A Chrome extension is also available for grabbing information from the internet and collecting information sent via email.

      The platform lets users know who’s asking for the change and what problem it solves. It uses an algorithm that summarizes changes requested and how they’re associated with the larger strategic drivers for the company. Then, project managers can prioritize the data in a hierarchy to determine what actions need to be completed when. A score is also assigned to each task so project managers have assistance in determining how to prioritize each task.

      Slides, an online service for creating, viewing and collaborating slideshow presentations was also launched at Disrupt SF. The goal of Slides is to bring together all of the elements in current presentation management services, such as PowerPoint and SlideShare, into one updated and seamless experience.

      The platform is flexible in that people can watch presentations in real time while on conference calls and mobile devices rather than only being accessible in one room. The sleek design and easy-to-use interface with pre-existing templates makes it easy for companies to import their own content during the creation experience.

      The company is working on adding a limited comment section. 

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    10. Want To Double Your Salary? Of Course You Do—Try This | Fast Company | Follow @2elearning s

      Want To Double Your Salary? Of Course You Do—Try This | Fast Company | Follow @2elearning s

      Research shows money (in the form of a paycheck) can buy happiness. Experts craft a game plan to double your salary.

      The best things in life may be free, but a study out of Case Western Reserve University found that money does indeed buy happiness. Increasing income—to the tune of an annual salary of $80,000— also relieves negative emotions and reduces the incidence of serious mental illness, according to the research.

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    11. Udacity plans to build its own open-source self-driving car | Follow @2Elearning

      Udacity plans to build its own open-source self-driving car | Follow @2Elearning

      Sebastian Thrun’s online education startup Udacity recently created a self-driving car engineering nanodegree, and on stage at Disrupt today Thrun revealed that the company intends to build its own self-driving car as part of the program, and that it also intends to open source the technology that results, so that “anyone” can try to build their own self-driving vehicle…

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