Technology has modernized the system of education for students with various disabilities, making it easier for them to keep up with academic curriculums and even compete with their peers in classrooms. According to Open Colleges, most of the common disabilities can be categorized into any of the following classification -- Physical (students using wheelchairs, prosthetic limbs, or dealing with diseases such as muscular dystrophy, Lou Gehrig's disease, multiple sclerosis, etc), Sensory (students lacking in normal visual, hearing or speaking abilities), Cognitive (students with weaknesses when it comes to memory, self-expression, information processing, and other learning disabilities), Psychiatric (students may suffer from an array of challenges, ranging from social phobias, bipolar and/or other personality disorders), Health-related (students who have chronic illnesses like cancer, diabetes or epilepsy) A Palestinian child reads braille during a class at Al-Nour, which translates'we have seen,' Rehabilitation Center for the Visually Impaired, in Gaza City, Gaza Strip, May 7, 2006. Students who suffer from any form of disability might find it difficult to attend classes regularly, keep up with everything that is being taught and compete at the same level with children who are not plagued by the same impairments that they have. These students often need some extra assistance when it comes to performing academically. One of the best forms of assistance in today's times is the gift of technology.
USA TODAY Tech columnist Kim Komando has tips for organizing your online photos. Improved cameras on smartphones are flooding our digital accounts with snapshots. Using the most basic digital or smartphone camera, you can shoot thousands of photos, dump them onto a computer, and then shoot thousands more. In seconds, you can edit a photo series in ways that would take days to develop in the darkroom. But our images are usually stored on our various devices, often leaving duplicates to sort through.
Artificial intelligence, Machine Learning, and Deep Learning are more than futuristic concepts. These technologies are impacting the insurance industry in a significant way right now and this impact is likely to increase in the near future. The idea of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) may fascinate consumers who enjoy talking to their digital while admiring a Nest thermostat. But for the insurance industry, these terms are business-changers that affect products and services offered and interactions with consumers and other industry partners. The definitions of these terms may be a bit confusing to the uninitiated (see sidebar).
Big Data was a big deal just a few years ago. Farmers worried about who had access to their data; farm groups worried about who owned a farmer's data; and the agribusiness sector was trying to figure out how to make money with data. Year after year, farmers were able to collect more and more data, but the practical benefits of all this data remained somewhat limited. Yield data was the first to be deeply analyzed and still remains one of the main reasons growers subscribe to data analysis services. Crop inputs were next as growers learned how to determine which inputs were needed, which performed well, and which actually were worth the investment.
Jefferson Graham tests the Google Pixel 2 XL smartphone camera--is it the best one ever, as some have said? He compares to the Apple iPhone 8 Plus in a beach shootout on #Talking Tech. LOS ANGELES -- OK Google, we love the new Pixel XL 2 smartphone as a camera, but alas, for photos and videos, our hearts go to the Apple iPhone 8 Plus. With each new smartphone release, critics are quick to dub a new one as the best mobile camera out there. We said just that last year about the then-new Google Pixel, which won our 2017 shootout.
With the revolution of machine learning, a new trend has come to town and it is called face recognition. When Apple announced its FaceID feature, everyone started talking and thinking about implementing face recognition everywhere – business, mobile apps, medicine, retail, and whatnot. But how can you be sure this technology is what you need without its thorough understanding? We'll tell you today what face recognition is, how it works, and what are the different use cases for this technology. Let's just say, after reading this article, you'll become a real Jedi of face recognition.
Motorola has announced a new Moto Mod for its Moto Z smartphones that brings Amazon's Alexa voice assistant. Called the Moto Smart Speaker with Amazon Alexa, the new Moto Mod allows users to experience Alexa like they have an Amazon Echo speaker wherever they are. The new Moto Mod was promised by Motorola and Amazon earlier this year. Back in February during the Mobile World Congress, the two companies revealed that they were working together to bring Alexa to Moto Z smartphones as a Moto Mod accessory. The new Amazon Alexa Moto Mod is pretty much what most would expect.
About a year ago, Adobe announced its Sensei AI platform. Unlike other companies, Adobe says that it has no interest in building a general artificial intelligence platform -- instead, it wants to build a platform squarely focused on helping its customers be more creative. This week, at its Max conference, Adobe provided both more insight into what this means and showed off a number of prototypes for how it plans to integrate Sensei into its flagship tools. "We are not building a general purpose AI platform like some others in the industry are -- and it's great that they are building it," Adobe CTO Abhay Parasnis noted in a press conference after today's keynote. "We have a very deep understanding of how creative professionals work in imagining, in photography, in video, in design and illustration.
This popular internet meme demonstrates the alarming resemblance shared between chihuahuas and muffins. These images are commonly shared in presentations in the Artificial Intelligence (AI) industry (myself included). But one question I haven't seen anyone answer is just how good IS modern AI at removing the uncertainty of an image that could resemble a chihuahua or a muffin? For your entertainment and education, I'll be investigating this question today. Binary classification has been possible since the perceptron algorithm was invented in 1957.
Hiding racy photos on your phone can be a tedious, manual affair. Depending on the app, you need to first select all the pics you want to move, move them and then delete them from your original cameral roll. That's not to mention making sure they didn't go to any automatic cloud backup locations like iCloud or Google Photos. A new app, Nude, aims to make the process a lot easier by scanning your photos for nudes, putting them in a private vault, deleting them from your camera roll and then erasing them from iCloud. All of this analysis is done on your iPhone, too, so no sensitive information hits the cloud.