Shamayita Acharya

By Deborah Borfitz, Senior Science Writer, Cambridge Healthcare Thinking about artificial intelligence (AI) has changed dramatically over time and has become about as hard to describe as art, says Jeff Fried, director of product management for data management company InterSystems. Machine learning (ML) is commonly considered a subset of AI—often a necessary component, in fact—but also encompasses methodologies such as logistic regression once referred to simply as statistics. The data is in any case “much more important than the algorithms, which are pretty much the same as they were 20 years ago,” says Fried. Data scientists spend most of their time choosing, gathering, combining, structuring, and organizing data so an algorithm can generate meaningful patterns. While the volume of digital healthcare data has grown exponentially, Fried says, accessing it can be a challenge due to ever-present security and privacy concerns and because it’s often locked in siloes—even across departm

By Lance Eliot, the AI Trends Insider Perhaps one of the oldest questions asked by humans is whether or not there is free-will. It’s up there with questions such as why we all exist, how did we come to exist, and other such lofty and seemingly intractable queries. If you are anticipating that I’m going to tell you definitively herein whether there is free-will or not, I guess you’ll have to keep reading, and the choice you make will determine the answer to your question. I’ll pause while you ponder my point. Okay, let’s get back underway. Well, since you are now presumably reading these words, I gather that you choose to keep reading. Did you make that choice of your own free-will? We generally associate free-will with the notion that you are able to act on your own, making your own decisions, and that there isn’t any particular constraint on which way you might go. Things get muddy quite quickly when we begin to dig deeper into the matter. As I dig into this, please be aware th

By James Hendler, Rensselaer Polytechnic Institute Artificial intelligence systems can – if properly used – help make government more effective and responsive, improving the lives of citizens. Improperly used, however, the dystopian visions of George Orwell’s “1984” become more realistic. On their own and urged by a new presidential executive order, governments across the U.S., including state and federal agencies, are exploring ways to use AI technologies. As an AI researcher for more than 40 years, who has been a consultant or participant in many government projects, I believe it’s worth noting that sometimes they’ve done it well – and other times not quite so well. The potential harms and benefits are significant. In an early success, the U.S. Department of Homeland Security in 2015 developed an AI system called “Emma,” a chatbot that can answer questions posed to it in regular English, without needing to know what “her” introductory website calls “government speak” – all the o

Walmart recently unveiled a new “store of the future” test ground for emerging technologies, including AI-enabled cameras and interactive displays. The store, a working concept called the Intelligent Retail Lab — or “IRL” for short — operates out of a Walmart Neighborhood Market in Levittown, N.Y. The store is open to customers and is one of Walmart’s busiest Neighborhood Market stores, containing more than 30,000 items, the retailer says, which allows it to test out technology in a real-world environment. Similar to Amazon Go’s convenience stores, the store has a suite of cameras mounted in the ceiling. But unlike Amazon Go, which is a grab-and-go store with smaller square footage, Walmart’s IRL spans 50,000 square feet of retail space and is staffed by more than 100 employees. Plus, in Walmart’s case, these AI-powered cameras are not being used to determine which items customers are buying in order to automatically charge them. It still has traditional checkout stations. Instead,

Data mining and clustering are closely interlinked. They both focus on the pattern recognition underlying a particular dataset. Mainly, it’s a joint effort of machine learning, pattern recognition and statistics. They help in discovering patterns in data. Clustering is one of the various methods of data mining. What is clustering in data mining? Generally, the mining of data ends up at spotting the pattern. If you talk about clustering in particular, it’s an unsupervised data mining method that splits the data into natural groups. In other words, clustering is the statistical distribution of data into subclasses. Each subclass showcases a group of similar objects.  It’s a kind of unsupervised algorithm. Let’s consider this example to clarify its meaning. When you type a phrase in Google, it immediately monitors. Whenever you browse it again, it lines up an array of ads that are motivated by your previous search. Its bots take a few minutes to scan what you explored. Likewise, m

The benefits of AI for healthcare have been extensively discussed in recent years up to the point of the possibility to replace human physicians with AI in the future. Both such discussions and the current AI-driven projects reveal that Artificial Intelligence can be used in healthcare in several ways: AI can learn features from a large volume of healthcare data, and then use the obtained insights to assist the clinical practice in treatment design or risk assessment; AI system can extract useful information from a large patient population to assist in making real-time inferences for health risk alert and health outcome prediction; AI can do repetitive jobs, such as analyzing tests, X-Rays, CT scans or data entry; AI systems can help to reduce diagnostic and therapeutic errors that are inevitable in human clinical practice; AI can assist physicians by providing up-to-date medical information from journals, textbooks and clinical practices to inform proper patient care; AI can

By Melissa Pandika, Science Writer A viral video of what appears to be Barack Obama provided a chilling glimpse into the growing power of fake news when it was released last April. It opens with Obama warning viewers about how America’s enemies “can make it look like anyone is saying anything at any point in time.” At about the halfway mark, a split screen reveals director Jordan Peele impersonating Obama, who has merely been mouthing his words. Peele’s production company created the video with Adobe After Effects, a motion graphics software, and FakeApp, an AI-powered face-swapping app that resynthesized Obama’s mouth to be consistent with the audio track of Peele’s voice. The video played before a packed auditorium at the University of California, Berkeley to kick off a panel session at the recent TechCrunch event on Robotics + AI. Moderated by TechCrunch writer Devin Coldewey, the panel brought together two leading experts in AI and synthetic imagery to discuss the reality we now

We extol the virtues of robots and AI quite a bit on this blog, and rightfully so; beyond serving as one of our competitive advantages in innovative solution design and development, it’s also one of the most exciting frontiers in modern computer science (which at this point is to say, the modern world). But as with any level of automation, one of the first questions to follow (again, rightfully so) is whether or not these advancements will mean an end to thousands or millions of jobs. The good news is that humans are still too good at too much for AI to replace many of the jobs it might have had in its crosshairs. The better news? Robots and AI together might be able to eliminate many of the more tedious, time-consuming or boring tasks away from our jobs. Wouldn’t that be swell? Robots and AI fall short alone “We fleshy beings remain more creative, more dexterous, and more empathetic—a particularly important skill in health care and law enforcement,” according to Matt Simon over

We all know that growing your business is a necessity in order to stay in the game. However, there's more involved in the process than simply marketing to get more loyal customers through your front door. With the technology that we use, it's important to understand how to manage the data of your business as you continue to expand your customer base. Here are some great tips that you can start utilizing today to prepare for better data management in the future.  Know What Your Constraints Are While we all would like to have the fastest car in the world, most of us simply can't afford it due to our financial constraints. Sure, there are data management systems out there which can handle your business data to pretty much infinity, however, you must assess your business constraints to see what you can actually obtain. Cost is going to be the biggest of your constraints. How much money do you actually have to invest in a new data management approach? Second, think about the

This is an abstract of my presentation in Dubai on the 23rd April 2019. In 2016 in my article “ The future of “The Internet of Olympic Games”, I considered Rio as the first Internet of Things (IoT) Olympic games. In Rio, we saw how athletes, coaches, judges, fans, stadiums and cities benefited from IoT technology and IoT solutions and this somehow changed the way we see and experience sports.  Next year we will have the opportunity to verify if my predictions for Tokyo 2020 will become a reality and we will name Tokyo as the first Artificial Intelligent (AI) Olympic Games. During my presentation in Dubai, I explained the audience the incredible way IoT and AI technologies are impacting sports. I dedicated some time explaining how IoT and AI are playing an increasingly significant role in boosting talent, managing health and improving coaching and training.  Today these technologies are already enabling athletes to improve performance, coaches to better prepare games, judges to fail

By Lance Eliot, the AI Trends Insider A friend of mine in college was known for being very stoic. You could tell him that you had broken your leg skiing and he’d show no emotion. He’d just sit there and stare at you. No words came forth. No expression on his face. You might tell him that your dog got run over, and he’d continue to be without any kind of emotional response. I believe that if you told him that his dog got run over, he’d have the same kind of non-reaction, though I suppose he might be curious enough to ask how it happened. Some of us thought that he had watched way too many Star Trek TV shows and movies. He had become our version of Mr. Spock, the fictional character that generally showed little or no emotion. In case, you’ve been living in a cave and aren’t familiar with Star Trek, Spock was the science officer and first officer. To some degree, it was implied that his linage of Vulcan heritage allowed him through training and DNA to remain impartial and detached,