Even though predictive analytics has been around for quite some time, interest around this topic has increased over the last couple of years. It is no longer enough for a company to accurately record what has happened. Today, an organization's success depends on its ability to reliably predict what will happen – be it predictions about what a customer is likely to buy next, an asset that could require maintenance, or the best action to take next in a business process. Predictive analytics uses (big) data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data, enabling both optimization and innovation. Existing processes can be improved – for example by forecasting sales and spikes in demand and enabling the required adjustments to the production planning.
Technology is filled with buzzwords that come and go. However, three key ideas that have grown in stature and relevance over recent years are blockchain technology, artificial intelligence and the internet of things. These three emerging technologies represent different aspects of the data world, and 2018 may be the tipping point in their convergence. Three different pieces of technology will start working together in a seamless ecosystem, and the result is a more connected, more efficient and more secure world. The Internet of Things (IoT) world may be exciting, but there are serious technical challenges that need to be addressed, especially by developers.
In the latest of our Predictions series we take a look at what the future of healthcare will look like. Could artificial intelligence and smart technology improve every stage of our lives? We look at how the future of healthcare will affect us from birth including wearable tech and the internet of things to capturing baseline health data we can use to monitor our health as we grow older. From womb to tomb Health scanning and data will become ever present in our lives – even from the very start of life. Before birth, scanning will take place in the womb which will create a basic profile of a person's health and create treatment plans from the very start.
Emerging technologies are finding their way into everyday life as they mature and gain acceptance. But that doesn't mean they're without risk. The CERT Division of the Software Engineering Institute at Carnegie Mellon University once again has updated its list of technologies that might present challenges from an information security and safety perspective. In its Emerging Technology Domains Risk Survey, CERT examines a variety of trends that can provide a lot of benefits to people and businesses, but also pose risks that need to be addressed. Some of these areas are moving ahead so quickly in adoption that companies have not had a chance to completely evaluate their implications.
The Internet of Things (IoT) is at the heart of modern big data. It's what allows companies, and even cities, to collect endless quantities of information with minimal effort – and to act on that information, monetizing it, basing decisions on user data. Right now, though, IoT is on the edge of change because there's a new kid on the scene: 5G connectivity. Now phones act like computers and the competition for the next cutting edge innovation is stiffer than ever. As of this writing, 5G wireless technology is not yet ready to launch but the competition to bring it to market is stiff.
Alphabet Inc., Facebook Inc., Amazon.com Inc., Apple Inc. and others are hunting for new areas of growth--often on each other's turf--as they enjoy soaring revenues and stock prices. They are poised to bump into each other across the board, in online sports viewing, movies, news and even podcasting. Up for grabs is an extra $300 billion a year in revenues that Activate projects will flow into the $1.7 trillion global consumer media and internet market by 2021, through growing internet-access fees, ads and paid content. Activate estimates the market will grow 4.1% a year. Consumers' time, though, is already stretched, with young people in particular tethered to devices much of the day.
The concept of an Internet of Things (IoT) sounds futuristic, conjuring an image of a vast network of connected devices that are actively monitoring the world to give us much greater control over almost everything. But the reality is that the IoT is already here. According to Gartner, there are currently more than 8 billion individual devices connected through the Internet. This is more than twice the number of people online (about 3.7 billion), and more than the total global population (7.5 billion). What are all these connected things?
Last year, researchers at MIT set up a curious website called the Moral Machine, which peppered visitors with casually gruesome questions about what an autonomous vehicle should do if its brakes failed as it sped toward pedestrians in a crosswalk: whether it should mow down three joggers to spare two children, for instance, or veer into a concrete barrier to save a pedestrian who is elderly, or pregnant, or homeless, or a criminal. In each grisly permutation, the Moral Machine invited visitors to cast a vote about who the vehicle should kill. The project is a morbid riff on the "trolley problem," a thought experiment that forces participants to choose between letting a runaway train kill five people or diverting its path to kill one person who otherwise wouldn't die. But the Moral Machine gave the riddle a contemporary twist that got picked up by the New York Times, The Guardian and Scientific American and eventually collected some 18 million votes from 1.3 million would-be executioners. That unique cache of data about the ethical gut feelings of random people on the internet intrigued Ariel Procaccia, an assistant professor in the computer science department at Carnegie Mellon University, and he struck up a partnership with Iyad Rahwan, one of the MIT researchers behind the Moral Machine, as well as a team of other scientists at both institutions.
In 2016 it got exponential growth over 2012 and 2017 figures till Sept equally critical is delivering this performance with reduced silicon (all grey & thin areas) area and industry power consumption. Machine learning helps in reducing the required efforts bandwidth between the buyer, seller and manufacturers such bandwidth reductions also reduce the cost and required time. In eCommerce AI based technologies like Big Data, Machine Learning, Neural Networks, Data Science, Bots and Deep Learning (mainly for secured online payments) are currently buzzwords. To safe guard the business from anti social elements deep learning helps in fraud detection, prevention, velocity measure and makes better business decisions with deep understanding of entity resolution (avoid multiple accounts of same person), Image recognition and understanding, Concept extraction, sentiment and trend analysis makes buyers life easy to choose and buy.
Imagine AI, current AI, not some AI in the future, being able to identify a perfect stacked, ranked list of every person in the country who works against whatever your agenda is from top to bottom. Imagine AI, current AI, not some AI in the future, being able to identify a perfect stacked, ranked list of every person in the country who works against whatever your agenda is from top to bottom. GLENN: Well, and imagine -- we know that AI -- we know that a year or 18 months ago, we heard AI imitate the voice of Barack Obama, Bill Clinton, and I think Hillary Clinton. You want to start Civil War, show Donald Trump meeting with Vladimir Putin and -- and show him doing all kinds of wicked plans against the United States.