Science and technology trends not to be underestimated in the 2015

Is your company going to create the next Uber miracle? Have you ever imagined how you could use encrypted electronic money to enhance your company's digital security system? Have you considered that the algorithm your company uses may inadvertently lie to you?

At the end of the year-end, I applied a set of screening methods to find out some of the most important emerging trends in the field of digital media and technologies that are moving towards maturity. It analyzes consumer behavior patterns, microeconomic trends, government policies, market roles, and upcoming research projects in the context of our evolving technology and digital media ecosystems. My colleagues and I are working with a set of 5 core attributes: Ambivalence, transition, singularity, contingency, and contravariance, to find emerging signs that help us identify trends that may be coming out of the horizon. We then ask the following five questions for each trend:

1. Where do people waste their time?

2. where/How do people encounter technical difficulties?

3. Where do people find information?

4. where/How are people stuck?

5. How do people want to be perceived?

These 5 questions help us to assess the quality and quantity of a trend that can be maintained indefinitely. We also stress-test the ideas that are triggered by the trends we identify. The 2015-year trend we've screened, along with some extraordinary new challenges, provides significant opportunities for managers in all walks of life. Here are 6 notable trends.

Deep learning: AI computers can now use neural networks for deep learning, and you can interpret neural networks as a computer system that is inspired by the workings of the brain to translate pixels into English. At the end of 2014, Google researchers unveiled a new project that uses neural networks and depth learning to identify multiple elements of a scenario without the need for artificial assistance. Its software can "learn" how to think by handling massive amounts of data. For example, deep learning will eventually enable the robot to identify objects that have never been seen and navigate to new locations. Deep learning runs through many areas, and it will play a role in manufacturing, healthcare, retailing, public utilities and other industries in the near future.

Intelligent Virtual Personal assistant SPVA: A variety of SPVA applications began to appear on the market since 2013. At the time, they used semantics and natural language processing, data mining for our schedules, emails, and contacts, and our last few minutes of behavior to predict what we would think about for the next 10 seconds. Most of these original apps have been acquired. Google bought EMU, Yahoo bought Donna, Apple bought cue ... and other acquisitions are not listed here. During their active period, EMU was the embodiment of a private secretary. It monitors the conversation and automatically makes suggestions when both sides of the conversation enter text. For example, if you want to invite your friends to watch a movie, EMU will immediately position you, suggest a nearby cinema, show a list of movies and time, and then check your schedule to find out what your common hours are. It will even present a preview for you to see. Once it has identified your most appropriate meeting time, it will help you to purchase the tickets and enter all the data into your schedule. All of this is done by a single mobile application software. From 2015 onwards, consumers will see SPVA technology implanted in their phones. Google, for example, is starting to quietly release a new SPVA feature to Android users, and when you dock your car, it automatically senses the location you're parked on your Google Maps and then helps you get back to the dock when you need to drive. You don't have to give a clear instruction, it can do it all. It applies to marketers, credit card companies, banks, local government affiliates, political propaganda, and, more often, SVPA can be easily steered in order to deliver critical information and better investigate public sentiment.

More different types of companies emulate the Uber model: In spite of criticism of its way of doing business, 2014 is still a bumper year for Uber. This simple mobile application, which is used to connect drivers and passengers, is now valued at $40 billion trillion, surpassing the general Mills of Halliburton Halliburton Corporation, Aetna Aetna, Universal Mills, Delta Airlines, Kraft food Kraft Foods, Ka Shin Financial management Charles Schwab and other companies. Uber's rapid growth is attributed to the fact that consumers have adopted it at lightning speed because Uber has performed well in two ways. First, it allows people to make extra money in their spare time. Professional drivers can find passengers quickly and conveniently through Uber. It has long been a boon to those who have lost their jobs, offering them the opportunity to earn money when jobs are nowhere to be found. Second, Uber provides a perfect payment interface. Passengers are not required to carry cash or credit cards, and the entire transaction process is done through a simple mobile interface. Uber's success has inspired hundreds of entrepreneurs who want to emulate its most salient features. 2015, a large number of companies imitating the operation of the Uber operating mode of delivery and intermediary business will emerge, such as the rapid delivery of food and miscellaneous goods, helicopter passenger transport, portable automatic teller machines, liquor delivery, door-to-door massage, dry cleaning and washing, iphone repair, private shopping, medicinal marijuana, dog walking, Car Trouble Rescue and other business. At the same time, consumers will click on the "one-click completion" button in the background payment program, which means that retailers, transport companies, and banks, which have a good reputation, can take advantage of this convenience habit.

Oversight of algorithms: a set of algorithms is simply a set of codes or processes that must be followed to find a way to solve the problem. In the new year, we also have to ask the question: How to use the algorithm to do not touch the moral bottom line? We also need to examine the tendency of some algorithms to go awry. Programmers add subjective judgments to the algorithm to come up with an answer, which leads to more and more objects, data, and even people being incorrectly categorized in large data spaces. As a result of algorithmic errors, there have been many instances of mistaken identification of terrorist suspects at multiple airports. High-frequency trading algorithm once put the stock market cornered. An algorithmic error on Amazon's web site led to the price of a book called The Making of a fly:the genetics of Animal, which soared to 26,698,655 $93. Over the next few months, managers will have to discuss how to introduce accountability systems for algorithms.

Data privacy: The proliferation of privacy violations continues to destroy public trust. According to the Pew Research Center's poll of the Internet and society, 91% of Americans agree or strongly agree that consumers have lost control of their personal information and data. Perhaps because of the fear of third parties monitoring our use of mobile phones, or perhaps the security of online transactions, people are increasingly worried about their privacy, targeting companies rather than malicious hackers. In the 2015, companies were not only trying to keep the data encrypted, but also to make public the measures taken to protect our privacy. 2015 has a particularly noteworthy area: digital consent. Lawyers will soon be able to cite our privacy as evidence against us in court. In 2014, the Fitbit of the wearable Activity Tracking system, which was used in court as a "proof of evidence" after being processed by a third-party analysis tool, began to investigate Fitbit's practice of selling personal privacy to advertisers. We will witness the growth in demand for digital consent and the increase in transparency.

Block chain technology in distributed database: the so-called block chain refers to the transaction database that is shared by the participants of the "Bitcoin digital system". With this technology, encrypted electronic money guarantees complete anonymity when used by the public-supervised general ledger system. It can be understood as a distributed consensus system in which individuals cannot gain control over all data. Even if Bitcoin itself has not really grown, block chain technology is still promising. For example, it was argued that if the company used block chain technology, there would be no widespread disclosure of credit card information. A new company, called Blockstream, plans to use block chain technology to build a common platform that applies to any situation where signatures and identities need to be identified. It allows people to participate in "untrusted" transactions, which are done in collaboration with both buyers and sellers, as well as intermediaries such as third party trustees, trustees or other intermediaries.

In the coming year, these trends will have an impact on your business in some way. The best way to guard against the impact is to learn as much as possible, discuss the hidden possibilities with colleagues in your company, and then commit to launching a small in-house experiment to help you discern trends.