There is no doubt that there are currently three trends in the business model: Internet of Things (IoT), Big Data, and Artificial Intelligence. From the still fragmented Internet of Things, to the rapidly fluctuating computing paradigm, and even how AI reshapes our way of life, everyone is talking about these trends, but what is really happening?
The following is the understanding of these things need to understand the truth, as well as from the consumer perspective to see the future picture.
Big Data
As Wikipedia defines it, the term big data says that the data is so big and complex that it can't be handled by traditional data processing applications. Given this large data set, related challenges include capture, storage, analysis, data planning, search, sharing, transmission, visualization, querying, updating, and information privacy. However, it is often more meaningful to relate it to predictive analysis, user behavior analysis, and advanced data methods (including artificial intelligence) than to simply emphasize the size of the data set.
In 2017, it is expected that there will be application of blockchain technology, especially smart contracts that write contracts into general ledger system codes. These forms of contracts tend to be more secure and irrevocable than traditional contracts, but they also create efficiency in citing and implementing these contracts.
In addition, the rise of data-as-a-self-service solutions will also allow organizations to analyze their data without the need to establish a data science department. This will be extremely useful for SMEs because they do not need to recruit highly expensive data scientists this 2016 high demand job.
Hadoop, the framework that allows distributed processing of large data sets, has seen a rapid decline as it has proved challenging to recruit qualified people to support this framework. Now people seem to prefer to use cloud-based applications to reduce the data center's expenses, so the data, namely self-service model, has become popular.
As researcher Gartner pointed out in the Magic Quadrant of Analytic Data Management Solutions, “The current expectation is to move to the cloud as an alternative deployment option because cloud solutions have flexible, agile, and viable pricing models.†Because of this, Companies are empowering their employees with appropriate knowledge of structured and unstructured data. It is expected that the following insights for middle managers will also become more accessible.
But this is a double-edged sword, because the evolution of big data technology will also lift the appetite of the supervisors. These people will expect to get their own data right away instead of waiting for batch analysis reports to come out. So the pressure on the analysts will get bigger, because the higher level expects faster, near-real-time, actionable analysis.
Internet of Things
Forbes described the concept of the Internet of Things as connecting any switched device to the Internet (and/or to each other). If the device has a switch, it may be configured as part of the IoT.
You can think of a "smart home" device as a lock that turns on when it detects that your phone is nearby, or perhaps it can be thought of as a light that will only light up when motion is detected.
In 2016, we witnessed a large number of suppliers launching many similar solutions. In 2017, we can expect some of these suppliers to triumph, and this will mean that the market will eliminate a group of suppliers. With the reduction in the number of suppliers, we can also expect that regulation and normalization will come into play, leading us to a simpler and more cohesive solution. However, security issues will follow, as a cyber attack on IoT last year led to a grid collapse in West Ukraine. Of course, research on hacking attacks on unmanned vehicles may also cause concern, so security measures may be taken against IoT in 2017.
The current IoT market is still highly fragmented, but hopefully the next picture will become clearer as 2017 progresses, and IoT solutions will become more integrated and become part of an open ecosystem and platform. This promotes interoperability and provides services based on data from multiple devices and sources.
IoT will focus on two areas of application, one is a smart city and the other is a smart home. However, given that bandwidth is a prerequisite for any IoT technology, it is expected that there will be a simpler mesh or mesh-like product for future management this year.
This is what Errett Kroeter, vice president of brand and developer marketing at the nonprofit Bluetooth Special Interest Group, hopes: “Now some of the grid's standards are notoriously difficult to set up. Our goal is to keep the grid simple, Everyone is willing to use them."
Finally, the growth of IoT, coupled with the massive amounts of data generated by other devices and systems, is accelerating the demand for artificial intelligence because it creates meaning from the information.
artificial intelligence
Artificial intelligence's call definition is the machine's ability to imitate human behavior. Although we witnessed the rapid development of AI in 2016, this growth will further deepen in 2017. In 2016, we learned that Amazon's Alexa, the artificial intelligence that can be expressed in the form of human language, has reached more than 5 million households. You can ask Alexa about the weather or ask her to call you a taxi. She will respond. This means that AI has entered the mainstream adoption stage last year.
However, artificial intelligence also has many advances in health care. Focused healthcare AI startups have grown from around 20 in 2012 to nearly 70 in 2016. Among the notable ones are apparently the iCarbonX, which aims to establish a digital living ecosystem, to provide a personalized health management system, and Flatiron Health, which aims to fight cancer with organized data and help oncologists enhance health care.
In health technology giant Philips, about 60% of researchers, developers and software engineers are working on healthcare informatics, and a large part of them are seeking to apply artificial intelligence in current and future healthcare innovations.
The trend of healthcare that can still be highly intelligent is mainly focused on imaging and diagnostics, using AI to help find subtle details and changes that people can't see. This piece has increasingly become a crowded plate. However, the use of large data sets to help healthy people, high-risk groups, or chronic disease groups to prevent health deterioration is also a concern in this area.
According to Jeroen Tas, chief innovation and strategy officer at Philips, “AI plays a valuable role in supporting radiologists to prepare relevant information for cases and identify subtle changes in patients. Another area is the intensive care unit where AI can help identify Deterioration of the condition or early signs of serious events, such as sudden cardiac arrest or pregnancy."
Tas also believes that “combining genetic information with pathology, medical imaging, laboratory results, family history data, other situations, and previously effective or ineffective treatment options, etc., can lead to a richer picture of patients. This data can be organized. Together, with the help of AI, add important background information to help clinicians make more accurate diagnoses and provide support for personalized treatment options."
A multidisciplinary team of software engineers, designers, and other experts appears to have created and introduced the first feasible application for radiologists. In remote patient monitoring, AI can promote virtual companions and introduce virtual nurses.
Outlook after 2017
The Internet of Things, big data, and AI are all thriving, and are getting closer to commercial and large-scale use cases.
As these technologies enter the daily lives of ordinary people, in order to provide more powerful and more rationalized products, the convergence of these three trends will become imperative.
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