Deep Health

Deep learning is expected to be fully utilized for analyzing medical imaging data in the process of health diagnosis. Deep learning is a technology based on algorithms for self-learning and deduction as the human brain works, and it enables computers to learn by themselves, unlike the existing technologies involving artificial intelligence or machine learning. Deep learning-based image recognition is expected to enable more accurate cancer diagnosis than that provided by doctors, realizing an era of precision medicine with intelligent technology combined with personal genome data. Ultimately, the boundary between medicine and everyday life will be blurred, and the entire medical industry be redefined.

DNA image based on deep learning(Source : Pixabay.com)

Robo Internet

Cloud robotics enabling autonomous interaction between things and robots will define the direction of the IoT evolution. The IoT (Internet of Things) is projected to expand functions and intelligence of things and robots based on mutual connection. On the basis of “robo Internet,” which refers to the IoRT (Internet of Robotic Things) that converges the IoT and robots, a new ecosystem will emerge for intelligent devices that operate with data transferred through networks. The core technological elements of robo Internet include cloud robotics, the interface between things and humans, and autonomous control. As the combination of the IoT and robots will entail the accumulation and sharing of information about users’ habits and residential spaces, appropriate measures must be prepared in regard to issues such as standardization, privacy, and legal systems for humans and robots.

Teaching robot(Source : Ethz.ch

Drug Discovery Platform

Artificial intelligence used for the entire process of developing new drugs will reach the turning point of pharmaceutical research. As big data and artificial intelligence technologies are expected to have a significant influence on solving the challenges of new drug development, a number of global IT companies have begun competing for next-generation drug discovery platforms. For instance, Intel unveiled its plan in 2015 to invest a total of 50 million dollars for the next ten years in order to use quantum computers in solving challenges of drug development. In addition, start-up companies including Insilico Medicine, Atomwise, and Berg have begun to use independently developed intelligent drug discovery platforms as a means to expand their business through global collaborative research with medical institutions and universities. Information technology is expected to ultimately shift the paradigm of drug development and advance the revolution of human health.

New drug test tube(Source : Pixabay.com)

Super-fast Charging

Improved charging speed for secondary batteries is a core element to realize future core technologies such as electric cars and the IoT. Despite slow technological development, batteries are still the core element in areas of convergence in the future. As representative secondary batteries, lithium-ion batteries have seen annually improved energy density of around eight percent for the past two decades since their commercialization. The rate of performance being improved twofold every decade considerably lags behind the rate of IT performance being improved twofold every 18 months. Against this backdrop, the “flash batteries” recently developed by StoreDot can fully charge a smartphone within 30 to 40 seconds. Once this technology is commercialized to dramatically reduce the charging time of secondary batteries, electric cars will become popular and widely spread within a short period.

EV4 being charged(Source : Flickr.com)

Two Dimensional Nanomaterials

Computing devices based on graphene and black phosphorus are an alternative to overcome the limits of silicon chips. Sungkyunkwan University and the Korea Basic Science Institute have recently discovered that black phosphorus, has greater potential as a semiconductor device than the existing nanomaterials, and proved the possibility of realizing logic circuits based on new nanomaterials. As the performance of silicon-based computing devices is analyzed to have reached the physical limit, vigorous efforts are being made to develop logic circuits by using new alternative nanomaterials such as carbon nanotubes, graphene, and molybdenum disulfide. Although its zero band gap is a weakness of graphene, research to utilize the material for computing chips is expected to continue as the method of mass production has improved. In addition, computer simulation and big data will be used more actively for the purpose of accelerating the development of new materials.

Carbon nanotube(Source : Wikimedia.org)

Blockchain

The idea of a distributed trust mechanism and increased transparency will trigger innovation in financial and public sectors. Blockchain is a secure means to provide trade history to participants and prevent data forgery by comparing records whenever a transaction occurs. This technology is characterized by the absence of centralized servers to store ledger of transactions that have traditionally been kept by financial institutions. Providing trade transparency and anonymity, Blockchain is anticipated to drive the distribution of information and decentralization of power. The financial industry has already begun to actively use this technology for digital money and tradable assets of any kind. Blockchain will continue to bring a range of changes to non-financial industries and across society, prompting the emergence of safe and new innovative services and markets.

Replica of Bitcoin(Source : Flickr.com)

Data Capitalism

Technological and institutional alternatives must be prepared in order to tackle the monopoly and abuse of data, a new type of capital. Data is both a new form of capital and a dominant element of competition in intelligent social and economic systems. The ability to obtain and accumulate quality data will define market dominance. For instance, Google holds the monopolistic market dominance based on search history data accumulated thus far and is vigorously attracting new users through its search algorithms. If services with such market dominance increase and expand in the future, several issues for data economy will eventually arise in relation to data dominance as well as disclosure and utilization of data. As a result, it will be necessary to establish systemic countermeasures against threats such as privacy violations and data abuse or misuse.

Server room (Source : Flickr.com)