The term artificial intelligence (AI) was first coined by J. McCarthy at the Dartmouth Conference in 1956. Simply put, AI is technology that artificially creates human intelligence. The scope of AI study has continuously expanded, starting off with the notion of ‘computationalism’ to the more recent ‘connectionism’. Computationalism first emerged as people began to develop computers with the aim of creating machines capable of performing intellectual activities like human beings. However, there were many limitations, especially since machines are unable to communicate with humans. This later gave way to connectionism. As opposed to computationalism, connectionism argues that AI can construct artificial neural networks to imitate the human brain and continuously reduce human errors by identifying similar patterns. Connectionism has been instrumental in bringing about major achievements in the field of AI, including Google's AlphaGo, IBM's Watson and Apple's Cortana.
Artificial intelligence technology will naturally bring about
changes in the way of life. First, it will change people’s consumption
patterns and product marketing strategies. In the past,
consumers decided to buy a product because of its functions but
now, they do so because of the services offered by AI technologies.
As a result, the service industry will become more important
than the manufacturing industry.
For example, when Apple and Google provide services for
autonomous vehicles, the question will not be whether the car
runs well on the road, but rather what kind of smart services can
it provide for its users. In addition, focusing on electric vehicles
(IBM) IBM developed an artificial intelligence system called
Watson. As of the first half of 2016, more than 3,500 partners
are participating in developing Watson, and more than 270
applications are being commercialized. These major companies
include ANZ (Australia), Bumungrad (Thailand), CaixaBank
(Spain), Metropolitan Health (South Africa) and Red Ant. IBM
is trying to formulate a Watson-centered ecosystem that can provide
real-time data analysis services to users.
(Google) Google is developing AI technologies to upgrade its
engine and develop new applications. Areas of application
include home automation (Nest), automobiles (Google car),
voice recognition (Google Now) and photo recognition (Google
Photos). Google's ultimate goal is to become an artificial intelligence
company itself. In order to develop its artificial intelligence
engine, Google is focusing on securing relevant technologies
mainly through the acquisition of start-ups in the field of
recognition (video, face, gesture), natural language processing
and machine learning (deep learning), while developing its own
artificial intelligence engine.
(Apple) It wasn’t until recently that Apple established optimum
grounds for technological development in the field of artificial
intelligence. The company is now developing technologies
only in specific fields such as virtual assistance and automo-
biles. Apple recently hired a large number of researchers (86
people) to integrate artificial intelligence into the field of personal
assistance. It’s thus working hard to build a strong environment
for technological development and securing technological
competitiveness by acquiring start-ups like VocalIQ and
Perceptio. In October 2015, when these two firms were
acquired, Apple CEO Tim Cook said he would develop and
integrate technologies only in the areas where they could prove
to be competitive.
(Facebook) Facebook is developing technologies focusing on
image, sound and natural language processing with a strategy to
make the network smarter and more personalized. In December
2013, Facebook presented the possibility of applying artificial
intelligence technology to its services by recruiting Professor
Yan Le Cun from New York University, an eminent professor
in the field of deep learning technology. The company acquired
Wit.ai, a speech recognition startup in January 2015, and
released a virtual assistant deploying AI technology “M” to the
public in August 2015. Facebook is developing technologies
largely focusing on drones, artificial intelligence and VR technology.
It is also deploying strategies to make its social media
applications available anywhere in the world.
To sum up the business strategies of major AI developers,
there are three general trends: the support of enterprises, the
strengthening of its own applications and the exploring of new
business domains. When it comes to supporting enterprises,
IBM is the most well-known for developing various applications
for Watson. The second strategy is to develop the company’s
own applications. Google, Apple and Facebook are following
this strategy as they have developed or are developing a personal
assistant service to captivate their users and to make them
use their services at all times. Thirdly, the example of the business
expansion strategy is Google and Apple’s attempt to develop
autonomous vehicles. These companies are using artificial
intelligence to explore a new business domain that they have
never set foot in before.
(Samsung Electronics) The company introduced 'S Voice', a
smartphone application with voice recognition technology. It
focuses on developing stable voice recognition technology
which specializes in natural language processing. It is also
developing technology with quality speech recognition, even in
a noisy environment.
(NAVER) Through the use of artificial intelligence, NAVER
currently provides users with various functions like N Drive and
auto-complete function. When users upload pictures in the
cloud system, N Drive automatically classifies and places them
in various categories like animal, food, and text. With the autocomplete
function, certain search suggestions pop up on the
search box as users type in the first few letters based on analysis
of their past search results. Internet service providers (for portal,
mailing, backup, etc.) such as Google and Apple are developing
this technology as their core technology.
(Hyundai Motors)Since 2010, the company has aggressive-
ly expanded its development of autonomous vehicles. In 2012,
it succeeded in developing a highway driving support system.
Based on images, voice recognition and deep learning technology,
the highway support system includes functions such as lane
departure warning, lane keeping assistance, rear side warning,
vehicle speed control and autonomous emergency braking.
(NCSOFT) NCSOFT established its own AI center, consisting
of the artificial intelligence lab and the natural language
analysis lab in 2012. In the artificial intelligence lab, researchers
are finding ways to combine deep learning technology with the
company’s gaming system to adjust the level of difficulty
according to the skills of the user. In the natural language analysis
lab, researchers are mainly developing technologies converting
recognized voice into text to facilitate NPC(non-player
character)-to-user and user-to-user communication.
But it’s not only major companies that are developing their
AI systems; SMEs and start-ups are as well. Although they have
yet to commercialize their products, various SMEs and startups
are developing technologies to apply AI and increase the efficiency
of their applications. The number of SMEs developing
AI technology is also increasing because there is demand from
the government and big corporations. DIOTEK, Cldi, UBIC,
KonoLabs, Lunit, Standigm and MindsLab are newly-rising
players and they are gaining attention in the market.
According to the Ministry of Science, ICT and Future Planning, which cited Hyundai Research Institute, the global AI market will grow from KRW 3.6 trillion (USD 3.1 billion) in 2013 to KRW 6.4 trillion (USD 5.4 billion) in 2017. KT Economic Management Research Institute predicted that the market will grow to KRW 27.5 trillion (USD 23.4 billion) by 2030. It is expected that the domestic AI market will increase following such global trends, but there will be no dramatic changes because the industry is still in its infant stage.
Although the government has initiated projects such as Exobrain and DeepView with an aim to develop core artificial intelligence technologies, there are still some hurdles to get through to revitalize the AI industry. First, more diverse participants should participate in the process of developing technologies. This will not only increase supply but also demand for relevant technologies. Second, more efforts should be put on creating a code of ethics or moral standards for artificial intelligence, as opposed to the primary focus having been put on developing applications. Third, unnecessary regulations should be adjusted or eradicated in advance.
