Patent Analysis for Technology Development of Artificial Intelligence: A Country-Level Comparative Study

Innovation ◽  
2012 ◽  
pp. 1366-1385
Author(s):  
Chun-Yao Tseng ◽  
Ping-Ho Ting
2021 ◽  
Vol 65 (8) ◽  
pp. 51-60
Author(s):  
Yujeong Kim

Today, each country has interest in digital economy and has established and implemented policies aimed at digital technology development and digital transformation for the transition to the digital economy. In particular, interest in digital technologies such as big data, 5G, and artificial intelligence, which are recognized as important factors in the digital economy, has been increasing recently, and it is a time when the role of the government for technological development and international cooperation becomes important. In addition to the overall digital economic policy, the Russian and Korean governments are also trying to improve their international competitiveness and take a leading position in the new economic order by establishing related technical and industrial policies. Moreover, Republic of Korea often refers to data, network and artificial intelligence as D∙N∙A, and has established policies in each of these areas in 2019. Russia is also establishing and implementing policies in the same field in 2019. Therefore, it is timely to find ways to expand cooperation between Russia and Republic of Korea. In particular, the years of 2020and 2021marks the 30th anniversary of diplomatic relations between the two countries, and not only large-scale events and exchange programs have prepared, but the relationship is deepening as part of the continued foreign policy of both countries – Russia’s Eastern Policy and New Northern Policy of Republic of Korea. Therefore, this paper compares and analyzes the policies of the two countries in big data, 5G, and artificial intelligence to seek long-term sustainable cooperation in the digital economy.


Author(s):  
Gyanendra Mohan Patel ◽  
Anupam Singh ◽  
Tanishka Bhala ◽  
Aryaman Jora ◽  
Divyansh Chandna

2017 ◽  
Vol 6 (3) ◽  
pp. 57 ◽  
Author(s):  
Amit Patil ◽  
Marimuthu K ◽  
Nagaraja Rao A ◽  
Niranchana R

Before chatbots there were simply bots: The invention of a chatbot brought us to the new era of technology, the era of conversation service. A chatbot is a virtual person that can effectively talk to any human being with the help of interactive conversion textual skill. Now a days there are many cloud-based platforms available for developing and deploying the chatbot such as Microsoft bot framework, IBM Watson, Kore, AWS lambda, Microsoft Azure bot service, Chatfuel, Heroku and many more but all those techniques has some drawbacks such as built-in Artificial Intelligence, NLP, conversion service, programming etc. This paper represents the comparison between all cloud-based chatbot technologies with some constraint such as built-in AI, setup time, completion time, complexity etc. Finally, by the comparison, we will get to know that which cloud platform is efficient and suitable for developing chatbot.


2020 ◽  
Vol 2 (1) ◽  
pp. 4-18 ◽  
Author(s):  
Francesco Contini

The paper connects the potentially disruptive effects of Artificial Intelligence (AI) deployment in the administration of justice to the pre-existing trajectories and consequences of court technology development. The theoretical framework combines Luhmann’s theory of technology with actor–network theory to analyse how the new digital environment affects judicial agency. Then, it explores law and technology dynamics to map out the conditions that make legal the use of technologies in judicial proceedings. The framework is applied to analyse ‘traditional’ digital technologies (simple online forms and large-scale e-justice platforms) and AI-based systems (speech-to-text and recidivism assessment). The case comparison shows similarities and dynamics triggered by AI and traditional technologies, as well as a radical difference. While system developers and owners remain accountable before the law for the functioning of traditional systems, with AI, such accountability is transferred to users. Judges—users in general—remain accountable for the consequences of their actions supported or suggested by systems that are opaque and autonomous. This contingency, if not adequately faced with new forms of accountability, restricts the areas in which AI can be used without hampering judicial integrity.


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