Simultaneous Interpreting (SI): the Holy Grail of Artificial Intelligence – An SI Practitioner’s Perspective

2017 ◽  
Vol 62 (2) ◽  
Author(s):  
Ailing Zhang
Keyword(s):  
Artificial Intelligence ◽  
Computer Program ◽  
Image Recognition ◽  
Human Performance ◽  
Rapid Progress ◽  
Holy Grail ◽  
Simultaneous Interpreting ◽  
The Past ◽  
World Class ◽  
Near Future

AbstractArtificial Intelligence (AI) has been become a household expression, especially in the past couple of years thanks to Google’s AI Computer program AlphaGo defeating a couple of world-class Go masters from Korea and China. In recent years, machines have surpassed humans in the performance of certain specific tasks, such as some aspects of image recognition. Although it is unlikely that machines will exhibit broadly-applicable intelligence comparable to or exceeding that of humans in the near future, experts forecast that rapid progress in the field of specialized AI will continue, with machines reaching and exceeding human performance on an increasing number of tasks. Simultaneous interpreting, being among the most complex of human cognitive/linguistic activities, with all the associated ergonomic elements, has been discussed profusely as one of the most likely to be taken over by AI in a couple of years. Given that so much has to be there simultaneously, i. e. anticipation, restoration of the implicit-explicit balance, and communicative re-packaging (‘re-ostension’

scholarly journals Robotics and Artificial Intelligence

2020 ◽  
Vol 10 (2) ◽  
pp. 57-78 ◽  
Author(s):  
Estifanos Tilahun Mihret
Keyword(s):  
Artificial Intelligence ◽  
At Risk ◽  
Human Beings ◽  
The Past ◽  
Near Future ◽  
And Robotics

Artificial intelligence and robotics are very recent technologies and risks for our world. They are developing their capacity dramatically and shifting their origins of developing intention to other dimensions. When humans see the past histories of AI and robotics, human beings can examine and understand the objectives and intentions of them which to make life easy and assist human beings within different circumstances and situations. However, currently and in the near future, due to changing the attitude of robotic and AI inventors and experts as well as based on the AI nature that their capacity of environmental acquisition and adaptation, they may become predators and put creatures at risk. They may also inherit the full nature of creatures. Thus, finally they will create their new universe or the destiny of our universe will be in danger.

scholarly journals Robotics and Artificial Intelligence in Gastrointestinal Endoscopy: Updated Review of the Literature and State of the Art

2021 ◽  
Author(s):  
Ivo Boškoski ◽  
Beatrice Orlandini ◽  
Luigi Giovanni Papparella ◽  
Maria Valeria Matteo ◽  
Martina De Siena ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Gastrointestinal Endoscopy ◽  
State Of The Art ◽  
Unmet Need ◽  
Diagnostic Techniques ◽  
Review Of The Literature ◽  
The Past ◽  
Wide Range ◽  
Near Future ◽  
Artificial Intelligence Systems

Abstract Purpose of Review Gastrointestinal endoscopy includes a wide range of procedures that has dramatically evolved over the past decades. Robotic endoscopy and artificial intelligence are expanding the horizons of traditional techniques and will play a key role in clinical practice in the near future. Understanding the main available devices and procedures is a key unmet need. This review aims to assess the current and future applications of the most recently developed endoscopy robots. Recent Findings Even though a few devices have gained approval for clinical application, the majority of robotic and artificial intelligence systems are yet to become an integral part of the current endoscopic instrumentarium. Some of the innovative endoscopic devices and artificial intelligence systems are dedicated to complex procedures such as endoscopic submucosal dissection, whereas others aim to improve diagnostic techniques such as colonoscopy. Summary A review on flexible endoscopic robotics and artificial intelligence systems is presented here, showing the m3ost recently approved and experimental devices and artificial intelligence systems for diagnosis and robotic endoscopy.

scholarly journals Artificial Intelligence in Capsule Endoscopy: A Practical Guide to Its Past and Future Challenges

Diagnostics ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1722
Author(s):  
Sang Hoon Kim ◽  
Yun Jeong Lim
Keyword(s):  
Artificial Intelligence ◽  
Capsule Endoscopy ◽  
Reading Time ◽  
Diagnostic Process ◽  
The Past ◽  
Computer Aided ◽  
Future Challenges ◽  
Medical Diagnostic ◽  
Reading System ◽  
Near Future

Artificial intelligence (AI) has revolutionized the medical diagnostic process of various diseases. Since the manual reading of capsule endoscopy videos is a time-intensive, error-prone process, computerized algorithms have been introduced to automate this process. Over the past decade, the evolution of convolutional neural network (CNN) enabled AI to detect multiple lesions simultaneously with increasing accuracy and sensitivity. Difficulty in validating CNN performance and unique characteristics of capsule endoscopy images make computer-aided reading systems in capsule endoscopy still on a preclinical level. Although AI technology can be used as an auxiliary second observer in capsule endoscopy, it is expected that in the near future, it will effectively reduce the reading time and ultimately become an independent, integrated reading system.

Understanding Molecular Process and Chemotherapeutics for the Management of Breast Cancer.

2020 ◽  
Vol 14 ◽  
Author(s):  
Abhishek Kumar ◽  
Neeraj Masand ◽  
Vaishali M. Patil
Keyword(s):  
Breast Cancer ◽  
Molecular Mechanisms ◽  
Molecular Targets ◽  
Molecular Classification ◽  
Neoplastic Disease ◽  
Molecular Process ◽  
The Past ◽  
Anti Cancer ◽  
Molecular Etiology ◽  
Near Future

Abstract: Breast cancer is the most common and highly heterogeneous neoplastic disease comprised of several subtypes with distinct molecular etiology and clinical behaviours. The mortality observed over the past few decades and the failure in eradicating the disease is due to the lack of specific etiology, molecular mechanisms involved in initiation and progression of breast cancer. Understanding of the molecular classes of breast cancer may also lead to new biological insights and eventually to better therapies. The promising therapeutic targets and novel anti-cancer approaches emerging from these molecular targets that could be applied clinically in the near future are being highlighted. In addition, this review discusses some of the details of current molecular classification and available chemotherapeutics

The Future of Work and the Changing Workplace

2018 ◽  
Author(s):  
Mahesh K. Joshi ◽  
J.R. Klein
Keyword(s):  
Artificial Intelligence ◽  
Machine Intelligence ◽  
Political Issue ◽  
Digital Innovation ◽  
Future Of Work ◽  
The Past ◽  
The World ◽  
Public Debates ◽  
The Future ◽  
Market Opportunities

The world of work has been impacted by technology. Work is different than it was in the past due to digital innovation. Labor market opportunities are becoming polarized between high-end and low-end skilled jobs. Migration and its effects on employment have become a sensitive political issue. From Buffalo to Beijing public debates are raging about the future of work. Developments like artificial intelligence and machine intelligence are contributing to productivity, efficiency, safety, and convenience but are also having an impact on jobs, skills, wages, and the nature of work. The “undiscovered country” of the workplace today is the combination of the changing landscape of work itself and the availability of ill-fitting tools, platforms, and knowledge to train for the requirements, skills, and structure of this new age.

Artificial Intelligence and Human Rights: Four Realms of Discussion: Summary of Remarks

2020 ◽  
Vol 114 ◽  
pp. 242-245
Author(s):  
Jootaek Lee
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Deep Learning ◽  
Language Processing ◽  
Human Reasoning ◽  
The Past ◽  
Making Choices ◽  
Data Capturing ◽  
Intensive Procedures

The term, Artificial Intelligence (AI), has changed since it was first coined by John MacCarthy in 1956. AI, believed to have been created with Kurt Gödel's unprovable computational statements in 1931, is now called deep learning or machine learning. AI is defined as a computer machine with the ability to make predictions about the future and solve complex tasks, using algorithms. The AI algorithms are enhanced and become effective with big data capturing the present and the past while still necessarily reflecting human biases into models and equations. AI is also capable of making choices like humans, mirroring human reasoning. AI can help robots to efficiently repeat the same labor intensive procedures in factories and can analyze historic and present data efficiently through deep learning, natural language processing, and anomaly detection. Thus, AI covers a spectrum of augmented intelligence relating to prediction, autonomous intelligence relating to decision making, automated intelligence for labor robots, and assisted intelligence for data analysis.

Evaluation and Comparison of Artificial Intelligence Vision Aids: Orcam MyEye 1 and Seeing AI

2021 ◽  
pp. 0145482X2110274
Author(s):  
Christina Granquist ◽  
Susan Y. Sun ◽  
Sandra R. Montezuma ◽  
Tu M. Tran ◽  
Rachel Gage ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Human Performance ◽  
Visual Impairments ◽  
Light Level ◽  
Viewing Distance ◽  
Light Perception ◽  
Time To Completion ◽  
Significant Difference ◽  
Text Reading ◽  
Size Contrast

Introduction: We compared the print-to-speech properties and human performance characteristics of two artificial intelligence vision aids, Orcam MyEye 1 (a portable device) and Seeing AI (an iPhone and iPad application). Methods: There were seven participants with visual impairments who had no experience with the two reading aids. Four participants had no light perception. Two individuals with measurable acuity and one with light perception were tested while blindfolded. We also tested performance with text of varying appearance in varying viewing conditions. To evaluate human performance, we asked the participants to use the devices to attempt 12 reading tasks similar to activities of daily living. We assessed the ranges of text attributes for which reading was possible, such as print size, contrast, and light level. We also assessed if individuals could complete tasks with the devices and measured accuracy and completion time. Participants also completed a survey concerning the two aids. Results: Both aids achieved greater than 95% accuracy in text recognition for flat, plain word documents and ranged from 13 to 57% accuracy for formatted text on curved surfaces. Both aids could read print sizes as small as 0.8M (20/40 Snellen equivalent, 40 cm viewing distance). Individuals successfully completed 71% and 55% ( p = .114) of tasks while using Orcam MyEye 1 and Seeing AI, respectively. There was no significant difference in time to completion of tasks ( p = .775). Individuals believed both aids would be helpful for daily activities. Discussion: Orcam MyEye 1 and Seeing AI had similar text-reading capability and usability. Both aids were useful to users with severe visual impairments in performing reading tasks. Implications for Practitioners: Selection of a reading device or aid should be based on individual preferences and prior familiarity with the platform, since we found no clear superiority of one solution over the other.

scholarly journals Boundaries Between Research Ethics and Ethical Research Use in Artificial Intelligence Health Research

2021 ◽  
pp. 155626462110027
Author(s):  
Gabrielle Samuel ◽  
Jenn Chubb ◽  
Gemma Derrick
Keyword(s):  
Artificial Intelligence ◽  
Health Research ◽  
Decision Makers ◽  
Societal Impact ◽  
The Past ◽  
Research And Innovation ◽  
The United Kingdom ◽  
Responsible Research ◽  
Past Half

The governance of ethically acceptable research in higher education institutions has been under scrutiny over the past half a century. Concomitantly, recently, decision makers have required researchers to acknowledge the societal impact of their research, as well as anticipate and respond to ethical dimensions of this societal impact through responsible research and innovation principles. Using artificial intelligence population health research in the United Kingdom and Canada as a case study, we combine a mapping study of journal publications with 18 interviews with researchers to explore how the ethical dimensions associated with this societal impact are incorporated into research agendas. Researchers separated the ethical responsibility of their research with its societal impact. We discuss the implications for both researchers and actors across the Ethics Ecosystem.

The Future of the Planetary Trust in a Kaleidoscopic World

2021 ◽  
pp. 1-8
Author(s):  
Edith Brown Weiss
Keyword(s):  
Artificial Intelligence ◽  
Natural Resource ◽  
Human Activities ◽  
New Technologies ◽  
Future Generations ◽  
Nuclear War ◽  
Human Environment ◽  
The Past ◽  
Resource Degradation ◽  
Shared Goal

Today, it is evident that we are part of a planetary trust. Conserving our planet represents a public good, global as well as local. The threats to future generations resulting from human activities make applying the normative framework of a planetary trust even more urgent than in the past decades. Initially, the planetary trust focused primarily on threats to the natural system of our human environment such as pollution and natural resource degradation, and on threats to cultural heritage. Now, we face a higher threat of nuclear war, cyber wars, and threats from gene drivers that can cause inheritable changes to genes, potential threats from other new technologies such as artificial intelligence, and possible pandemics. In this context, it is proposed that in the kaleidoscopic world, we must engage all the actors to cooperate with the shared goal of caring for and maintaining planet Earth in trust for present and future generations.

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