Legal Knowledge Management and the Rise of Artificial Intelligence
Robotic Refactoring the Workplace
Why Your Next Insurance Claims Processor Could be a Robot
Building an AI Based Machine Learning for Global Economics
The Forgotten Element in Your Big Data Strategy
HK Bain, CEO, Digitech Systems
WiFi Networks: Shifting from Providing a Service to Improving the...
Daniel J. Strojny, Interim Associate Director of Network and IT Operations, University of St. Thomas
Breaking the Stereotypes in the Development of AI
Yves Jacquier, Executive Director, Production Studio Services, Ubisoft
Operationalize Machine Learning
Zongjie Diao, Director of Product Strategy and Management, Data Center Compute Group, CISCO
Thank you for Subscribing to CIO Applications Weekly Brief
AI is Transforming the Engineering Landscape!
The integration of AI is augmenting the engineering processes by facilitating enhanced interaction between the machines and humans.
FREMONT, CA – Since the inception of computing technology, researchers and scientist have dreamed of the day they could impart the capability of the human brain to computers. The technological revolution has made it possible to realize that dream with the emergence of artificial intelligence (AI). The simpler forms of AI are rapidly permeating everyday devices, empowering a smart lifestyle.
The incorporation of AI has significantly enhanced the capabilities of the engineering sector. It has enabled the development of machines capable of conducting sophisticated design and development tasks with minimal human intervention. The most prominent engineering applications of AI are in automotive manufacturing. The integration of robust hardware and software with AI has simplified the sophisticated process involved in the production line, enabling precision movements for more intricate functions.
Natural Language Processing (NLP)
NLP has simplified the interaction between humans and machines. However, NLP leverages large data sets and algorithm-based learning to impart human-like speech to machines. It has enabled smartphone manufacturers to integrate their phones with robust artificial assistants with the capability of understanding and responding to human speech. The evolution of NLP will allow design engineers to directly consult with the machine regarding the various aspects of their plan.
The modern landscape is fueled by data, which has enabled organizations to derive valuable insights and gain a competitive edge over their competition. Even the development of sophisticated AI models requires large data sets. Machine learning (ML), one of the prominent applications for engineering, is based on the constant generation and analysis of data. Engineers working on large scale public projects can leverage big data to draw important insights, leading to enhanced infrastructure decisions.
ML technology has revolutionized the engineering sector, enabling machines to learn and achieve human-like capabilities. Self-analyzing machines will not only refine the processes but will also lead to cost-effectiveness. In the manufacturing industry, ML technology will enable machines to identify minute errors which would have been indiscernible by humans. Also, the data collected by the ML-enabled devices can be organized in a central repository, which will enable it to formulate solutions, rather than following pre-defined routines.