The idea of 'a machine that thinks' dates back to ancient Greece times, but since the advent of electronic computing and the overwhelming amount of data generated by the human race in the last 50 years, the realisation of intelligent machines that can think like humans has been almost tangible.
In 1950 Alan Turing published his seminal work Computing Machinery and Intelligence. In the paper, Turing proposed to answer the question "Can machines think?" and introduced the Turing Test to d...
The idea of 'a machine that thinks' dates back to ancient Greece times, but since the advent of electronic computing and the overwhelming amount of data generated by the human race in the last 50 years, the realisation of intelligent machines that can think like humans has been almost tangible.
In 1950 Alan Turing published his seminal work Computing Machinery and Intelligence. In the paper, Turing proposed to answer the question "Can machines think?" and introduced the Turing Test to determine if a computer could demonstrate the same intelligence as a human.
In 1956 John McCarthy coined the term 'artificial intelligence' at the first-ever AI conference at Dartmouth College saying Artificial intelligence, " …is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable."
Today, there is a great deal of hype surrounding AI systems and intelligent machine development, which is of course to be expected of any new emerging technology. But what exactly is AI and what does it mean for the world of mechanical engineering?
In this I2I podcast special, Helen speaks with Neil Lawrence and Alan King about what AI and machine learning is all about, what their uses will be, and how engineers will benefit from using these systems in their working environments.
Professor Neil Lawrence is the inaugural DeepMind Professor of Machine Learning at the University of Cambridge, Senior AI Fellow at The Alan Turing Institute, and Visiting Professor of Machine Learning, University of Sheffield.
He received his bachelor's degree in Mechanical Engineering from the University of Southampton in 1994 and spent his early career as a field engineer on oil rigs in the North Sea. He has been working on machine learning models for over 20 years and recently returned to academia after three years as Director of Machine Learning at Amazon where he worked on deploying machine learning solutions for Prime Air, Alexa and the Amazon supply chain.
Alan King is Head of Global Membership Strategy at the Institution of Mechanical Engineers. He joined IMechE as a Business Development Executive in 2004 with a background in both engineering and business. His father, both an engineer and joint owner of an engineering firm, introduced Alan to engineering at an early age and he then combined his fascination for the subject with an interest in business at university, studying for a Master's in International Business.
As the Head of Global Membership Strategy, Alan supports the development of IMechE's comprehensive 5-year strategy. Collaborating with organisations worldwide, his team delivers exceptional support to IMechE members while crafting engaging membership marketing content for pivotal campaigns throughout the year.
Alan is now focusing his attention on how Artificial Intelligence could enhance both member services and support staff in their everyday tasks within the IMechE. He also recently wrote a fascinating article for Institution News on the practical applications of AI and Machine Learning in the engineering sector.
Useful Links:
Challenges in Deploying Machine Learning - Case Studies
How AI is Already Changing Engineering and the Role of the Engineer
Understanding Artificial Intelligence
PE Magazine report on Sustainability
We would love to hear your thoughts and comments on this episode. If you would like to get in touch, email us at podcast@imeche.org
You can find more information about the work of the IMechE at www.imeche.org
