Submitted by Tamra S. Connor
Alan Turing, first wrote about the concept of machines that could learn in a paper published in 1950. In his paper Computing Machinery and Intelligence, he discussed how to build an intelligent machine and then test its intelligence. In 1956, a proof of concept was presented thanks to funding by RAND, the Research and Development Corporation. The Logic Theorist, by Allen Newell, Cliff Shaw, and Herbert Simon was presented at the Dartmouth Summer Research Project on Artificial Intelligence (DSRPAI).
Over the next two decades, AI continued to grow and was refined by the researchers. The attendees at DSRPAI were avid supporters and worked with the Defence Advance Research Projects Agency (DARPA) to fund AI research and several institutions. Computers were extremely expensive and the patience of researchers and those who funded the research waned. The biggest limitation for AI was limited memory capacity of the current computers. Even in the absence of government funding and public hype, AI research continued to grow and thrive. Between 1990 and the early 2000s, the early goals of AI were realized. In 1997, the grandmaster of chess, Gary Kasparov played a game of chess with the IBM creation, Deep Blue, a chess playing computer program. Also in 1997, Microsoft introduced the speech recognition program Dragon.
The limitation of computer storage has virtually been eliminated, allowing the rapid growth of AI in the public realm. In today's world of big data it is virtually impossible for a human to process all the data that is available; however, with AI, this is not an issue. When you call a company or use the chat feature, many times, your conversation is with the computer using AI.
The future of AI here. How we use AI is the big question. There are so many questions that must be answered in the world of computers and ethics.
So, how are you using AI in your classrooms and in life?
Anyoha, R. (2017, Summer). History of AI. Science in the News: Special Edition: Artificial Intelligence. https://sitn.hms.harvard.edu/special-edition-artificial-intelligence/
Adopting hybrid teaching approaches in common
courses in architectural and civil engineering programs
Submitted by Ms Qingyuan Yang
There is an urgent need for improvements in engineering education to ensure graduates are equipped with essential skills (Piyush, Mohamed & Gabriella, 2022). This paper suggests the utilization of hybrid teaching approaches in the design of common courses in Architectural and Civil Engineering (ACE) education. The ideas are applicable to other disciplines.
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