MANHASSET, NY -- A symposium held at Carnegie Mellon University this week brought together academic minds to share ideas with students about what's possible with IBM's Watson OAQA technology in such areas as medicine, law, business, computer science, and engineering.
A team of researchers from CMU, led by Eric Nyberg, professor at Language Technologies Institute of the CMU School of Computer Science assisted IBM in the development of the Open Advancement of Question-Answering Initiative methodology for Watson. CMU also made two direct contributions to Watson: a source expansion algorithm which identifies the best text resources for answering questions about given topic, and an answer-scoring algorithm which improves Watson’s ability to recognize when a candidate answer is likely to be correct.
At the symposium teams of students from CMU and the University of Pittsburgh put their skills to the test in a demonstration of IBM Watson’s question and answer capabilities. It marked the first time students had the chance to face Watson’s analytical capabilities in a practice round exhibition game.
IBM chose to host the first Watson university symposium in Pittsburgh because of Carnegie Mellon’s key contributions to the development of Watson. The University of Pittsburgh has a long productive partnership with IBM in research projects such as cloud computing, carbon nanotubes, and smarter healthcare research around pandemic disease outbreaks and tissue regeneration.
By bringing the Watson technology to the university community, IBM's aim was to inspire the next generation of innovators and entrepreneurs how Watson can benefit society.
“Our hope is that seeing Watson first hand will spark innovation from the leaders of tomorrow so that together we can continue to build a smarter planet,” said Bernie Meyerson, vice president of innovation and university programs for IBM.
Watson, named after IBM founder Thomas J. Watson, was built by IBM scientists to have a machine that rivals a human’s ability to answer questions posed in natural language. The Jeopardy! format, where the machine was pegged against three humans, has provided the ultimate challenge because the game’s clues involve analyzing subtle meaning, irony, riddles, and other language complexities in which humans excel and computers traditionally do not.
Watson's combination of processing power, natural language recognition and machine learning was developed in collaboration between IBM’s Watson Research team and the academic community including CMU.
I am sure this will inspire next generation of innovators and entrepreneurs to exploit the capabilities of Watson to build smarter planet. I hope this will not just be limited to CMU but will be repeat across the globe.
David Patterson, known for his pioneering research that led to RAID, clusters and more, is part of a team at UC Berkeley that recently made its RISC-V processor architecture an open source hardware offering. We talk with Patterson and one of his colleagues behind the effort about the opportunities they see, what new kinds of designs they hope to enable and what it means for today’s commercial processor giants such as Intel, ARM and Imagination Technologies.