Intelligence-Sharing Tools Will Enable Smarter Devices

This transformation is being made possible by a surge in data and computing power that can help machine learning algorithms not only perform device-specific tasks, but also help them gain intelligence or knowledge over time. In the not-so-distant future, artificial intelligence and machine learning tasks will be carried out among connected devices through wireless networks, dramatically enhancing the capabilities of future smartphones, tablets, and sensors, and achieving what's known as distributed intelligence. As technology stands right now, however, machine learning algorithms are not efficient enough to be run over wireless networks and wireless networks are not yet ready to transmit this type of intelligence. With the support of a National Science Foundation Faculty Early Career Development Program (CAREER) grant, Tianyi Chen, an assistant professor of electrical, computer, and systems engineering at Rensselaer Polytechnic Institute and member of the Rensselaer-IBM Artificial Intelligence Research Collaboration (AIRC), is exploring how to make such knowledge-sharing tools a reality. "I think in the future, the main terminal of intelligence will be our phones. Our phones will be able to control our computers, our cars, our meeting rooms, our apartments," Chen said.