IEEE Princeton Central Jersey Section

IEEE PCJS Volunteers, spouses, local section leadership, Region 1 leaders and Awardees are invited to this Awards Banquet. We will host this banquet at Mercer Oaks Golf Course in West Windsor, NJ on May 8. Buffet Dinner with beef, eggplant, potatoes and vegetables Cash Bar Dessert with tea/coffee Agenda: 6:00 pm Registration and Networking - Appetizers 7:00 pm Awards Presentation 7:30 pm Awards Dinner 8:15 pm Featured Speaker (TBD) Mercer Oaks Golf Club, 725 Village Road West, Princeton Junction, New Jersey, United States, 08550

Hello, Webex PCNJ invites you to join this WebEx meeting. IEEE PCJS DL “Continuum Robots” by Prof. Dr. Burgner-Kahrs Thursday, May 16, 2024 6:45 pm | Eastern Daylight Time (New York, GMT-04:00) | 2 hrs (https://ieeemeetings.webex.com/ieeemeetings/j.php?MTID=m0d519da85d82588bc18a02a15bd83ba9) https://ieeemeetings.webex.com/ieeemeetings/j.php?MTID=m0d519da85d82588bc18a02a15bd83ba9 Meeting number: 2533 281 0850 Meeting password: 3ZRmzc Join from a video conferencing system or application Dial [email protected] You can also dial 173.243.2.68 and enter your meeting number. To dial from an IEEE Video Conference System: *1 2533 281 0850 Join by phone +1-415-655-0002 United States Toll 1-855-282-6330 United States Toll Free Access code: 2533 281 0850 (https://ieeemeetings.webex.com/ieeemeetings/globalcallin.php?MTID=m85dfaca8f2a1a1993db67730eca01941) | (https://cisco.com/go/toll-free-dialing-restrictions) (https://ieeemeetings.webex.com/ieeemeetings/j.php?MTID=m3646ee0fc7ae677d776ef3d26f19e894) to your calendar. (Cannot add from mobile devices.) Speaker(s): Prof. Dr. Burgner-Kahrs, Virtual: https://events.vtools.ieee.org/m/418861

Lifelong Learning (or Lifelong Machine Learning) is an advanced Machine Learning (ML) paradigm: an architecture for ML systems that learn continuously, accumulate knowledge learned in the past, and use that knowledge to help future learning and problem solving. This talk will explore three aspects of Lifelong Learning. First, traditional ML is generally an energy-hungry process: the process of building and training of the model requires huge computational resources. It might be expected that Lifelong Learning might be limited to cloud and off-line computing only. But this talk will explain some ways that Lifelong Learning avoids that constraint – by introducing a signal propagation approach that combines learning into the inference process, enabling the system to add classes to its knowledge model at the same time it is being used to solve problems. Second, most ML approaches are limited in their ability to utilize temporal patterns in its computation. But in Lifelong Learning, there are some new mechanisms that can make the AI temporally aware, mechanisms which can improve the system's ability to work effectively with limited data as well as a significant savings in size and power usage. Third, Lifelong Learning research continues to explore new models of computation – going beyond the traditional Turing computation model. Lifelong Learning researchers have been investigating “Super-Turing computation,” a model of computation that resembles biological learning. Speaker(s): Hava Siegelmann, Room: Room 105, Bldg: Computer Science Building, 35 Olden St., Princeton University, Princeton, New Jersey, United States, 08544, Virtual: https://events.vtools.ieee.org/m/375905

The Secure Use of Artificial Intelligence Author: Dr. Nancy M Landreville Monay, May 20, 2024 at 6:30 PM - 8:00 PM - Virtual Co-sponsored by: Power Energy Speaker(s): Nancy Landreville, Agenda: Virtual: https://events.vtools.ieee.org/m/418243