(https://engineering.stanford.edu/people/john-hennessy), past President of Stanford University (2000-2016) and Chairman of Alphabet Inc. will be in conversation with (https://muckrack.com/alan-weissberger/bio) of the (https://r6.ieee.org/sv-techhistory/) about the history of technologies and companies in Silicon Valley since the late 1970s. They will be joined on stage by IEEE past President (https://iwrc.ieeeusa.org/blog/portfolio-items/thomas-coughlin/) to discuss recent IEEE accomplishments, current focus areas and suggestions on how to strengthen the world’s largest technology non-profit organization. Our conversation will cover the evolution of RISC (Reduced Instruction Set Computing) and its applications in smart phones, tablets and other devices. We will discuss the evolution of GPUs, the computational demands of machine learning, and the emergence of domain-specific architectures (DSAs). We will also discuss the founding of Atheros Communications (acquired by Qualcomm in 2011) and its development of chip sets for WiFi, Bluetooth and other OFDM (Orthogonal Frequency-Division Multiplexing) technologies. That will lead us into a brief discussion of WiFi – one of the most successful IEEE standards (802.11) – and Bluetooth, along with the associated semiconductor and equipment companies that developed those ubiquitous technologies. Finally, we will turn to Google’s history, particularly its research activities. As a Google Board member for more than two decades, Prof. Hennessy has played a role in helping develop Google's strategic direction. With the current pervasiveness of AI, what does that hold for the future of science, technology and higher education? Co-sponsored by: IEEE Communications Society, SCV chapter (ComSoc SCV) , Santa Clara University IEEE Student Chapter Speaker(s): John, Alan, Tom Agenda: 5:00 - 5:25 pm Registration and Networking 5:25 - 5:30 pm Intro by Tom Coughlin about IEEE and its SV Tech History Committee 5:30 - 6:15 pm Conversation 6:15 - 6:55 pm Audience Q & A 6:55 - 7:00 pm Closing Remarks Bldg: Locatelli Student Activity Center, 500 El Camino Real, Santa Clara, California, United States, 95053, Virtual: https://events.vtools.ieee.org/m/496561

#ieeeday Free Registration (with a Zoom account; you can get one for free if you don't already have it. This requirement is to avoid Zoom bombing. Please sign in using the email address tied to your Zoom account — not necessarily the one you used to register for the event.): https://sjsu.zoom.us/meeting/register/GGH84KjiSTiIr_W1K8MJVg Synopsis: In an era where data never sleeps, streaming algorithms offer a powerful toolkit for extracting meaningful insights from high-velocity data flows. This talk explores some foundational techniques that enable efficient, real-time analytics with minimal memory requirements. The algorithms covered include a clever bit-based strategy for approximating the count of 1s in a sliding window, ideal for binary streams where space efficiency is paramount. Another algorithm helps estimate statistical moments (mean, variance, skewness) using compact sketches, enabling a deeper understanding of stream distributions without storing the entire dataset. One other algorithm identifies trending items with exponential decay, giving more weight to recent data, a crucial method for dynamic environments like social media or sensor networks. Techniques like these form the backbone of intelligent stream processing. Through intuitive examples and practical applications, this session will demystify how these algorithms work, why they matter, and how they can be used to monitor, summarize, and react to data in motion. --------------------------------------------------------------- By registering for this event, you agree that IEEE and the organizers are not liable to you for any loss, damage, injury, or any incidental, indirect, special, consequential, or economic loss or damage (including loss of opportunity, exemplary or punitive damages). The event will be recorded and will be made available for public viewing. Speaker(s): Dr. Vishnu S. Pendyala Virtual: https://events.vtools.ieee.org/m/497694