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SUMMARY:OCCS GET Series: Bridging AI Integration & Exploring the Inner Workings of LLMs
DESCRIPTION:We are excited to continue the Orange County Computer Society (OCCS) Global Emerging Technologies (GET) Series—a monthly platform dedicated to spotlighting transformative innovations in computer science and technology. Hosted by the IEEE Orange County Computer Society Chapter\, this series unites professionals\, students\, and tech enthusiasts to explore the cutting edge of what’s possible.\nFollowing a highly engaging May session filled with thought-provoking conversations on Gen AI in healthcare and insurance\, we’re thrilled to bring you a powerful double-feature this June that explores both the strategic and technical sides of artificial intelligence.\nThis month\, we shift focus to the evolving AI ecosystem\, with two compelling talks. As AI adoption accelerates across industries\, organizations face significant challenges with integration\, scalability\, and security. At the same time\, large language models (LLMs) are transforming how we build\, deploy\, and interact with intelligent systems.\nIn this session:\n???? The first talk dives into enterprise-level strategies to overcome AI integration hurdles\, addressing legacy systems\, data silos\, and fragmented infrastructure to enable scalable\, secure solutions.\n???? The second talk takes you behind the scenes of LLMs—unpacking how they’re trained\, optimized\, and deployed—with real-world use cases that reveal how these models are powering next-generation applications.\nKey topics include:\n✅ Scalable and secure AI architectures\n✅ Bridging strategy and execution in AI adoption\n✅ Training pipelines\, fine-tuning\, and inference of LLMs\n✅ Bias mitigation\, privacy\, and responsible AI practices\n✅ Cross-domain LLM applications in real-world scenarios\nWhether you're building AI strategies at the enterprise level or curious about the inner workings of LLMs\, this session delivers valuable insights\, practical takeaways\, and a deeper understanding of AI’s rapidly growing impact.\n???? Don’t miss this opportunity to dive into the evolving world of enterprise AI and model development—where practical integration meets technical innovation.\n???? Interested in speaking at a future session? Reach out to swapnali.karvekar@ieee.org—we’re always looking for passionate voices to lead the conversation.\nJoin us as we learn\, connect\, and shape the future of emerging technologies—together.\nSpeaker(s): Pradyumna\, Tharun\nAgenda:\nTime (in PST)	Activity\n05:00pm – 05:15pm	Check-in and networking\n05:15pm – 05:30pm	OCCS Chapter Introduction!\n05:30pm – 06:00pm	Speaker: Pradyumna Amasebail Kodgi\n06:00pm – 06:30pm	Speaker: Tharun Sure\n06:30pm – 07:00pm	Q/A\nVirtual: https://events.vtools.ieee.org/m/487510
URL:https://svec.org/event/occs-get-series-bridging-ai-integration-exploring-the-inner-workings-of-llms/
LOCATION:Virtual: https://events.vtools.ieee.org/m/487510
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DTSTART;TZID=America/Los_Angeles:20250624T170000
DTEND;TZID=America/Los_Angeles:20250624T190000
DTSTAMP:20260515T045500
CREATED:20250617T053307Z
LAST-MODIFIED:20250617T053307Z
UID:75963-1750784400-1750791600@svec.org
SUMMARY:Generic LLMs in Cybersecurity
DESCRIPTION:Generic Large Language Models (GLLMs) are continually being released with increased size and capabilities\, enhancing the capabilities of these tools as universal problem solvers. While the reliability of GLLMs' responses is questionable in many situations\, these models are often augmented or retrofitted with external resources for various applications\, including cybersecurity.\nThe talk will discuss major security concerns of these pre-trained models: first\, GLLMs are prone to adversarial manipulation\, such as model poisoning\, reverse engineering\, and side-channel cyberattacks. Second\, the security issues related to LLM-generated codes using open-source libraries/codelets for software development can involve software supply chain attacks. These may result in information disclosure\, access to restricted resources\, privilege escalation\, and complete system takeover.\nThis talk will also cover the benefits and risks of using GLLMs in cybersecurity\, particularly in malware detection\, log analysis\, intrusion detection\, etc. I will highlight the need for diverse AI approaches (non-LLM-based smaller models) trained with application-specific curated data\, fine-tuned for well-tested security functionalities in identifying and mitigating emerging cyber threats\, including zero-day attacks.\nNote:\n– You will require a Zoom account (free to obtain) to join the meeting. 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. Register here: https://sjsu.zoom.us/meeting/register/2XuaGc9ISoCWOu1dt6ANog\n– 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.\nCo-sponsored by: Vishnu S. Pendyala\, SJSU\nSpeaker(s): Dr. Vishnu S. Pendyala\, Prof. Dipankar Dasgupta\, IEEE Fellow\, NAI Fellow\, AIIA Fellow\nVirtual: https://events.vtools.ieee.org/m/489327
URL:https://svec.org/event/generic-llms-in-cybersecurity/
LOCATION:Virtual: https://events.vtools.ieee.org/m/489327
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