OCCS GET Series: Bridging AI Integration & Exploring the Inner Workings of LLMs
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.
Following 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.
This 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.
In this session:
🔹 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.
🔹 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.
Key topics include:
✅ Scalable and secure AI architectures
✅ Bridging strategy and execution in AI adoption
✅ Training pipelines, fine-tuning, and inference of LLMs
✅ Bias mitigation, privacy, and responsible AI practices
✅ Cross-domain LLM applications in real-world scenarios
Whether 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.
📅 Don’t miss this opportunity to dive into the evolving world of enterprise AI and model development—where practical integration meets technical innovation.
🎤 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.
Join us as we learn, connect, and shape the future of emerging technologies—together.
Date and Time
Location
Hosts
Registration
- Date: 25 Jun 2025
- Time: 12:00 AM UTC to 02:00 AM UTC
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- Starts 01 June 2025 09:55 PM UTC
- Ends 24 June 2025 11:00 PM UTC
- No Admission Charge
Speakers
Pradyumna of Oracle Corporation
Integration Challenges Enterprises Face While Implementing AI
Enterprises adopting AI often struggle with integration challenges such as legacy systems, data silos, and inconsistent infrastructure. These issues complicate data access, limit scalability, and create security and governance concerns. Without a cohesive integration strategy, AI initiatives risk delays, reduced accuracy, and limited impact. Successfully implementing AI requires bridging these gaps with modern, scalable, and secure integration approaches that align with enterprise architecture and digital transformation goals, enabling businesses to unlock AI’s full potential.
Biography:
Pradyumna has nearly two decades of experience in enterprise integration technologies, building robust, enterprise-grade solutions for global customers. He currently serves as a Product Manager for the Oracle Automation Platform, where he is responsible for designing of scalable integration platforms used by enterprises worldwide. With deep expertise in hybrid deployments, cloud services, and modernization of legacy integration systems, he is passionate about driving seamless integration and enabling digital transformation through intelligent, low-code automation solutions.
Email:
Tharun of ServiceNow
Behind the Scenes: The Journey of LLMs from Training to Real-World Application
Behind the Scenes: The Journey of LLMs from Training to Real-World Application” offers an in-depth exploration of the development and deployment of large language models (LLMs). It outlines the multifaceted process of training these models, highlighting the data acquisition, preprocessing, and the intricacies of neural network architectures that enable them to understand and generate human-like text. The talk explores the challenges encountered during training, including computational demands and ethical considerations, and discusses the methodologies employed to refine the performance of large language models (LLMs). Furthermore, it examines the transition from theoretical models to practical applications in various fields, including customer service, content creation, and education. By showcasing real-world examples, the article illustrates the profound impact of LLMs on industries and everyday life while addressing ongoing concerns about bias, privacy, and the responsible use of AI technologies. Ultimately, this work aims to bridge the gap between the technical underpinnings of LLMs and their tangible benefits and challenges in real-world settings.
Biography:
I am Tharun Sure, Senior IEEE Member, an award judge and industry expert specializing in AI, healthcare technology, and enterprise software. With over a decade of experience leading innovation at prominent companies like Dexcom, ServiceNow, and Verizon, I have had the privilege of reviewing and evaluating cutting-edge advancements in AI, cloud computing, cybersecurity, and digital health solutions. I hold patents in AI-driven cybersecurity and healthcare data encryption, and I have served as a judge for global awards that recognize excellence in SaaS, MedTech, and emerging technologies.
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Agenda
| Time (in PST) | Activity |
| 05:00pm - 05:15pm | Check-in and networking |
| 05:15pm - 05:30pm | OCCS Chapter Introduction! |
| 05:30pm - 06:00pm | Speaker: Pradyumna Amasebail Kodgi |
| 06:00pm - 06:30pm | Speaker: Tharun Sure |
| 06:30pm - 07:00pm | Q/A |