From Prompts to Power: A Talk on Prompt Engineering followed by A Hands-on Workshop
-- Generative AI, LLMs, Vision Language Models(VLMs), Retrieval-Augmented Generation (RAG), ...--
6 pm Pacific Time (PT) Prompt Engineering: Making the most out of LLMs
Synopsis: Speakers are the authors of https://www.manning.com/books/prompt-engineering-in-action.
(There will be a raffle for five free books to be given away to the selected in-person attendees. All attendees will get a special discount code to purchase the book. Other than that, the speakers assure that the presentation will not discuss the book in any way or form.)
LLMs are in every part of our lives. They play a vital role in increasing productivity, improving creativity, and bridging the technology gap between different industries. Hard-to-optimize problems have today become when to optimize because the technology is readily available. In this talk, we will look at different aspects of Prompt Engineering, including templates, techniques, and patterns that you can use while interacting with models. We will also walk through advanced techniques such as RAG and show how implementing these can solve some limitations and real-world problems that we face today. LLMs are transforming industries by enhancing productivity, fostering creativity, and bridging technological gaps. As AI capabilities expand, the challenge is no longer whether problems can be optimized but how to optimize effectively. This talk explores the principles of Prompt Engineering, covering key templates, techniques, and patterns to enhance model interactions. We will dive into advanced strategies like Retrieval-Augmented Generation (RAG) and show their real-world applications in overcoming LLM limitations.
Attendees will walk away with actionable insights to harness the full potential of LLMs in their workflows.
7 pm (PT) Hands-on Workshop: Building Advanced AI Applications and Agents
This workshop offers a comprehensive and hands-on experience in building advanced AI applications and AI agents. We will use the state-of-the-art Large Language Models (LLMs) and Vision Language Models(VLMs) to explain the process. Participants will explore practical techniques to leverage these powerful models for tasks such as Natural Language Understanding (NLU), Natural Language Processing (NLP), decision-making, text/image generation, and task automation. This workshop enables attendees to understand the essential topics, including open-source package requirements in Python, model selection, fine-tuning, and integrating external data sources. The session covers the design and implementation of AI agents by utilizing open-source models like Llama for tuning parameters and deploying real-world AI solutions. Emphasis will be placed on architecture design, training optimization, scalability, efficiency, and ethical considerations. The workshop will adapt its use case and model selection (e.g., language agent vs. vision agent) based on the audience's background to ensure the relevance and effectiveness of the session. By the end of the session, participants will have the foundational knowledge and skills to effectively create and deploy full-stack AI applications and agents tailored to their fields of interest.
- $3 registration is mainly to prevent food wastage because of casual registrations and no-shows.
- We are unable to accommodate food preferences. Attendees with dietary restrictions can bring their own food.
- Virtual attendees NEED NOT pay the $3 or register here. They can directly register on Zoom (account required) or watch directly on the YouTube Channel at 6 pm (California time)
- Virtual attendees require a Zoom account (free to obtain). 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.
- 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.
Date and Time
Location
Hosts
Registration
- Date: 17 Apr 2025
- Time: 12:30 AM UTC to 03:30 AM UTC
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- 2225 Lawson Lane
- Santa Clara, California
- United States 95054
- Building: A
- Room Number: A1 All Hands 1
- Starts 19 March 2025 07:00 AM UTC
- Ends 16 April 2025 09:00 PM UTC
- Admission fee ?
Speakers
Dr. Vishnu S. Pendyala of San Jose State University
Moderator
Biography:
Vishnu S. Pendyala, PhD is a faculty member in Applied Data Science and an Academic Senator with San Jose State University, current chair of the IEEE Computer Society Santa Clara Valley Chapter, and IEEE Computer Society Distinguished Contributor. During his recent 3-year term as an ACM Distinguished Speaker and before that as a researcher and industry expert, he gave numerous (70+) talks in various forums such as faculty development programs, the 12th IEEE GHTC h5-index:14, h5-median:19, IEEE ANTS h5-index:15 h5-median:19, 11th and 12th IACC H5-Index: 606, H10-Index: 305, 10th ICMC H5-index: 10, h5-median: 15, IUCEE, to audiences at venues such as Stanford University, University of Bolton, Universidad de Ingeniería y Tecnología, Lima, Peru, IIIT Hyderabad, KREA, IIT Indore, IIIT Bhubaneswar. Some of these talks are available on YouTube and IEEE.tv. He is a senior member of the IEEE and has over two decades of experience in the software industry in the Silicon Valley, USA. His book, “Veracity of Big Data,” is available in several libraries, including those of MIT, Stanford, CMU, the US Congress and internationally. Two other books on machine learning and software development that he edited are also well-received and found a place in the US Library of Congress and other reputed libraries. Dr. Pendyala taught a one-week course sponsored by the Ministry of Human Resource Development (MHRD), Government of India, under the GIAN program in 2017 to Computer Science faculty from all over the country and delivered the keynote in a similar program sponsored by AICTE, Government of India in 2022. Dr. Pendyala recently served on the US government's National Science Foundation (NSF) proposal review panel. He received the Ramanujan Memorial gold medal and a shield for his college at the State Math Olympiad.
Address:One Washington Sq, San Jose State University, San Jose, United States, 95192-0250
Shivendra Srivastava
Prompt Engineering: Making the most out of LLMs
Biography:
Shivendra Srivastava has more than a decade of experience working in the field of Cloud/Distributed Computing, Machine Learning, and Artificial Intelligence. Shivendra is an experienced engineer and engineering manager who has worked across various industries such as Retail, Pharmacy, and more recently in Cloud Computing companies. He holds a Master’s degree in computer science from Georgia Institute of Technology.
Shivendra is an Engineering Manager at AWS, where he focuses on building highly available, low latency and scalable serverless solutions that power AWS Lambda, Athena, Glue and Bedrock. You can learn more about Shivendra at https://www.linkedin.com/in/shivendrasrivastava/
Naresh Vurukonda
Prompt Engineering: Making the most out of LLMs
Biography:
Naresh Vurukonda has worked in Data Engineering, Machine learning, and Artificial Intelligence for more than a decade. He is an engineer who has worked in various industries, including Amgen, Viacom Media Networks, and Valuelabs, where he led the Data Engineers and Artificial Intelligence associates. He holds a master’s degree in computer science from Southern Arkansas University.
Naresh is an Information Systems Associate Director at Amgen, focusing on building Deep learning models and LLM solutions to enhance engineers’ productivity and serve patients on drug accessibility. You can learn more about Naresh at www.linkedin.com/in/nareshvurukonda.
Dr. Mehdi Bahrami
Hands-On Workshop: Building Advanced AI Applications and Agents in One Hour
Biography:
Email: