Min Maung, Lwin Maung

Min Maung:

Min is a versatile technical expert with extensive experience spanning IoT devices, multi-platform mobile development, and emerging technologies like AI. He has significantly influenced the transformation of numerous organizations and businesses in various capacities, including architect, director, and data scientist. Recognized as a Microsoft MVP, Min's tech proficiency extends across an array of devices, evidenced by his diverse collection of smartphones and gadgets. Displaying technological impartiality, he consistently explores mobile platforms like Android and even designs personalized microcontrollers for his robotics ventures. Beyond coding, Min channels his energy into constructing robots, steadily expanding his robotic repertoire. Catch him presenting at top-tier regional conferences. On weekdays, his focus shifts to crafting innovative solutions in IoT, Cloud, and AI domains.

Lwin Maung:

An accomplished author, mentor, and sought-after technology advisor, Lwin has been a guiding force for numerous C-level executives within Fortune 100 companies. Lwin has architected and spearheaded the creation of AI and IoT solutions, leaving an indelible mark on clients and end users across the globe and enriching countless lives. Collaborating with his brother Min, Lwin's applications have garnered recognition on prominent technology platforms such as engadget, gizmodo, and pocket now. They have undertaken the design and production of programmable microcontrollers and robots, tailored for educational purposes—empowering teens to grasp the fundamentals of programming. Lwin dedicates his free time to instructing and mentoring high school and university students, nurturing the next generation of application developers. His influence reverberates across various technical conferences where he regularly takes the stage to share his insights and expertise.

Sessions

Build Large Language Models from 0 to 60 (Llama, GPT, OpenAI)

Everyone is talking about AI, and using tools from OpenAI such as ChatGPT. Want to know what it takes to build your own Large Language Models(LLMs)? We will explore the tools ranging from hardware requirements to software requirements. We'll discuss the key elements of language model design, including tokenization strategies, neural network architectures, and training techniques. Attention will be drawn to the significance of quality training data, exploring techniques for data collection, cleaning, and augmentation. This presentation, suitable for ML enthusiasts, data scientists, and curious individuals, promises a comprehensive understanding of constructing large language models, marking the pathway from zero knowledge to a functional model.