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Min Maung
Mentor, Technical Presenter, Data Scientist
Chicago, Illinois, United States
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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 conferences like That Conference and CodeMash. On weekdays, his focus shifts to crafting innovative solutions in IoT, Cloud, and AI domains.
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Windows IoT: Create IoT Core images for production
Have you thought about mass-producing devices running Windows 10 IoT Core? Windows 10 IoT is a member of the Windows 10 family that brings enterprise-class power, security, and manageability to the Internet of Things. Learn how to pick baseboards, modify packages, sign BSPs, and create secured system images, update the system as well as the applications running on IoT appliances.
In this session, we will show how to create a secure IoT core image, test a gateway system image and application running on it. Finally, we will create the final FFU and deploy the image on the IoT device and update it via Azure device management portal. We will be using Snapdragon 410C and Intel platform for this talk. Come listen to the team that wrote the IoT core device manufacturing guide.
Revolutionizing IoT Systems: Predictable Maintenance Notifications with AI and Custom Data Models
In today's interconnected world, IoT systems have become integral to various industries, from manufacturing to healthcare. However, one of the key challenges faced by organizations is ensuring timely maintenance of these complex systems to prevent costly downtime and disruptions.
This talk dives into the innovative use of Artificial Intelligence (AI) and custom data models to transform IoT systems' maintenance strategies. By leveraging AI algorithms and predictive analytics, organizations can move from reactive to proactive maintenance approaches, predicting failures before they occur and sending actionable notifications to maintenance teams.
Attendees will explore real-world case studies highlighting the benefits of incorporating AI-driven predictive maintenance into IoT systems. From optimizing equipment performance to reducing maintenance costs and improving overall reliability, this session will demonstrate the power of combining cutting-edge technologies for sustainable and efficient operations.
Key topics covered in the talk include:
Understanding the challenges of traditional maintenance approaches in IoT systems.
Introduction to AI and machine learning techniques for predictive maintenance.
Developing custom data models tailored to specific IoT environments.
Implementation strategies for integrating predictive maintenance notifications into existing systems.
Case studies showcasing successful deployments and tangible business outcomes.
Future trends and opportunities in AI-driven IoT maintenance solutions.
Join us to discover how AI and custom data models are revolutionizing IoT systems, enabling organizations to achieve unprecedented levels of efficiency, reliability, and cost-effectiveness in maintenance operations.
AI data privacy: Securing your own data on open platforms (like openAI)
This is a combined talk with Min Maung.
This presentation will delve into the intersection of AI, data privacy, and data ownership, focusing on its implications for the enterprise. It is an era where business competitiveness is tightly interwoven with AI advancements, yet, data privacy and ownership concerns present critical challenges. We will discuss how businesses can protect privacy while harnessing AI's potential, exploring regulatory frameworks like GDPR and CCPA that guide this delicate equilibrium.
We'll investigate ownership issues concerning private data models, a growing concern as AI becomes a cornerstone for enterprise innovation. Join us as we delve into the depths of data privacy in the enterprise AI landscape, highlighting the significance of striking a delicate balance between technological advancement and ethical responsibility.
The journey promises insights into overcoming data privacy challenges and fostering a culture of privacy-centered innovation in the business world.
Let's Build A Custom Smart EBike with IoT and AI Services
In the ever-evolving landscape of the Internet of Things (IoT), the integration of cutting-edge technologies has the potential to revolutionize traditional industries. This technical presentation unveils the journey of creating a Smart IoT Bike, a project that seamlessly combines Azure cloud services and Artificial Intelligence (AI) to enhance the biking experience and safety.
Our project's foundation lies in Azure IoT Hub, a robust platform for connecting, monitoring, and managing IoT devices. We will delve into the architecture, demonstrating how Azure IoT Hub facilitates real-time data ingestion from various sensors embedded in the bike, such as GPS, accelerometer, and heart rate monitors.
We will showcase how computer vision and machine learning models are employed to analyze live video streams from onboard cameras, ensuring rider safety by detecting potential hazards and providing timely alerts.
Furthermore, our Smart IoT Bike leverages Azure Machine Learning for predictive maintenance. We will discuss how data from sensors are used to predict and prevent mechanical issues, extending the bike's lifespan and reducing maintenance costs.
Implementing Readily Available AI Models (Hugging Face) In Existing Applications
In today's dynamic business landscape, organizations are constantly seeking innovative solutions to streamline operations, enhance productivity, and gain a competitive edge. One remarkable avenue that has emerged in recent years is the integration of open source models into custom applications, enabling businesses to revolutionize their workflow optimization strategies. This presentation abstract delves into the transformative power of AI models and their pivotal role in reshaping the future of business operations.
This presentation will explore the following key points:
Introduction to Models on Hugging Face: An overview of the Hugging Face ecosystem, providing a foundation for understanding their relevance in business workflows.
Custom Application Integration: A deep dive into the concept of custom application integration, showcasing how custom models can be seamlessly embedded into existing software and systems to augment their functionality.
bling data-driven decision-making processes.
Workflow Optimization: Exploring how the integration of open models can streamline internal workflows, automating repetitive tasks, accelerating document processing, and improving overall operational efficiency.
Future Directions: A glimpse into the evolving landscape of AI models and their potential to drive even greater advancements in business workflow optimization.
Building Custom Large Language Models with Llama: Exploring Pros and Cons
Come join two experts that have been working with LLMs for the past few years building real world solutions for customers.
In the rapidly evolving landscape of natural language processing, the demand for large language models has surged. Customization of these models to suit specific domains and tasks has become crucial. This technical presentation delves into the world of building custom large language models using the innovative framework known as Llama. Llama stands for "Language Model Learning Architecture," and it has emerged as a powerful tool for tailoring language models to diverse applications.
In this presentation, we will explore the step-by-step process of creating custom large language models with Llama, covering key concepts such as fine-tuning, transfer learning, and data preparation. We will also delve into the extensive pros and cons associated with this approach.
By the end of this presentation, attendees will gain a comprehensive understanding of the Llama framework, its capabilities in custom model creation, and the nuanced trade-offs between customization and generic large language models. Whether you are a researcher, developer, or decision-maker in the field of NLP, this presentation will equip you with valuable insights into harnessing the power of Llama for your specific language model needs.
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.
Cream City Code 2019 Sessionize Event
![](https://sessionize.com/image/e075-400o400o2-YDWrakvdv5m3gYuK637ri6.jpeg)
Min Maung
Mentor, Technical Presenter, Data Scientist
Chicago, Illinois, United States
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