<div dir="ltr"><p data-sourcepos="1:1-1:1091">Azure AI Connect stands as a vibrant series, meticulously crafted for Microsoft Professionals, esteemed MVPs, and passionate Technology Enthusiasts, all converging to explore the expansive Azure AI Ecosystem. We find ourselves at the dawn of the AI Application era, a period of unprecedented growth where collective learning and evolution are paramount. The sheer magnitude of AI Technology advancements is staggering, and Azure emerges as a premier ecosystem, empowering a diverse spectrum of Applications, groundbreaking Innovations, and seamless Integrations. With its rich array of tools and capabilities, Azure stands ready to fuel the next wave of technological progress. This series is your gateway to unraveling the intricacies of Azure AI, offering invaluable insights and practical knowledge. By participating in these sessions, you'll embark on a journey of continuous learning, evolving alongside seasoned Professionals and recognized Experts, ensuring you remain at the forefront of this transformative technological revolution. Join us, and be part of shaping the future of AI.</p></div>
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Azure AI Connect - Global AI Bootcamp

Room 1

Room 2

Get started using Microsoft's Semantic Kernel for .NET to connect to your OpenAI account hosted on Azure. Explore the Semantic Kernel API and learn how to build .NET apps which utilize OpenAI.

Using Semantic Kernel in .NET with Azure AI

We hear about the dangers of Generative AI. Generative AI can exclude people. The system can generate bias and it's possible to strengthen the current stigma people from diverse backgrounds may have. But for this talk, let's reverse the question: Can Generative AI make the world more inclusive, in specific for people with disabilities?

As a tech-optimist I would say yes. But you don't need to believe me. Instead of a blind believe in the yes, I give you some interesting cases where Generative AI limits bias and makes the world more inclusive.

- For people without formal education, Gen AI can explain theories;
- For people with dyslexia, Gen AI can write stuff in better wordings and grammar;
- For people with autism, Gen AI can help them to understand social situations better;
- For people with a visual impairment, Gen AI can help with reading text;

In this talk we are going to explore some use-cases how Gen AI can make the world more a more inclusive and better place for everyone, in specific for people with disabilities.

Can Gen AI make the world Disability inclusive?

As vector search and RAG become mainstream for GenAI use cases, we’re looking ahead to what’s next. Generative Feedback Loops (GFL) represent the next evolution in AI where the AI outputs are improved over time through a cycle of feedback and learning based on the production data. In this talk, we’ll break down how this works, and you will learn how to build a sample AI app with feedback loops in .NET using Azure Functions, Neon serverless Postgres, and Azure OpenAI. 

Generative Feedback Loops (GFLs) in action

AI in Education: Nonlinear and Exponential

1) Personalized Learning (Content for One): Tailoring educational content to align with the unique preferences and learning styles of each individual student.
2) Real-Time Feedback: Empowering students with instant insights through AI, ensuring they grasp concepts accurately during the learning process.
3) Dynamic Pathways: AI creating adaptive learning pathways or course plans that evolve in real-time, accommodating changes in goals or external circumstances.

AI in Education

In the rapidly evolving landscape of artificial intelligence, Large Language Models (LLMs) are proving to be both revolutionary and dangerously vulnerable. While their transformative potential is undeniable, their deployment creates new risks and amplifies existing threats. Alarmingly, current enterprise security tools are unequipped to address these vulnerabilities, leaving organizations exposed. As a result AI systems are either going live without proper security assurances or being blocked altogether, stifling innovation and adoption.

In this talk, Dr. Peter Garraghan takes the audience on a deep dive into the underbelly of AI vulnerabilities. Drawing on over a decade of research, Dr. Garraghan will demystify how attackers exploit weaknesses in AI to disrupt services, leak sensitive data, and reverse-engineer proprietary capabilities. He will also highlight how the unique, dynamic behavior of AI amplifies these risks, making them particularly vulnerable to sophisticated attacks that can be triggered through seemingly benign user interactions, turning ordinary usage into a potential threat vector.

Through a live demonstration, attendees will witness how adversarial attacks can be launched quickly and cheaply, highlighting the need for AI safeguards. Dr. Garraghan will introduce practical guardrails, emerging AI security tooling, and best practices to mitigate AI risk, empowering organizations to adopt AI safely and securely.

Can My AI Be Hacked?

We are moving on from building just intelligent systems to creating responsible, ethical, and impactful solutions. Join us for a hands-on session on building ethical and safe AI solutions using Azure AI Foundry. Let's cut through the jargon and discuss practical ways to make your AI projects more responsible. In this session, you'll learn:
	• The basics of Responsible AI and why it matters
	• How to use Azure AI Foundry's tools for safer AI development
	• Practical tips for content moderation in AI applications
	• Real-world techniques for ethical AI governance

The session is intended for developers, data scientists, and tech leaders who want to create AI that's not just smart, but also trustworthy. Let's see how it's done. 
Key takeaways:
	• Understand what Responsible AI really means in practice
	• Learn to use Azure AI Foundry's safety features effectively
	• Master practical content moderation techniques
Implement ethical AI governance in your projects

Building Trustworthy AI: Practical Approaches with Azure AI Foundry

What if I told you that you could use GPT-powered natural language to investigate and respond to security incidents, threats, and vulnerabilities facing your organization right now? This presentation on Microsoft Copilot for Security will showcase its advanced integration with Microsoft 365 Security technologies. This innovative tool leverages AI to enhance threat detection, automate responses, and provide comprehensive insights into security incidents. By seamlessly integrating with Microsoft Defender, Azure AD, and other 365 security services, Copilot for Security elevates organizational protection and streamlines security operations, ensuring robust defense against evolving cyber threats.

Microsoft Copilot for Security: Use AI to defend!

Learn how Azure OpenAI empowers you to scale your LLM deployments, ensuring they are cost-effective, high-performance, and ready for the real world. Discover how to navigate critical metrics like TPMs, RPMs, and PTUs, tackle latency challenges, and handle bursty traffic with Azure API Management (APIM). We’ll share practical strategies for controlling costs, enabling multi-region scalability, and using Azure’s capacity planning tools to meet your growing needs. Whether you're scaling a chatbot, automating document workflows, or building enterprise AI applications, this session provides the roadmap to turn your LLM aspirations into operational success.

Discover powerful frameworks that take enterprises from concept to implementation—whether on the cloud, on-prem, or in a hybrid environment.
Ready to take your AI initiatives to the next level? Join this session to unlock the secrets to building enterprise-grade LLM deployments that are truly game-changing.

Accelerating AI Success: Leveraging Scalable and Cost-Efficient LLMs with Azure

Did you know that you can combine various AI services such as Open AI, Azure Open AI and Hugging Face in your own custom application?

In this session you will learn how you can build your own CoPilot experience using the Semantic Kernel which is released as an open source project. 

I will demonstrate how you can use skills, memories, connectors and plugins in order to enhance the experience for your users.

This session is a developer focused session meaning that you do not need to have any AI knowledge in order to benefit from the examples demonstrated in the session.

How to enhance your own AI services using Semantic Kernel

In the rapidly evolving world of AI, choosing the right tools can make or break your project. This talk dives into the pros, cons, and performance of Azure AI Language versus popular open-source NLP solutions (Hugging face, Haystack, SpaCy, etc). From scalability and integration to cost and customization, discover which approach aligns best with your goals. Whether you're a cloud enthusiast or an open-source advocate, this session will provide valuable insights to empower your AI strategy.

Battle of the titans: Azure AI Language vs. OpenSource solutions

Discover Firebase Genkit in this introductory workshop. We'll explore how this versatile framework empowers developers to build AI-driven applications with ease. Learn to deploy Genkit's open-source applications for Node.js and Go, integrate with generative AI models, and run independently of Google services. Perfect for those looking to streamline their AI development process. We will talk about Github, Azure and Google Models too.

Introduction to Firebase Genkit

AI has transformed various industries, including DevOps, by preventing service disruptions, improving security, and enabling anomaly detection. In this talk, you'll learns some of the best ways to apply AI to manage and secure Azure infrastructure, from code generation to policy enforcement to remediation. 

We'll walk through real code examples and applications, that will enable you to supercharge your cloud ops and security through AI.  

Don't miss out on this opportunity to stay ahead in the AI revolution.



Elevating Cloud Security with AI: A DevSecOps Revolution

In this session we will learn how to boost your copilot studio generative AI responses by connecting it to Azure Search through Azure Open AI. In this way, we can create our own index configuration in Azure AI Search, using semantic ranking to prioritize the content that is more relevant to our users. 

Boost Copilot Studio using Azure AI Search

This presentation explores the transformative capabilities of Retrieval-Augmented Generation (RAG), a cutting-edge framework that integrates retrieval systems with generative language models. Tailored for researchers and practitioners, the session provides a detailed examination of RAG's architecture, demonstrating its ability to overcome challenges such as static knowledge and limited contextual understanding in traditional models.

The talk includes an in-depth walkthrough of RAG's implementation pipeline, covering techniques for efficient information retrieval, integration with generative models, and optimising responses for diverse applications such as question answering, summarisation, and dialogue systems. Attendees will gain a robust understanding of how to build and deploy RAG systems effectively, bridging the gap between retrieval and generation for state-of-the-art performance in real-world scenarios.

Demystifying Retrieval-Augmented Generation (RAGs)

This session will guide participants in enhancing and integrating an application with Azure services. Key tasks include configuring and integrating the app with Azure Kubernetes Service (AKS). Additionally, participants will expose OpenAI via API Management, update Docker images, and build a Copilot App using Semantic Kernel Tools.

Build Intelligent Apps with Microsoft's Copilot stack & Azure OpenAI

Discover how Microsoft Azure AI Agent capabilities and Azure AI Foundry are revolutionizing AI-driven automation. This session will introduce the fundamentals of AI agents, explore Azure AI Foundry, and demonstrate how multi-agent automation enhances productivity across various use cases. We'll dive into practical implementations using Autogen, showcasing how multiple specialized agents can collaborate seamlessly. Join us for an insightful session with a live demo, where you'll learn how to build intelligent, automated workflows with Azure AI.

Unlocking AI powered automation with Microsoft Azure AI Agent

AI technologies are increasingly integrated into many aspects of daily life, especially for developers. However, this integration has not yet consistently resulted in inclusive and accessible products and services. In this presentation, I will explore how Azure AI is leading the way in achieving accessibility at scale. Through two compelling use cases, I will demonstrate how these technologies can be seamlessly incorporated into design processes to enhance services. First, discover a news site enhanced with Azure’s Text to Speech and SEEING AI APIs. These services enable a read-aloud function with image descriptions as well aiding visually impaired users and others as well, such as those listening while driving. Next, learn about a multilingual chatbot powered by Azure OpenAI and Speech to Text capabilities. This inclusive tool breaks language barriers and assists users with mobility challenges, showcasing how accessible design benefits diverse audiences. Through this exploration, I hope to inspire you to consider the vast possibilities of accessible design, encouraging you to go beyond mere regulatory compliance and truly innovate for inclusivity.

Azure AI – Shaping an accessible world

Dive into the future of AI-driven development with Autogen Framework, an open-source tool that revolutionizes how we build complex workflows using conversational agents and patterns. In this demo-ful session, we’ll explore the fundamental concepts and conversational patterns essential for crafting multi-agent AI applications within the .NET ecosystem.

The session will try to help you to build a robust understanding of how to leverage large language models (LLMs) to orchestrate sophisticated, agentic workflows. Topic covered:

Core Concepts: Get to grips with the foundational elements of the Autogen Framework.

Conversational Patterns: Learn how to design and implement effective conversational agents that can collaborate seamlessly.

Practical Applications: Walk through real-world scenarios and use cases to understand the framework's potential.

Unleash the Power: Crafting Agentic AI .NET Apps with Autogen Framework

Artificial Intelligence (AI) has rapidly evolved, promising transformative advancements. However, as AI systems become increasingly sophisticated and integrated into our daily lives, so do the security risks associated with them. This talk delves into the realities of AI security, beyond the hype and promises. We will explore the vulnerabilities inherent in AI systems, including data privacy breaches, adversarial attacks, and model poisoning. The presentation will also discuss the ethical implications of AI, such as bias and discrimination, and how they intersect with security concerns. By the end of this talk, attendees will gain a comprehensive understanding of the challenges and best practices for securing AI systems, enabling them to build and deploy AI solutions responsibly.

Between the main points of the talk we can highlight:
-The evolving threat landscape(Adversarial attacks,data privacy and security)
-Ethical implications of AI security
-Securing AI systems: Best practices and emerging technologies
-The future of AI security

Beyond the hype: The reality of AI security

Hands On: Copilot for Security

Discover how GitHub Copilot's Private Extensions are reshaping the development landscape by providing AI-powered, context-aware code suggestions tailored to your organization's unique needs. This session will explore how these extensions enhance productivity, streamline collaboration, and boost code quality by leveraging proprietary knowledge. Learn how to securely integrate Copilot into your workflows, transforming the way your teams code, refactor, and innovate. Perfect for developers looking to harness AI to optimize their custom projects.

How GitHub Copilot Private Extensions Transform the Coding Experience

Discover the core principles and best practices of deploying AI solutions in the cloud. This session will dive into reference architectures, covering key components like data pipelines, model training, deployment, and scalability. Learn how to leverage cloud services for efficient, scalable, and robust AI implementations. Ideal for architects and developers.

Reference Architecture of AI in the Cloud

Discover how to access Azure Open AI from Azure SQL, querying your data with natural language and opening a world of possibilities

Azure SQL and Open AI using T-SQL

25 years after Agent Smith coined “Never send a human to do a machine’s job”, this futuristic idea seems closer than ever...

Not so long ago, AI was known for its ability to excel at specific tasks (“cat vs dog”), earning it the reputation of a specialist. However, with the advent of Large Language Models like OpenAI’s GPT, AI has transformed into a generalist, capable of writing naturally, answering questions, and even generating code. Despite facing limitations such as hallucinations, knowledge cutoffs, and struggles with basic math, these AI systems have opened up a world of possibilities.

Today, the next frontier in AI development are AI agents. By combining the power of LLMs with advanced capabilities such as planning, reflection, and tool use, AI agents are becoming the “jack-of-all-trades” in the tech world. Drawing inspiration from human cognition, AI Agents can accomplish complex goals, thinking and acting much like us humans. Join us as we explore agentic workflows and discuss the role of developers in guiding AI agents and shaping the future of AI. We’ll get familiar with the world of AI agents, and understand their potential to revolutionize the way we work and interact with technology, ultimately allowing humans (and developers 😉) to focus on the bigger picture.

The Rise of AI Agents

Keeping the production environment under control is becoming increasingly challenging, but luckily, with AI-powered tools, you can get the assistance you need by implementing true AIOps.

In this session, we will explore and test the various tools Azure Monitor offers to automate multiple IT Operations tasks with AI support, from log analysis to alerts and workload optimization.

Identify and mitigate production issues by adopting AIOps in Azure Monitor

In this session i will be showcasing you how to create your first AI based application using RAG model

Build Your First AI Application with RAG

Join us to discover the transformative potential of Azure AI Speech across diverse industries. Azure AI Speech empowers businesses with advanced capabilities such as speech recognition, text-to-speech, and speech translation, facilitating the creation of voice-enabled applications that significantly boost operational efficiency.
We will kick off the session by introducing Azure AI Speech services and their wide-ranging applications, emphasizing key features like real-time speech recognition, text-to-speech conversion, and speech translation. You will learn how to set up and configure Azure AI Speech for real-time speech-to-text conversion, with practical use cases including dictation, call center assistance, and live meeting captioning.
The session will delve into text-to-speech capabilities, demonstrating how to convert text into natural-sounding speech using Azure AI, with applications in virtual assistants, accessibility tools, and automated announcements. Additionally, we will explore speech translation for multilingual interactions and its use cases in global support and cross-language communication.
We will outline the steps to integrate Azure AI Speech into existing applications and share best practices for deploying and scaling speech-enabled solutions. Through case studies and success stories, we will illustrate how businesses leverage Azure AI Speech to enhance operational efficiency and accessibility.  Unlock the potential of Azure AI Speech and transform your interactions with cutting-edge voice technology. Don't miss this opportunity to stay ahead in the AI-driven future—register now and take the first step towards revolutionizing your business!


Revolutionizing Interactions with Azure AI Speech

The most popular AI demo is the AI chatbot that responds to questions asked by a human. This is a valid and instructive scenario but we aspire to go beyond the basics in this talk.

Imagine an AI that not only answers your questions but also actively works towards goals you've assigned to it. In this session, we'll explore the building of an AI Agent – an autonomous actor that can execute tasks and achieve objectives on your behalf.

We'll start with a basic C# chatbot built using Microsoft's Semantic Kernel framework. Then we'll transform it into a simple yet powerful AI Agent by giving it access to some tools and assigning it a goal to accomplish using those tools.

The end result is the core of an AI Agent - a tool that can do work on your behalf without you being there. We will also compare this to a Copilot since there's substantial overlap.

By the end of this talk, you'll understand how to approach building goal-driven AI solutions using Semantic Kernel and (hopefully!) be inspired to apply these techniques to your own projects.

This talk assumes user-level familiarity with LLMs like ChatGPT or Microsoft Copilot and basic prompt engineering concepts. Anything else will be explained. 

From Chatbot to Goal-Oriented AI Agent Using Semantic Kernel

"Threat or Opportunity? — Enhancing Software Development Efficiency with AI" explores the transformative role AI tools, like ChatGPT, play in the software development process. As AI continues to evolve, it presents both challenges and possibilities for developers. This presentation will focus on how AI can enhance productivity, reduce repetitive tasks, streamline code reviews, and support decision-making, ultimately making development workflows more efficient. It will dive into practical examples of integrating AI in everyday tasks, helping developers to leverage these technologies as powerful allies rather than seeing them as a threat.

Threat or Opportunity? — Enhancing Software Development Efficiency with AI

Do you need to search your data based on meaning instead of matching by keywords or phrases? Do you need to match the data in a language different from the query term?

Semantic search or search based on the meaning analyzes the context and intent behind the query term to provide relevant results. Using Vector embeddings, the data structure behind semantic search, you can supercharge your search to include text, images, and other types of data. With vector databases you can store and index vector embeddings and provide similarity search over these embeddings.

In this session, we will explore the building blocks of semantic search and explore vector embeddings and similarity metrics. You will learn how to generate embeddings with large language models using OpenAI. I will also explain how to store, index, and query vector embeddings using the vector data type in Azure SQL Database or with the upcoming Microsoft SQL Server 2025. Finally, you will see how optimize the queries with the DiskANN vector index.

Join me for a demo-rich session and learn how to implement semantic search in with Azure SQL Database.

Supercharged Search with Semantic Search and Vector Embeddings

Voice AI agents are transforming the operational landscape for small and medium-sized businesses (SMBs), offering automation and enhanced customer experiences. However, building these systems comes with unique challenges. This talk will explore the technical and operational hurdles in building and deploying voice AI agents tailored to SMB verticals. We will also delve into cutting-edge advancements, such as multi-agent system development, multimodal integration for richer interactions, and the use of reinforcement learning for continuous improvement. Lastly, the session will discuss evaluation frameworks—beyond traditional metrics—to measure performance, usability, and business impact in real-world settings.

Voice AI Agents for SMB Operations

Data-Centric AI: Accelerating Success Through Modern Data Products

Target Audience
- Data Leaders & Architects
- Data Engineers & Platform Engineers
- ML/AI Engineers & Data Scientists
- Analytics Engineers & Practitioners

Abstract
While organizations rush to advance their AI models, research shows that "reducing the technological gap alone is not enough to ensure success in AI projects" [The Data Death Cycle, 2024]. The key to accelerating AI success lies not in model optimization, but in data excellence. This session reveals how a data-centric approach, powered by Apache Iceberg and modern data architectures, dramatically improves AI systems by ensuring complete, consistent, and curated datasets from the start.

Overview
AI and analytics initiatives demand high-quality data, yet traditional model-centric approaches often overlook this fundamental requirement. We'll explore how data products, implemented through a combination of data mesh and data fabric patterns, provide the systematic data excellence that AI requires. Learn how Apache Iceberg's lakehouse architecture eliminates costly ETL while enabling "git-like" version control through metadata catalogs like Polaris and Nessie, providing comprehensive write-audit-publish capabilities for data changes.

Through real-world examples and architectural patterns, we'll demonstrate how organizations can:
- Accelerate AI success through systematic data excellence rather than just model optimization
- Create trusted data products that ensure quality, completeness, and consistency
- Implement efficient data integration without expensive ETL processes
- Enable version control and auditability for data changes
- Balance centralized governance with domain agility

Key Takeaways

1. Data-Centric Advantage
- Why focusing on data quality accelerates AI success more effectively than model optimization
- How systematic data excellence reduces the 80% of time data scientists spend on data preparation
- The critical role of complete, consistent, and curated datasets in AI/ML success

2. Modern Data Products
- How data products enable systematic management of data quality
- Why combining data mesh and data fabric creates the ideal architecture for AI-ready data
- Patterns for implementing data products that ensure quality, governance, and reliability

3. Technical Foundation
- How Apache Iceberg enables efficient data integration without costly ETL
- The role of metadata catalogs in providing git-like version control for data
- Practical patterns for implementing write-audit-publish workflows for data changes

4. Implementation Path
- Steps for transitioning to a data-centric approach
- How to begin implementing data products in your organization
- Methods for measuring and demonstrating success

Whether you're struggling with AI initiatives or looking to accelerate existing programs, this session provides practical insights into building the data foundation that modern AI demands. You'll learn why data-centric approaches succeed where model-centric efforts fail, and how to implement the technical architecture that makes it possible.

Join us to discover how combining data-centric thinking with modern technologies like Apache Iceberg can transform your organization's ability to deliver successful AI initiatives. Leave with concrete steps for implementing data products that provide the complete, consistent, and curated data that AI systems require.

Data-Centric AI: Accelerate Success with Apache Iceberg Data Products

Explore how to harness the power of large language models (LLMs), Cognitive Services, and intelligent tools to create innovative solutions for modern business challenges. Through real-world examples and a live demonstration, learn how to integrate Azure AI into your workflows, automate processes, and build AI-powered applications seamlessly. Whether you're a developer, data scientist, or tech enthusiast, this session will equip you with actionable insights and practical knowledge to accelerate your AI journey with Azure.

Innovation with Azure AI: From LLMs to Cognitive Services

As AI systems grow more complex and integrated into daily life, the need for transparency, accountability, and trust is crucial. Explainable AI (XAI) bridges the gap between advanced algorithms and human understanding. 

Join us for an insightful session exploring the core principles of XAI, cutting-edge interpretability techniques, model diagnostics, and ethical implications. Learn how to transform opaque AI models into responsible, understandable systems aligned with human values. Whether you’re an AI professional, researcher, or enthusiast, this session equips you with practical tools to build trustworthy AI.

Key takeaways include the importance of XAI, advanced techniques for model interpretability, and the intersection of ethics, responsibility, and transparency in AI. We’ll explore real-world applications and case studies, providing insights into integrating XAI into your projects. Challenge the status quo and discover how AI can serve everyone.

Demystifying AI: Unlocking Transparency with Explainable AI (XAI)

In this session we will have an introductory overtime of Microsoft Fabric. Understanding the components and seeing examples of the different personas approach. Will review the approach for Data Factory, Data Engineering, Data Science, Data Warehousing, Real-Time Analytics and Power BI. Finally, we will see how to start getting involved with the new platform for Data analytics for the era of AI

Introduction to Microsoft Fabric - Data analytics for the era of AI

Discover how to use Azure OpenAI real-time APIs with your applications to build low-latency, AI-powered voice agents. This session will demonstrate how to create interactive experiences that process and respond to audio input instantly over VOIP and telephony. The talk will include a case study and a live coding demo to illustrate the concepts.

Build low-latency AI voice agents using real-time GPT models

In this session, we will explore Phi Models, one of the most innovative approaches within Small Language Models (SLMs). We’ll discuss how these models are designed to deliver exceptional performance in natural language processing tasks while maintaining a compact structure, making them more efficient and accessible than traditional large-scale models. 

The session will cover how Phi Models leverage the strengths of SLMs to tackle challenges such as reducing computational resources, improving inference speed, and optimizing applications on resource-constrained devices. Additionally, we will look at their real-world applications and the impact they are having on the development of more agile and sustainable AI solutions.

Phi Models: Innovation in Small Language Models for efficient language processing

In this session, we’ll explore how Azure OpenAI and Azure Search can improve your document processing. Learn how Azure OpenAI can help with tasks like extracting and summarizing content from documents, while Azure Search allows you to quickly find and analyze information. We’ll look at real-world examples showing how these tools work together to automate document handling, save time, and make it easier to find important insights. By the end of the session, you'll have a clear understanding of how to use these tools to streamline your document workflows.

Enhance Document Processing with Azure OpenAI and Azure Search

Join Alon Fliess, Azure AI Platform MVP and Microsoft Regional Director, for a transformative lecture exploring how Semantic Kernel is ushering in a new era of software development. In a world where deterministic algorithms are no longer sufficient on their own, developers and architects must embrace hybrid solutions that integrate deterministic logic, heuristic approaches, and cutting-edge AI technologies such as generative AI and machine learning.

This session dives into the paradigm shift in software engineering, highlighting the challenges and opportunities of building systems that must evaluate and manage non-deterministic results alongside deterministic logic. With the increasing use of AI agents that generate solutions and validation agents that safeguard and guide their output, responsible AI practices are becoming central to modern software development.

Attendees will gain insights into the capabilities of Semantic Kernel, a project that seamlessly integrates C# with AI-driven functionalities. By combining traditional programming approaches with AI capabilities, developers can craft systems that are not only intelligent but also adaptable to complex and evolving environments. This lecture will showcase real-world applications of Semantic Kernel, demonstrating its potential to revolutionize diagnostics, analysis, and decision-making in sophisticated systems.

By the end of the session, C# developers and architects will have a deep understanding of the concepts and methodologies driving this paradigm shift. They will leave equipped with the tools and knowledge to harness Semantic Kernel and its capabilities, bridging the gap between conventional programming and the dynamic, AI-powered future of software development.

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Community Days | Azure AI Connect - Global AI Bootcamp