Veronika Kolesnikova
Senior Software Engineer, Microsoft MVP (AI)
Boston, Massachusetts, United States
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Software engineer by day and AI enthusiast by night. Veronika has extensive experience in full-stack development using C#, .NET, Java and Typescript, Azure and AWS clouds. Public speaker, hackathon volunteer, co-organizer of Boston Azure user group, and mentor. Curious about mobile and Augmented Reality.
Veronika holds a master's degree in Information Technology. She likes dancing, traveling and practicing aerial fitness in her free time.
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Responsible AI and Content Safety
Nowadays with the development of AI, it became a big part of our lives. It started with statistics, so was focused mostly on numbers: precision, recall, etc. But at some point, it became obvious lots of AI models were missing something very important: responsibility.
Content Safety got everyone's attention with increasing popularity of Generative AI. How to protect both inputs and outputs? What can be done other than prompt engineering? Content Safety detects harmful user-generated and AI-generated content in applications and services and can help you with putting guardrails around your Generative AI models.
Let's discuss the principles of Responsible AI and some tools to support AI developers. In this session we will talk about AI and ML in general, data preparation, Responsible AI and Content Safety principles and tools. In the end, I will show a demo using some of the tools supported by Azure AI.
Langchain vs prompt engineering: real life observations
Langchain and similar open source frameworks for building language model based applications are probably as popular as those language models: ChatGPT, GPT-4, etc. But how approachable and useful those frameworks are? At the same time prompt engineering presented as something that can be easily implemented, used by non-developers and developers alike and light-weight. How powerful is it?
Let's talk about scenarios when it's better to use Langchain and when a good prompt can be enough. I will use my personal projects as examples, and the attendees are welcome to share their experience as well.
Azure OpenAI in the heart of your smart bot
If you heard about ChatGPT – one of the most popular artificial intelligence platforms in the world right now, you heart about OpeAI. Azure is making it more accessible and adding all the benefits of the cloud to it. Let’s figure out what’s hiding behind all the hype.
You will learn about the core components of a chatbot and how Azure supports these components with its AI and machine learning capabilities. The talk will also showcase how OpenAI can be integrated into Azure-powered chatbots to add even more advanced features such as natural language processing, sentiment analysis, and recommendation engines.
In this session we’ll talk about general concepts of artificial intelligence, OpenAI offerings and machine learning models you can access using Azure OpenAI service. Then you'll learn about bot design and development tricks, tools and services to make your bot user appealing. In the end you'll see how to start developing a completely custom bot backed up by Azure OpenAI service.
Responsible AI
Nowadays with the development of AI, it became a big part of our lives. It started with statistics, so was focused mostly on numbers: precision, recall, etc. But at some point, it became obvious lots of AI models were missing something very important: responsibility.
Microsoft came up with basic principles of Responsible AI and provided some tools to support AI developers. In this session we will talk about AI and ML in general, data preparation and Responsible AI principles and tools. In the end, I will show a demo using some of the tools inside Azure ML.
Machine Learning for .NET developers
Machine Learning is the future and it's already here. There’re so many opportunities for developers to include it in a wide variety of applications. If you heard a lot about data collection and processing, creating and training models and ready to try it all yourself with the help of .NET, I'll show you where to start. Your first completely functional ML.NET project won't take too long to create. In this session we'll talk about the specifics of ML.NET, its applications and see how Auto ML can be a good starting point.
KCDC 2023 Sessionize Event
Festive Tech Calendar 2022 Sessionize Event
TechBash 2022 Sessionize Event
Visual Studio Live! New Orleans, Boston & Microsoft HQ 2019 Sessionize Event
Xamarin Developer Summit Sessionize Event
Veronika Kolesnikova
Senior Software Engineer, Microsoft MVP (AI)
Boston, Massachusetts, United States
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