AI Con USA 2025 - Consultant
Customize your AI Con USA 2025 experience with sessions for consultants.
Monday, June 9
Getting Started with AI and Machine Learning
Are you a software professional who would like to learn to use AI and machine learning (ML), but don't know how to get started? One of the best ways to get into ML is by designing and completing small projects. Although you will ultimately need to understand the fundamentals of AI/ML, there's no reason why you can't learn foundational terms, concepts and principles as you put them into practice. Join Dionny Santiago as he introduces you to the world of applied machine learning. Dionny will guide you through a series of ML projects end-to-end, enabling you to gain experience with creating...
Beginning Data Analysis and Machine Learning with Jupyter Notebooks
In this beginner-friendly workshop you'll see how you can get started with data analytics and data science using Jupyter Notebooks. Matt will start with the basics of notebooks and then move on to using Python, Pandas, and NumPy to perform basic exploratory data analysis. See how you can use Plotly Express to create interactive charts and visuals with only a minimal amount of code. Once you've grasped the basics of understanding and visualizing the data Matt will move on to machine learning with SciKit-Learn as you train and evaluate predictive regression and classification models. The...
Get Your Data Ready for AI/ML
Understanding the readiness of your source data before you launch an expensive AI/ML project lets you take corrective data engineering measures that will streamline the project and give you the best probability of a successful outcome. Artificial Intelligence (AI) and Machine Learning (ML) projects can provide significant returns on investment when they are applied to narrow but difficult business problems and are supported by adequate amounts of relevant, quality data. Many such projects start with high hopes but get derailed due to fundamental problems with source data, which were...
Introduction to RAG Applications: Building Conversational AI for Domain-specific Search
NewThis beginner-friendly workshop introduces participants to the fundamentals of Retrieval-Augmented Generation (RAG) applications. Using a pre-configured Docker environment featuring Python, Elasticsearch for vector storage, and OpenAI as the LLM, attendees will learn how to build a RAG-powered conversational portal. Throughout the session, participants will create a RAG application to consume and query a sample dataset of Washington State regulation documents. Replace these sample documents with your own PDF files, and you’ll interact with your data in no time! By the end, attendees will...
Tuesday, June 10
Image Classification using LLMs and Transfer Learning
Large language models, like Generative Pre-trained Transformers (GPTs) to create textual content in ChatBots and other Generative AI applications, have garnered much attention recently. However, not all data is textual. Another important use of LLMs is for image processing to address real-world problems such as: real-time object recognition, classification of images, and generation of modern art. Jeffery Payne will explore how large language models for images (also known as visual language models - VLMs) can be used for image classification, object detection, image capture generation, and...
This Is Our Agent, We Make the Call
NewAgents! Finally, a term that might be even more over-hyped than AI! But what exactly are Agents, and more importantly, how do you use them? Where do Agents fit within the overall AI toolkit? What capabilities do they add, and what tasks can they help us perform? Dona and Jeremiah will help you gain a solid understanding of Agents and the fundamental components of an Agent-based AI system. You’ll learn key design principles for Agents, as well as when to leverage them and scenarios where they may not be the best choice. We'll cover how to identify business problems that are well-suited for...
Wednesday, June 11
Best Practices for Using AI for Structured Data Extraction
Structured data extraction, or data tagging, is one of the easiest and impactful applications of modern AI. Before the wide availability of pre-trained AI models, the process of “understanding” unstructured data either required constructing complex heuristic logic or investing in a machine learning team who could train models in-house. Now, cheap and powerful tagging machines are an API call away, redefining what is possible for how we can understand our data. In this talk, I'll share how we’ve used AI at Yahoo News to improve our content understanding pipelines. Yahoo was a pioneer in...
The Impact of AI on Developer Productivity
Generative AI tools hold promise to increase human productivity. In the world of software development, GitHub Copilot was one of the first practical applications of the use of generative AI to support developer productivity. However, measuring software productivity is non-trivial. For example, developer productivity gains is more than just producing code faster. If these artifacts don’t meet quality standards or themselves bring cost efficiency challenges then there may not be much overall improvement. To truly understand the benefits and challenges of AI-powered copilots requires real-...
Test Machina: Demystifying AI-Driven Testing Agents
Software vendors and practitioners are using artificial intelligence (AI) and machine learning (ML) to create a new wave of test automation tools. Such tools leverage autonomous and intelligent agents to explore, model, reason and learn about a software product. But how do these testing agents really work? Is this technology any good? And can we really trust them to validate software? Tariq King will introduce you to the world of agentic AI and discuss its benefits, challenges and other limitations. Learn how AI test agents use AI/ML technologies to mimic human testing activities such as...
Powering Complex Solutions with Agentic Systems
This session explores the revolutionary potential of agentic systems—autonomous agents equipped with diverse tools to tackle multifaceted tasks effectively. By integrating tools, agentic workflows enable intelligent, adaptive solutions to complex challenges. Apurva will start with an introduction to agentic systems, highlighting their ability to utilize various tools dynamically to achieve goals with minimal human intervention. Through real-world case studies, she will demonstrate how tools like APIs, databases, and external services are orchestrated within these systems to simulate...
Operationalizing Disruptive Technologies: A Strategic Framework for Harnessing the Power of GenAI
The advent of disruptive technologies, particularly in artificial intelligence, has ushered in a new era of possibilities and challenges. This talk proposes a comprehensive framework for operationalizing disruptive technologies, specifically focusing on the transformative potential of Generative Artificial Intelligence (GenAI). As organizations grapple with integrating GenAI into their operations, there is a pressing need for a structured approach that addresses technical, ethical, and organizational considerations. Mary will delve into a strategic framework designed to guide businesses in...
AI for Real People—Panel
We have heard a LOT of hype about AI and AGI and ASI and all of the nonsense. But in year 3 of Generative AI, people are actually moving beyond talking and finding real value in AI. Come and hear from REAL AI implementers about how AI is having an impact on businesses across the board including small businesses, non-profits, big companies, and more.
Thursday, June 12
AI at Scale: Balancing innovation, governance, and risk in large organizations
As AI reshapes industries, large organizations must scale innovation while upholding governance, security, and ethical responsibility. Deploying AI at scale isn’t just a technical challenge—it’s a strategic balancing act between agility and compliance, risk and reward. Andreas Bohman, CIO at the University of Washington, will discuss strategies to drive AI-powered innovation without compromising regulatory obligations, operational effectiveness, or public trust. He will share governance strategies that enable innovation rather than restrict it. He’ll also talk about addressing critical...
Mastering Quality Engineering in the Age of AI
PreviewAI is transforming the software quality engineering industry by automating routine tasks and enabling smarter testing approaches. Its integration into software development has profoundly reshaped the field of Quality Engineering (QE). This presentation explores the evolving role of QE in the AI era, addressing the challenges, opportunities, and strategies for achieving excellence in AI-driven environments. By examining the intersection of AI and QE, it provides valuable insights into best practices for maintaining high-quality software and equips QE professionals with the knowledge...
Continuous Testing for AI Applications
In the era of artificial intelligence, software testing has evolved from a finite phase in development to an ongoing, dynamic process of monitoring. Unlike traditional deterministic systems, AI-driven applications operate probabilistically, introducing variability and uncertainty in outputs even with consistent inputs. This paradigm shift requires a rethinking of testing strategies, moving towards continuous monitoring to ensure performance, fairness, and reliability in production environments. This session will explore how QA teams can integrate AI-specific methods, anomaly detection, and...
Brewing Better Technology: How Human Insights Enhance AI Capabilities
PreviewStriking the right balance between the efficiency of artificial intelligence (AI) and the nuanced insight of human interaction is crucial. The motivation behind integrating AI in development and testing is to enhance decision-making and productivity through automation. However, solely relying on AI can overlook critical elements that only human testers can provide, such as emotional intelligence and contextual understanding. To illustrate this dynamic, Emma Pyne will use the analogy of AI as coffee brewing machines and human testers as skilled baristas in Seattle's coffee shops. AI...