AI Con USA 2026 - Machine Learning
Sunday, June 7
Fundamentals of AI—ICAgile Certification (ICP-FAI)
Monday, June 8
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...
A Quality Engineering Introduction to AI and Machine Learning
Although there are several controversies and misunderstandings surrounding AI and machine learning, one thing is apparent — people have quality concerns about the safety, reliability, and trustworthiness of these types of systems. Not only are ML-based systems shrouded in mystery due to their largely black-box nature, they also tend to be unpredictable since they can adapt and learn new things at runtime. Validating ML systems is challenging and requires a cross-section of knowledge, skills, and experience from areas such as mathematics, data science, software engineering, cyber-security,...
Tuesday, June 9
This Is Our Agent, We Make the Call
Agents! 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 10
Beyond Generative AI: How Large Quantitative Models Are Transforming Scientific Discovery
PreviewScientific discovery faces a major bottleneck: while generative AI has transformed information processing, it has not yet unlocked comparable acceleration in understanding the physical world. Traditional computational chemistry and materials modeling remain too slow, expensive, and limited to power large-scale innovation. SandboxAQ tackled this challenge by developing Large Quantitative Models (LQMs) — a new class of AI models that merge machine learning, physics-based simulation, and quantum-inspired algorithms to model molecular and material interactions at unprecedented speed and...
Preparing for the Age of Physical AI: How Robot Learning Is Reshaping Manual Labor
Advances in robot learning and affordable general-purpose hardware are changing physical work faster than any past wave of automation. Industrial robot arms transformed repetitive factory tasks, but they could only operate in tightly controlled settings. Now, new learning methods and off-the-shelf mobile robots make it possible to teach machines to perform many kinds of hands-on work in warehouses and logistics facilities. This session looks at where the technology stands today, what has changed, and what the next few years will bring. Attendees will learn how to spot real opportunities...