Presented by the Pittsburgh Technology Council and CGI, the 2024 Beyond Big Data: AI/Machine Learning Summit provided a unique opportunity for participants on every level to learn more about the opportunities and challenges of data analytics, artificial intelligence, and machine learning across multiple industries and practices.
The summit highlighted the transformative power of these technologies in empowering businesses, solving complex challenges, and enhancing productivity. Leaders from different industries are leveraging these technologies to make better business decisions, improve efficiency, better connect to customers, and so much more. However, navigating through the vast amount of data and understanding the hype around these technologies can be a challenge, which is why the Beyond Big Data Summit seeks to provide insights and best practices in these areas.
Manoj Mishra, Senior Vice President at CGI, kicked off the summit providing a state of the industry address for the AI industry. followed by a fireside chat with world renowned AI expert Andrew Moore. Moore is the founder of Lovelace AI, a new startup currently in stealth mode, dedicated to providing AI to support national security missions. Prior to Lovelace, Andrew spent his career in roles within Google and within Carnegie Mellon University.
The full-day summit explored insights from local and national leaders across panel discussions focusing on generative AI use cases, implications of big data and cutting-edge appliactions. Break out sessions included a plethoras of topics ranging from the future of work to aplied machine learning/artificila intelligence. Carolyn Ujcic, Director of AI Services at Google Cloud Consulting, provided the lunch keynote address exploring how we must ensure that AI ensures privacy and safety above all.
Andrew Moore, Lovelace AI
Fireside Chat with Audrey Russo
Andrew Moore is the founder and CEO of Lovelace AI. Lovelace is a new startup currently in stealth mode, dedicated to providing AI to support national security missions. Prior to Lovelace, Andrew spent his career in roles within Google and within Carnegie Mellon University. He was General Manager and VP for the AI division of Google Cloud, responsible for products such as Vertex AI platform, Contact Center AI, Anti-Money Laundering AI, Vertex AI Computer Vision Suite, and AI applications in logistics. Before that, Andrew was Dean of the School of Computer Science at CMU, and prior to his deanship, he founded the Google Pittsburgh office.
Carolyn Ujcic, Google
Lunch Keynote Address
Carolyn Ujcic is a compassionate leader with hands-on experience in AI, ML, and digital transformation. She is currently the Director of AI Services at Google Cloud Consulting, where she leads a dynamic team of AI consultants and engineers who help customers adopt AI in the enterprise. Throughout her 13+ years at Google, she has held positions of increasing responsibility including AI Consultant, Machine Learning Strategic Cloud Engineering Manager, and Machine Learning Global Practice Lead. Prior to Google, she served as a management consultant for multinationals at Accenture.
John Kalafut, Asher Orion Group
Tech Talk - Assessing and Tracking Hidden Stratification - The Importance of Sub-Group Analyses of your AI/ML Training and Run-Time Data
Hidden stratification is a phenomenon that affects the robustness and generalizability of machine learning-based AI. It occurs when the performance of an AI or ML model varies across different subgroups of data that are not well represented or balanced in the training dataset. This can lead to performance gaps, spurious correlations, and biases that may not be detected by testing with a large, heterogeneous dataset. In this presentation, I will explain the importance of sub-group analysis and edge-case testing of AI and ML models during external validation.
Andy Hannah, 1486 Labs
Tech Talk: Maximizing the Value of the External Data that Powers AI/Analytics Engine
The market for third-party data/external data could be well over $1 Trillion today growing to $3 Trillion by the end of the decade. This data, along with first-party data, fuels the analytic engines that solve problems and open opportunities for companies and organizations looking to gain value from AI, advanced analytics (e.g., predictive and prescriptive analytics).
Research conducted by 1486 Labs uncovered that there are significant issues with buying and using such data including:
Shayna Robinson, Circle of Friends
Tech Talk: What Keeps Hidden Workers Hidden
Technology is powerful as it is often aimed to help increase flexibility and automation while decreasing administrative burdens. But what happens when the very technology that is supposed to increase efficiency decreases visibility of quality talent? It makes you question if there is really a talent shortage or shortage of resources to tap into hidden talent.
Panel Discussion: AI on the Cutting Edge
On this panel, we’ll hear from research and industry about the what’s next for AI and ML. We’ll hear from leading experts on what we may see in the next 5-10 years and the challenges that we need to overcome to make the future a reality.
Implications of Big Data, Predictive Analytics and AI
This panel will discuss the many opportunities that have been created by Big Data and AI, the obstacles facing industry and the public. We’ll discuss how companies are managing data use within their organizations and where we need guide rails. As the next big technological leap, it’s clear that AI is changing our world. This panel discussion will delve into the profound implications of Big Data, Analytics and AI, exploring the multifaceted impacts these technologies have on our society, businesses, and daily lives.
Shannon Gregg, Cloud Adoption Services
Tech Talk: Managing the Change: Building an AI-Ready Culture
AI is here, and it is lurking around your organization. But are your people, processes, and tech stack ready? In this session, learn academic theory and then practical tactics to ensure your organization is AI- ready. Using the Lewin Change Management Theory as a basis, and applying the OCAI Culture Tool to the Group Decision Support System tool will allow participants to establish a baseline of the organization. Attendees will be informed on how to use the CATM approach and how to apply it to understand their organization's ability to be AI-ready.